JP2006154121A - Fingering information generating device and fingering information generation processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To realize a fingering information generating device that generates fingering information on easy-to-play fingering while taking the positions of hands moving according to music progress into consideration. <P>SOLUTION: Breaks of keying operation is detected from musical piece data MidiEvent representing respective sounds constituting the music, phrase data Phrase specifying respective sections defined by the detected breaks is generated, and the positions of the hands are set by the sections that the generated phrase data Phrase specifies according to an operation range determined by the key position of the highest pitch and the key position of the lowest pitch wherein keys are operated in the sections. Fingering data are generated which allocate the finger closest to a key to be played among respective fingers operating keys corresponding to the set positions of the hands. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a fingering information generation apparatus and a fingering information generation processing program suitable for use in an electronic musical instrument having a keyboard.

  2. Description of the Related Art There is known an apparatus that generates fingering information that guides a performer to use a finger (fingering) when operating a key. For example, in Patent Literature 1, two-finger fingering data representing ease of finger use when operating the keyboard for two adjacent sounds is stored in association with each combination of fingers. The two-finger fingering data corresponding to the song data (sound string of the given melody) is read from within, and the fingering information is generated by determining the fingering that optimizes the accumulated value of the read two-finger fingering data An apparatus is disclosed.

Japanese Patent No. 2526954

By the way, in the apparatus disclosed in the above-mentioned patent document 1, in order to generate a representative fingering that is uniquely determined from the song data, it is easy to play the finger using a finger that is easy to play while considering the position of the hand moving as the song progresses. There is a problem that finger information cannot be generated.
Therefore, the present invention has been made in view of such circumstances, and fingering information generation that can generate fingering information for easy fingering while considering the position of a hand that moves according to the progress of a song. An object is to provide a device and a fingering information generation processing program.

  In order to achieve the above object, according to the first aspect of the present invention, the phrase data that detects the break of the key operation from the song data representing each sound constituting the song and designates each section delimited by the detected break Data is generated by the phrase data generating means, the setting means for setting the position of the most suitable hand for the key operation for each section specified by the phrase data generated by the phrase data generating means, and the setting means Fingering data generating means for generating fingering data assigned to the finger to be played among the fingers to be operated by keys corresponding to the position of the hand that is to be played. To do.

  In the invention according to claim 2, phrase data generating means for detecting a break of an operation of performing a key operation from music data representing each sound constituting the music and generating phrase data for designating each section delimited by the detected break Corresponding to the operation range determined by the key position of the highest pitch and the key position of the lowest pitch for each section specified by the phrase data generated by the phrase data generation means Setting means for setting the position of the hand, and fingering data assigned to the finger to be played the finger closest to the key to be played among the fingers to be operated by keys corresponding to the position of the hand set by the setting means And fingering data generation means for generating

  In the invention according to claim 3, phrase data generating means for detecting a break of an operation of performing a key operation from music data representing each sound constituting the music and generating phrase data for designating each section delimited by the detected break Corresponding to the operation range determined by the key position of the highest pitch and the key position of the lowest pitch for each section specified by the phrase data generated by the phrase data generation means A setting means for setting the position of the hand that has been operated, and of each finger that is key-operated corresponding to the position of the hand set by the setting means, the finger position is positioned on the lower side than the key to be played, and the key pressing operation And fingering data generating means for generating fingering data assigned to the finger to be played.

  In the invention according to claim 4, phrase data generating means for detecting a break in the operation of key operation from music data representing each sound constituting the music and generating phrase data for designating each section delimited by the detected break And motion data generating means for generating motion data representing the position of the hand performing the music from the music data, and for each section specified by the phrase data generated by the phrase data generating means, the motion corresponding to that section Of the fingers that are operated by keys at the position of the hand represented by the data, the finger position is positioned lower than the key to be played, and the fingering data that is assigned to the finger to be played by the finger that has not been pressed is generated. And finger data generation means.

  In the invention according to claim 5, phrase data generating means for detecting a break of an operation of performing a key operation from music data representing each sound constituting a song and generating phrase data for designating each section delimited by the detected break And motion data generating means for generating motion data representing the position of the hand performing the music from the music data, and for each section specified by the phrase data generated by the phrase data generating means, the motion corresponding to that section Fingering data generating means for generating fingering data assigned to the finger to be played among the fingers to be operated at the position of the hand represented by the data, the finger closest to the key to be played is provided.

  In the invention according to claim 6, phrase data generating means for detecting a break of an operation of performing a key operation from music data representing each sound constituting the music and generating phrase data for designating each section delimited by the detected break And motion data generating means for generating motion data representing the position of the hand performing the music from the music data, and for each section specified by the phrase data generated by the phrase data generating means, the motion corresponding to that section Of the fingers that are operated by keys at the position of the hand represented by the data, the finger position is positioned lower than the key to be played, and the fingering data that is assigned to the finger to be played by the finger that has not been pressed is generated. Fingering that evaluates the difficulty of fingering according to the separation distance between the finger specified by the finger data generating means and the fingering data generated by the fingering data generating means and the key to be played And an optimization means for optimizing the operation data so that the difficulty of fingering evaluated by the fingering evaluation means falls within a preset allowable range. To do.

  In the invention according to claim 7, phrase data generating means for detecting a break of an operation for performing a key operation from music data representing each sound constituting the music and generating phrase data for designating each section delimited by the detected break And motion data generating means for generating motion data representing the position of the hand performing the music from the music data, and for each section specified by the phrase data generated by the phrase data generating means, the motion corresponding to that section Fingering data generating means for generating fingering data assigned to the finger to be played among the fingers to be operated at the hand position represented by the data, the finger closest to the key to be played, and generated by the fingering data generating means The fingering evaluation means for evaluating the difficulty of playing the finger according to the separation distance between the finger specified by the fingering data and the key to be played, and evaluated by the fingering evaluation means Playing difficulty of fingering, to fit in the allowable range set in advance, it is characterized by comprising the optimization means for optimizing the operation data.

  In the invention according to claim 8, phrase data generation processing for detecting a break of an operation of performing a key operation from music data representing each sound constituting a song and generating phrase data specifying each section delimited by the detected break And a setting process for setting an optimum hand position for key operation for each section specified by the phrase data generated by the phrase data generation process, and a hand position set by the setting process Then, a fingering data generation process for generating fingering data assigned to the finger to be played among the fingers to be operated by the key closest to the key to be played is executed by the computer.

  According to the ninth aspect of the present invention, phrase data generation processing for detecting a break of an operation for performing a key operation from music data representing each sound constituting a song and generating phrase data for designating each section delimited by the detected break And for each section specified by the phrase data generated by the phrase data generation process, the operation range determined by the key position of the highest pitch and the key position of the lowest pitch that are key-operated in that section A setting process for setting the position of the hand, and fingering data assigned to the finger to be played among the fingers to be operated by keys corresponding to the position of the hand set by the setting process. And a fingering data generation process for generating the data.

  In the invention according to claim 10, phrase data generation processing for detecting a break of an operation of performing a key operation from music data representing each sound constituting a song and generating phrase data for designating each section delimited by the detected break And for each section specified by the phrase data generated by the phrase data generation process, the operation range determined by the key position of the highest pitch and the key position of the lowest pitch that are key-operated in that section A setting process for setting the position of the hand that has been placed, and of each finger that is key-operated corresponding to the position of the hand set by the setting process, the finger position is positioned on the lower side of the key to be played and the key-pressing operation A fingering data generation process for generating fingering data assigned to a finger to be played with a finger that has not been played is executed by a computer.

  In the invention of claim 11, phrase data generation processing for detecting a break of an operation of key operation from music data representing each sound constituting a song and generating phrase data for designating each section delimited by the detected break And motion data generation processing for generating motion data representing the position of the hand performing the music from the music data, and for each section specified by the phrase data generated by the phrase data generation processing, the operation corresponding to that section Of the fingers that are operated by keys at the position of the hand represented by the data, the finger position is positioned lower than the key to be played, and the fingering data that is assigned to the finger to be played by the finger that has not been pressed is generated. The finger data generation process is executed by a computer.

  In the invention described in claim 12, the phrase data generation processing for detecting the break of the key operation from the song data representing each sound constituting the song and generating the phrase data for designating each section delimited by the detected break And motion data generation processing for generating motion data representing the position of the hand performing the music from the music data, and for each section specified by the phrase data generated by the phrase data generation processing, the operation corresponding to that section A fingering data generation process for generating fingering data assigned to the finger to be played among the fingers to be operated by keys at the position of the hand represented by the data is performed by a computer. To do.

  In the invention according to claim 13, phrase data generation processing for detecting a break of an operation of performing a key operation from music data representing each sound constituting a song and generating phrase data designating each section delimited by the detected break And motion data generation processing for generating motion data representing the position of the hand performing the music from the music data, and for each section specified by the phrase data generated by the phrase data generation processing, the operation corresponding to that section Of the fingers that are operated by keys at the position of the hand represented by the data, the finger position is positioned lower than the key to be played, and the fingering data that is assigned to the finger to be played by the finger that has not been pressed is generated. A finger data generation process and an operation for evaluating the difficulty of fingering according to the separation distance between the finger specified by the fingering data generated by the fingering data generation process and the key to be played. Causing the computer to execute an evaluation process and an optimization process for optimizing the motion data so that the fingering difficulty evaluated by the fingering evaluation process falls within a preset allowable range. Features.

  According to the fourteenth aspect of the present invention, phrase data generation processing for detecting a break in the operation of key operation from music data representing each sound constituting a song and generating phrase data specifying each section delimited by the detected break And motion data generation processing for generating motion data representing the position of the hand performing the music from the music data, and for each section specified by the phrase data generated by the phrase data generation processing, the operation corresponding to that section Generated by fingering data generation processing for generating fingering data assigned to the finger to be played with the finger closest to the key to be played among the fingers operated by keys at the position of the hand represented by the data, and generated by the fingering data generation processing Fingering evaluation means for evaluating the difficulty of fingering according to the separation distance between the finger specified by the fingering data and the key to be played, and evaluated by the fingering evaluation means. Luck playing difficulty of fingers is to fit in the allowable range set beforehand, characterized in that to perform the optimization process for optimizing the operation data in the computer.

  According to the first and eighth aspects of the present invention, a break of a key operation is detected from music data representing each sound constituting a song, and phrase data specifying each section delimited by the detected break is generated. For each section specified by the phrase data, an optimal hand position for key operation is set. Since fingering data assigned to the finger to be played among the fingers to be operated by keys corresponding to the set hand position is assigned to the finger to be played, the hand moving as the music progresses is generated. It is possible to generate fingering information for fingering that is easy to play while considering the position of the finger.

  According to the second and ninth aspects of the invention, the break of the operation of key operation is detected from the music data representing each sound constituting the music, and the phrase data specifying each section delimited by the detected break is generated. For each section specified by the phrase data, a hand position corresponding to the operation range determined by the key position of the highest pitch and the key position of the lowest pitch that are key-operated in the section is set. Since fingering data assigned to the finger to be played among the fingers to be operated by keys corresponding to the set hand position is assigned to the finger to be played, the hand moving as the music progresses is generated. It is possible to generate fingering information for fingering that is easy to play while considering the position of the finger.

  According to the third and tenth aspects of the present invention, a break of the key operation is detected from the music data representing each sound constituting the music, and phrase data specifying each section delimited by the detected break is generated. For each section specified by the phrase data, a hand position corresponding to the operation range determined by the key position of the highest pitch and the key position of the lowest pitch that are key-operated in the section is set. Of the fingers that are key-operated in accordance with the set hand position, the finger position is located lower than the key to be played and the finger that has not been pressed is assigned to the finger to be played. Since the data is generated, it is possible to generate fingering information for fingering that is easy to play while considering the position of the moving hand as the music progresses.

  According to invention of Claim 4, 11, the break of the operation | movement which carries out key operation is detected from the music data showing each sound which comprises music, and the phrase data which designates each area divided by the detected break is produced | generated. At the same time, motion data representing the position of the hand performing the music is generated from the music data. Then, for each section specified by the phrase data, among the fingers that are key-operated at the position of the hand represented by the operation data corresponding to that section, the finger position is located on the lower side than the key to be played, and the key pressing operation Since fingering data assigned to a finger to be played is generated, fingering information for easy fingering can be generated while taking into account the position of the moving hand according to the progress of the music.

  According to the fifth and twelfth aspects of the present invention, the break of the key operation is detected from the music data representing each sound constituting the music, and the phrase data specifying each section delimited by the detected break is generated. At the same time, motion data representing the position of the hand performing the music is generated from the music data. For each section specified by the phrase data, fingering data assigned to the finger to be played is the finger closest to the key to be played among the fingers to be operated at the position of the hand represented by the motion data corresponding to the section. Therefore, it is possible to generate fingering information for fingering that is easy to play while considering the position of the hand moving as the music progresses.

  According to the invention described in claims 6 and 13, the break of the operation of key operation is detected from the music data representing each sound constituting the music, and the phrase data specifying each section delimited by the detected break is generated. At the same time, motion data representing the position of the hand performing the music is generated from the music data. Then, for each section specified by the phrase data, among the fingers that are key-operated at the position of the hand represented by the operation data corresponding to that section, the finger position is located on the lower side than the key to be played, and the key pressing operation When the fingering data assigned to the finger to be played is generated, the difficulty of fingering is evaluated according to the separation distance between the finger specified by this fingering data and the key to be played. Since the motion data is optimized so that the difficulty of playing the fingering is within the preset allowable range, the fingering information for fingering that is easy to play while considering the position of the moving hand as the song progresses Can be generated.

  According to the seventh and fourteenth aspects of the present invention, the break of the key operation is detected from the music data representing each sound constituting the music, and the phrase data specifying each section delimited by the detected break is generated. At the same time, motion data representing the position of the hand performing the music is generated from the music data. For each section specified by the phrase data, fingering data assigned to the finger to be played is the finger closest to the key to be played among the fingers to be operated at the position of the hand represented by the motion data corresponding to the section. Is generated, the difficulty of fingering is evaluated according to the distance between the finger specified by the fingering data and the key to be played, and the evaluated difficulty of fingering is set in advance. Since the operation data is optimized so as to be within the range, fingering information for easy fingering can be generated while taking into account the position of the moving hand as the music progresses.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
[First Embodiment]
A. Constitution
FIG. 1 is a block diagram showing the overall configuration of the fingering information generating device according to the first embodiment. The fingering information generation device includes a CPU 1, a ROM 2, a RAM 3, an input unit 4, a display unit 5, and a MIDI interface 6. In accordance with an instruction from the input unit 4 to be described later, the CPU 1 fetches “music data” in the SMF format from the electronic musical instrument 7 through the MIDI interface 6 and stores it in the RAM 3, and then performs time-series data generation processing and sound strings. Analysis processing is executed to derive “time series data” and “phrase data” from “music data”. In addition, the CPU 1 executes fingering data generation processing, refers to “time series data” and “phrase data”, and considers the position of the hand moving according to the progress of the song. Data "is generated. The configuration of these series of data and their intended purpose will be described in detail later.

  The ROM 2 stores various control programs and tables that are loaded into the CPU 1. The various control programs referred to here include a main routine including the above-described time-series data generation process, sound string analysis process, and fingering data generation process. The RAM 3 temporarily stores buffer data representing the state of the hand, etc., in addition to various register / flag data used in the main routine (time series data generation processing, sound string analysis processing, and fingering data generation processing) executed by the CPU 1. And a data area for storing the above-described series of data (music data, time series data, phrase data, hand state data). The main data structure stored in the RAM 3 will be described later.

  The input unit 4 generates an operation event corresponding to the user operation and supplies it to the CPU 1. Specifically, for example, an event for instructing the RAM 3 to take “music data” in the SMF format from the electronic musical instrument 7 via the MIDI interface 6 is supplied to the CPU 1, or based on “music data” stored in the RAM 3. The CPU 1 is supplied with an event for instructing execution of a main routine for generating “fingering data”. Under the control of the CPU 1, the display unit 5 displays, for example, music data as a score, and also displays fingering data corresponding to each sound constituting the music data in the displayed score.

B. Data Configuration Next, the configuration of various data (on-buffer data, music data, time series data, note data, phrase data, and hand state data) stored in the RAM 3 will be described with reference to FIGS.

(1) Configuration of On-Buffer Data FIG. 2 is a diagram showing a configuration of on-buffer data OnBuf [0] to [N] provided in the work area of the RAM 3. One on-buffer data OnBuf is data representing each sound read in accordance with the progress of the music when the music data is played (automatic performance). The sound generation start time lTime, the mute time lOffTime, the pitch Pitch (note number) ), And a pointer pNote for designating corresponding music data.

(2) Configuration of Music Data MidiEvent FIG. 3 is a diagram showing a configuration of music data provided in the data area of the RAM 3. The music data MidiEvent represents each sound constituting the music, and END data is provided at the end of the music. The music data MidiEvent includes a sound generation start time ITime, a tone length lGate, a pitch Pitch, and a pointer pNext that designates the next music data MidiEvent.

(3) Configuration of Time Series Data NoteGroup FIG. 4 is a diagram showing a configuration of time series data provided in the data area of the RAM 3. The time-series data NoteGroup is data obtained by searching for sounds (chords or non-harmonic sounds) that are simultaneously generated from the music data MidiEvent and collecting the corresponding sounds together.
In the time series data NoteGroup, the sound generation start time lTime, the mute time lTerm, the keyboard coordinate maximum value iPosMax, the keyboard coordinate minimum value iPosmin, the coordinate difference iTend, the difference are shown as the attributes representing the sound generation / mute timing and pitch relation of simultaneously sounding sounds. It has a change continuation value iTendCont, a difference change continuation step iTendStep, a neighborhood data maximum value iNPosMax, a neighborhood data minimum value iNPosmin, a pointer NoteEv, a pointer next, and a pointer prev.
The pointer NoteEv is a pointer for designating note data Note corresponding to the time series data NoteGroup. The pointer next and the pointer prev are pointers that specify the next time series data and the previous time series data, respectively.

(4) Configuration of Note Data Note FIG. 5 is a diagram showing a configuration of note data provided in the data area of the RAM 3. The note data Note is data representing music data MidiEvent corresponding to each of the simultaneously sounding sounds that are grouped as time-series data NoteGroup, and includes pointer pEvent, keyboard coordinates iPos, fingering number cfig (fingering data And a pointer next and a pointer prev.
The pointer pEvent is a pointer that designates corresponding music data MidiEvent. The pointer next is a pointer for designating the next note data. The pointer prev is a pointer that designates the previous note data.

(5) Configuration of Phrase Data Phase FIG. 6 is a diagram showing a configuration of phrase data provided in the data area of the RAM 3. The phrase data Phase is data that detects a section delimited by rests from the music data MidiEvent as a break of the key operation, and represents the start / end time of the section. The start time lTime, the end time lTerm The keyboard coordinate maximum value iPosMax in the phrase, the keyboard coordinate minimum value iPosmin in the phrase, the pointer NoteEv, the pointer next, and the pointer prev.
The pointer NoteEv is a pointer that designates note data Note corresponding to the phrase data. The pointer next and the pointer prev are pointers that specify the next phrase data and the previous phrase data, respectively.

(6) Configuration of Hand Status Data Hand FIG. 7 is a diagram showing a configuration of hand status data provided in the work area of the RAM 3. The hand state data Hand includes an identification flag iRL for identifying a hand to be operated by a key (indicating a right hand when “0” and a left hand when “1”), a hand position coordinate iPos, and a keyboard coordinate maximum value iPosMax. , Keyboard coordinate minimum value iPosmin, thumb data fig [0], index finger data fig [1], middle finger data fig [2], ring finger data fig [3], and little finger data fig [4].
Each finger data fig [0] to [4] includes a state flag status, a previous state flag statprev, a pointer event, and a finger coordinate iPos.
The status flag “status” indicates a mute state when “0”, and indicates that the key is being depressed when “1”. The previous state flag statprev indicates a mute state when “0”, and indicates that the key is being depressed when “1”. The pointer event designates the note data being pressed.

C. Operation Next, the operation of the first embodiment will be described with reference to FIGS. In the following, the operation of the main routine will be described on the assumption that the music data shown in FIG. 3 is stored in the data area of the RAM 3 via the MIDI interface 6.

(1) Operation of main routine When an event for instructing execution of the main routine is supplied from the input unit 4 to the CPU 1, the CPU 1 executes the main routine shown in FIG. Execute. As will be described later, in the time-series data generation processing, sounds that are simultaneously pronounced are searched from the music data MidiEvent, and the corresponding sounds are grouped together and provided with attributes representing the pronunciation / mute timing and pitch relationship. While generating the data NoteGroup, in addition to generating the note data Note representing the music data MidiEvent corresponding to the time series data NoteGroup, the start / interval of the section delimited by the rest of the key operation from the music data MidiEvent Phrase data Phase representing end time and the like is generated.

  Next, in step SA2, a sound string analysis process is executed. As will be described later, in the sound sequence analysis process, the maximum and minimum of pitch change are detected according to the pitch difference (maximum value difference iDH / minimum value difference iDL) between adjacent time-series data NoteGroup and the flag ifig. Or a processing operation for detecting the maximum value / minimum value of the neighborhood data, whereby the neighborhood data maximum value iNPosMax, the neighborhood data minimum value iNPosmin, the difference change continuation value iTendCont, and the difference change continuation step iTend of each time series data NoteGroup are performed. In addition, the keyboard coordinate maximum value iPosMax and keyboard coordinate minimum value iPosmin of the corresponding phrase data Phase are generated.

  Subsequently, in step SA3, fingering data generation processing is executed. As will be described later, in the fingering data generation process, it is first determined whether or not hand movement is necessary in the current phrase section. If hand movement is necessary, the neighborhood data maximum value iNPosMax in the current time series data NoteGroup is determined. The keyboard coordinate maximum value iPosMax and the keyboard coordinate minimum value iPosmin in the hand state data Hand are updated based on the minimum neighbor data iNPosmin and the middle finger coordinate Hand.iPos as the first hand position coordinate iPos (Hand.iPos). fig [2]. Set iPos.

  When the position of the first hand is determined, among the fingers of the hand to be operated by the key, the finger position is equal to or less than the coordinates of the key to be played, and the finger that has not been pressed is assigned as the finger to be played. After this allocation, it is determined again whether the next time-series data NoteGroup is before or after the break of the key operation, and if it is after the break of the key operation, it is determined whether or not the hand needs to be moved. If it is determined and the hand needs to be moved, the keyboard coordinate maximum value iPosMax in the hand state data Hand and the keyboard based on the neighborhood data maximum value iNPosMax and the neighborhood data minimum value iNPosmin in the next time-series data NoteGroup. After updating the minimum coordinate value iPosmin, the middle finger coordinate Hand.iPos is set as the position coordinate iPos (Hand.iPos) of the next hand. fig [2]. Set iPos. Thereafter, this processing operation is repeated for all the time series data NoteGroup to complete this processing.

(2) Operation of Time Series Data Generation Processing Next, the operation of time series data generation processing will be described in detail with reference to FIG. When this process is executed via step SA1 (see FIG. 8) of the main routine described above, the CPU 1 proceeds to step SB1 shown in FIG. 9 and resets the pointers me, ngr, nTmp, and phTmp to zero. Here, the pointer me is a pointer for designating the music data MidiEvent shown in FIG. The pointer ngr is a pointer that specifies the time-series data NoteGroup illustrated in FIG. The pointer nTmp is a pointer that designates the note data Note illustrated in FIG. The pointer phTmp is a pointer that designates the phrase data Phase shown in FIG.

In step SB2 and subsequent steps, time-series data NoteGroup, phrase data Phase, and note data Note are derived based on the attributes of the music data MidiEvent designated according to the progress of the pointer me.
As described above, the time-series data NoteGroup searches for sounds (chords or non-harmonic sounds) that are simultaneously pronounced from the music data MidiEvent, puts the corresponding sounds together, and relates to their pronunciation / mute timing and pitch. It is data with an attribute representing. The note data Note is data representing music data MidiEvent corresponding to each of the simultaneously sounding sounds that are grouped together as time-series data NoteGroup. Phrase data Phase is data that detects a section delimited by rests from the music data MidiEvent as a break between key operations, and represents the start / end time of the section.

  First, in step SB2, it is determined whether or not the music data MidiEvent designated by the pointer me advanced in step SB14 has reached the end END, that is, whether all the music data MidiEvent has been read. When the reading is completed, the determination result is “YES”, and this process is completed. If the reading is not completed, the determination result is “NO”, and the process proceeds to Step SB3. In step SB3, the sound generation start time ITime (me.ITime) in the music data MidiEvent designated by the pointer me is stored in the register lTprog.

  Subsequently, in step SB4, time-series data NoteGroup is formed based on each attribute of the music data MidiEvent designated by the pointer me. That is, the pointer nTmp is stored in the note data pointer NoteEv (ngr.NoteEv) in the time-series data NoteGroup designated by the pointer ngr. Further, the value of the register lTprog (the sounding start time ITime in the music data MidiEvent specified by the pointer me) is stored in the sounding start time lTime (ngr.lTime) in the time-series data NoteGroup specified by the pointer ngr. Furthermore, at the mute time lTerm in the time-series data NoteGroup specified by the pointer ngr, the sound generation start time ITime (me.ITime) in the music data MidiEvent specified by the pointer me and the music data MidiEvent specified by the pointer me The time obtained by adding the tone length lGate (me.lGate) is stored.

  In step SB4, the maximum value is stored in the keyboard coordinate maximum value iPosMax (ngr.iPosMax) in the time series data NoteGroup designated by the pointer ngr, and the minimum value is stored in the keyboard coordinate minimum value iPosmin (ngr.iPosmin). . Further, in step SB4, the pointer me specifying the music data MidiEvent is stored in the pointer pEvent (nTmp.pEvent) in the note data Note specified by the pointer nTmp.

  The maximum value / minimum value here refers to the keyboard coordinates (maximum value) corresponding to the highest pitch and the lowest pitch when there are multiple sounds that can be pronounced simultaneously. Indicates the coordinate (minimum value) of the keyboard corresponding to. Therefore, when the first music data MidiEvent is read, ngr. iPosMax and ngr. In iPosmin, the coordinates of the keyboard corresponding to the pitch Pitch of the music data MidiEvent are provisionally set. The keyboard coordinates are coordinates representing key positions in units of white keys with the white key of C4 sound on the keyboard as the origin.

Subsequently, in steps SB5 to SB9, phrase data Phase is created. In the first step SB5, the difference time between the mute time stored in the register lOffProg and the current sound generation start time ITime (me.ITime) is larger than a predetermined value, that is, a rest that becomes a break of the key operation. Determine the presence or absence.
At the time of reading the first music data MidiEvent, the mute time is not stored in the register lOffProg, so the determination result of this step SB5 is “NO”, and the flow proceeds to step SB10. In steps SB10 to SB14, as will be described later, since sounds that are simultaneously generated are combined into one time-series data NoteGroup, when the first music data MidiEvent is read, the determination result in step SB10 is “NO”. Thus, the process proceeds to step SB13.

  In step SB13, the sound generation start time lTime (ngr.lTime) in the time-series data NoteGroup designated by the pointer ngr is stored in the register lOffProg. Subsequently, in step SB14, in order to generate time series data NoteGroup from the next music data MidiEvent, the pointer pNext (me.pNext) in the music data MidiEvent designated by the current pointer me is updated to the next pointer me. Then, the process returns to step SB2 described above.

  Thereafter, steps SB2 to SB16 described above are repeated from the second piece of music data MidiEvent to the end of music data END. If a rest that becomes a break in the key operation in the process is found, the determination result in step SB5 is “YES”, and the process proceeds to step SB6. In step SB6, the register lOffProg is stored as the start time lTime (phTmp.lTime) in the phrase data Phase specified by the pointer phTmp, and the sound generation start time ITime in the music data MidiEvent specified by the current pointer me is Stored as the end time lTerm (phTmp.lTerm) in the phrase data Phase specified by the pointer phTmp.

  Subsequently, in step SB7, a pointer value indicating a phrase data empty position is set in the pointer phNew. Next, in step SB8, the pointer phNew is stored as the pointer next (phTmp.next) in the phrase data Phase specified by the pointer phTmp, and the pointer phTmp is stored in the pointer prev in the phrase data Phase specified by the pointer phNew. Store as. In this way, each time a rest that becomes a break of the key operation is detected, phrase data Phase indicating the start / end time of the section delimited by the detected rest is generated. .

When the generation of the phrase data Phase is thus completed, the CPU 1 advances the process to step SB10. As described above, in steps SB10 to SB14, a process of collecting simultaneously sounding sounds into one time-series data NoteGroup is executed.
That is, in step SB10, the absolute difference between the sounding start time ITime (contents of the register lTPProg) in the currently specified music data MidiEvent and the sounding start time ITime (me.next.lTime) in the next music data MidiEvent. Is smaller than a predetermined value, that is, whether the sound is a sound that is pronounced simultaneously (chord or non-harmonic sound). If it is not a sound that sounds simultaneously, the determination result is “NO”, and the process proceeds to step SB15 described above. If it is a sound that sounds simultaneously, the determination result is “YES” and the process proceeds to step SB11.

  In step SB11, the pointer pNext (me.pNext) in the music data MidiEvent designated by the pointer me is set to the pointer meHarm, and the pointer value indicating the empty position of the note data Note is set to the pointer nHarm. Next, in step SB12, as the sound that is simultaneously generated is detected, the mute time lTerm (ngr.lTerm), keyboard coordinate maximum value iPosMax (ngr.iPosMax), keyboard coordinates in the time-series data NoteGroup designated by the pointer ngr is detected. The minimum value iPosmin (ngr.iPosmin) is updated. In step SB12, the pointer nHarm is stored as the pointer next in the note data Note designated by the pointer nTmp, and the pointer nTmp is stored as the pointer prev in the note data Note designated by the pointer nHarm.

  As described above, in the time-series data generation processing, a plurality of sounds (chords and non-harmonic sounds) that are simultaneously pronounced are searched from among the music data MidiEvent sequentially read according to the progress of the pointer me, and the corresponding plurality of sounds are searched for. In summary, the time series data NoteGroup having attributes representing the pronunciation / mute timing and pitch relationship and the note data Note representing the music data MidiEvent corresponding to the time series data NoteGroup are generated, and the music data MidiEvent Phrase data Phase indicating the start / end time of the section delimited by rests that become the breaks of the key operation is generated.

(3) Operation of Sound String Analysis Process Next, the operation of the sound string analysis process will be described with reference to FIG. When this process is executed via step SA2 (see FIG. 8) of the main routine described above, the CPU 1 proceeds to step SC1 shown in FIG. 10, and specifies a pointer ngr for specifying time-series data NoteGroup and note data Note. The pointer nTmp, the pointer phTmp designating the phrase data Phase, and the search data number iTendCnt are reset to zero. Next, in step SC2, the keyboard coordinate maximum value iPosMax (ngr.iPosMax) and the keyboard coordinate minimum value iPosmin (ngr.iPosmin) in the first time-series data NoteGroup are stored in the registers iMax and imin, respectively.

Subsequently, in step SC3, it is determined whether or not the time series data NoteGroup designated by the pointer ngr is “NULL”, that is, whether or not the sound string analysis is completed. When the sound string analysis is completed, the determination result is “NO”, and this process is completed. Otherwise, the determination result is “YES”, and the process proceeds to step SC4.
In step SC4, the presence / absence of the previous time-series data NoteGroup is determined. If the time-series data NoteGroup designated by the pointer ngr is the first, the previous time-series data NoteGroup does not exist, so the determination result is “NO”, and the flow proceeds to Step SC6 described later. On the other hand, if the previous time-series data NoteGroup exists, the determination result is “YES”, and the flow proceeds to step SC5.

  In step SC5, the keyboard coordinate maximum value iPosMax (ngr.iPosMax) in the currently designated time-series data NoteGroup, the keyboard coordinate maximum value iPosMax (ngr.prev.iPosMax) in the previous time-series data NoteGroup, and Are stored in the register iDH. Hereinafter, the register iDH is referred to as a maximum value difference iDH. In step SC5, the keyboard coordinate minimum value iPosmin (ngr.iPosmin) in the currently designated time-series data NoteGroup and the keyboard coordinate minimum value iPosmin (ngr.prev.iPosmin) in the previous time-series data NoteGroup are specified. ) Is stored in the register iDL. Hereinafter, the register iDL is referred to as a minimum value difference iDL. Further, in step SC5, a flag ifig indicating whether the keyboard coordinate value is currently rising or falling is set according to the values of the register iDH and the register iDL. The flag ifig represents an increase when “1” and a decrease when “0”.

  In steps SC6 to SC9, the contents of the registers iMax and imin are updated. In the first pass, the keyboard coordinate maximum value iPosMax (ngr.iPosMax) in the first time-series data NoteGroup is stored in the register iMax, and the keyboard coordinate minimum value iPosmin (ngr.iPosmin) in the first time-series data NoteGroup is stored in the register imin. Since each is stored, it is not updated, but the value of the register iMax is set to ngr. If it is smaller than iPosMax, ngr. iPosMax is updated and registered in the register iMax (steps SC6 to SC7). Further, the value of the register imin is ngr. If it is smaller than iPosmin, ngr. iPosmin is updated and registered in the register imin (steps SC8 to SC9).

Next, in step SC10, the search data number iTendCnt is incremented and stepped. Subsequently, in step SC11, it is determined whether or not the maximum value difference iDH is 0 or more and the minimum value difference iDL is 0 or less.
In the first pass, since the maximum value difference iDH and the minimum value difference iDL are not calculated in step SC5 and are “0”, the determination result is “YES”, the process proceeds to step SC12, and the currently designated time-series data After storing “0” in the coordinate difference iTend (ngr.iTend) in the NoteGroup, the process proceeds to step SC18.

In step SC18, neighborhood data processing is executed. In the neighborhood data processing, as will be described later, the keyboard coordinate maximum value iPosMax and keyboard coordinate minimum value iPosmin of the neighborhood time-series data NoteGroup are included in the currently designated time-series data NoteGroup, the neighborhood data maximum value iNPosMax, and neighborhood data. Store as the minimum value iNPosmin.
Subsequently, in step SC19, the start time lTime (phTmp.lTime) in the phrase data Phase specified by the pointer phTmp is before the pronunciation start time lTime (ngr.next.lTime) in the next time-series data NoteGroup. Judge whether there is. That is, it is determined whether the next time-series data NoteGroup is before or after the break of the key operation.

If the next time-series data NoteGroup is before the break of the key operation, the determination result in step SC19 is “NO”, and the process proceeds to step SC21 (described later).
On the other hand, if the next time-series data NoteGroup is after the break of the key operation, the determination result in step SC19 is “YES”, and the flow advances to step SC20.

In step SC20, the keyboard coordinate maximum value iPosMax stored in the register iMax, that is, the keyboard coordinate maximum value iPosMax (ngr.iPosMax) in the currently specified time-series data NoteGroup is the phrase data Phase specified by the pointer phTmp. Store in the maximum keyboard coordinate iPosMax.
In step SC20, the keyboard coordinate minimum value iPosmin stored in the register imin, that is, the keyboard coordinate maximum value iPosmin (ngr.iPosmin) in the currently specified time-series data NoteGroup is a phrase specified by the pointer phTmp. Store in the keyboard coordinate longest value iPosmin in the data Phase.
Further, in step SC20, the pointer phTmp is incremented so as to designate the next phrase data Phase. Then, the process proceeds to step SC21, the pointer ngr is incremented so as to designate the next time-series data NoteGroup, and then the process returns to the above-described step SC3.

Now, according to the progress of the pointer ngr, a pitch difference (maximum value difference iDH and minimum value difference iDL) is obtained based on the preceding and following time series data NoteGroup, and the obtained maximum value difference iDH is 0 or more. If the minimum value difference iDL is not less than or equal to 0, the determination result in step SC11 is “NO”, and the flow advances to step SC13.
In steps SC13 to SC16, the maximum / minimum change in keyboard coordinate value is determined based on the maximum value difference iDH, minimum value difference iDL and flag ifig obtained in step SC5. The maximum value of the keyboard coordinates is detected by the value processing. On the other hand, if the minimum value is the minimum, the minimum value of the keyboard coordinates is detected by the maximum / minimum value processing described later.

That is, in step SC13, it is determined whether the flag ifig is larger than “0” and the maximum value difference iDH is smaller than “0”, that is, whether it is a maximum. If it is the maximum, the determination result is “YES”, and after the maximum / minimum value processing (described later) is detected via step SC14 to detect the maximum value, the process proceeds to step SC17.
On the other hand, if it is not the maximum, the determination result in step SC13 is “NO”, and the flow proceeds to step SC15. In step SC15, it is determined whether or not the flag ifig is smaller than “0” and the minimum value difference iDL is larger than “0”, that is, whether or not it is minimal. If it is the minimum, the determination result is “YES”, and after the maximum / minimum value processing (described later) is detected via step SC15 to detect the maximum value, the process proceeds to step SC17. If it is not the minimum, the determination result is “NO”, and the flow proceeds to step SC17. In step SC17, the maximum value difference iDH is stored as the coordinate difference iTend in the currently designated time-series data NoteGroup. Thereafter, the above-described step SC18 and subsequent steps are executed.

As described above, in the sound string analysis processing, the keyboard coordinate maximum value iPosMax and the keyboard coordinate minimum value iPosmin are compared with each other between adjacent time series data NoteGroup, and the larger keyboard coordinate maximum value iPosMax is stored in the register iMax. The smaller keyboard coordinate minimum value iPosmin is stored in the register imin, while the pitch change varies depending on the pitch difference (maximum value difference iDH / minimum value difference iDL) between the adjacent time series data NoteGroup and the flag ifig. The maximum and minimum are detected, and the maximum value / minimum value of the neighborhood data is detected.
By such processing operation, the neighborhood data maximum value iNPosMax, the neighborhood data minimum value iNPosmin, the difference change continuation value iTendCont, and the difference change continuation step iTend of each time series data NoteGroup are obtained.
The maximum keyboard coordinate value iPosMax stored in the register iMax and the minimum keyboard coordinate value iPosmin stored in the register imin are registered as the maximum keyboard coordinate value iPosMax and the minimum keyboard coordinate value iPosmin in the corresponding phrase data Phase. It has become so.

(4) Operation of Maximum / Minimum Value Processing Next, the operation of maximum / minimum value processing will be described with reference to FIG. When this process is executed via step SC14 or step SC16 (see FIG. 10) of the above-described sound string analysis process, the CPU 1 proceeds to step SD1 shown in FIG. 11, and both the search pointer i and the detection step iSteps are zero. Reset. Next, in step SD2, the pointer prev (ngr.prev) in the time series data NoteGroup designated by the pointer ngr is set to the pointer ng. As a result, the pointer ng designates the time series data NoteGroup immediately before the time series data NoteGroup designated in the sound string analysis process.

  Subsequently, in step SD3, the determination result is “YES” until the search pointer i exceeds the number of search data iTendCnt, and step SD4 and subsequent steps are executed. In step SD4, the keyboard coordinate maximum value iPosMax (ng.next.iPosMax) in the time-series data NoteGroup next to the time-series data NoteGroup specified by the pointer ng and the maximum keyboard coordinates in the time-series data NoteGroup specified by the pointer ng. It is determined whether or not the value iPosMax (ng.iPosMax) does not match.

If both keyboard coordinate maximum values iPosMax match, the determination result is “NO”, and the process proceeds to step SD6 described later. On the other hand, if they do not match, the determination result is “YES”, the process proceeds to step SD5, the detection step iSteps is incremented, and the process proceeds to step SD6. In step SD6, in the case of maximum detection, the search pointer i + 1 is stored in the difference change continuation value iTendCont (ng.iTendCont) in the time series data NoteGroup specified by the pointer ng, and the difference change continuation step iTendSteps (ng .ITendSteps) stores the detection step iSteps.
On the other hand, in the case of minimum detection, the search pointer −i−1 is stored in the difference change continuation value iTendCont (ng.iTendCont) in the time series data NoteGroup specified by the pointer ng, and the difference change continuation step iTendSteps ( ng.iTendSteps) stores the detection step iSteps.

  Next, in step SD7, the pointer prev (ngr.prev) in the time series data NoteGroup designated by the pointer ngr is set to the pointer ng. In step SD8, the search pointer i is incremented and stepped, and then the process returns to step SD3. Thereafter, steps SD3 to SD8 are repeated until the incremented search pointer i exceeds the number of search data iTendCnt. When the search pointer i exceeds the search data number iTendCnt, the determination result in step SD3 is “NO”, the process proceeds to step SD9, and the search data number iTendCnt is reset to zero to complete this process.

Thus, in the maximum / minimum value processing executed when the maximum value of the keyboard coordinates is detected in the above-described sound string analysis processing, the difference change continuation value iTendCont in the time-series data NoteGroup having the maximum value is “ 1 ”is stored in the difference change continuation step iTendSteps, and thereafter, each time series data NoteGroup subsequent to the number of search data iTendCnt has a difference change continuation value iTendCont to which the search pointer i is added. And the difference change continuation step iTend of the value corresponding to the detection step iSteps is stored.
On the other hand, in the maximum / minimum value processing executed when the minimum value of the keyboard coordinates is detected in the above-described sound string analysis processing, the difference change continuation value iTendCont in the time-series data NoteGroup having the minimum value is set to “−1. ”Is stored in the difference change continuation step iTendSteps, and each time-series data NoteGroup subsequent to the number of search data iTendCnt has a difference change continuation value iTendCont and a value obtained by subtracting the search pointer i. , A difference change continuation step iTend of a value corresponding to the detection step iSteps is stored.

(5) Operation of Neighborhood Data Processing Next, the operation of neighborhood data processing will be described with reference to FIG. When this process is executed via step SC18 (see FIG. 10) of the above-described sound string analysis process, the CPU 1 proceeds to step SE1 shown in FIG. 12, and resets the search pointer i to zero. Next, in step SE2, it is determined whether or not the number of searches MAXNBR has been exceeded and there is neighboring data.
The neighborhood data here refers to time series data NoteGroup after the time series data NoteGroup specified by the pointer ngr in the sound string analysis processing. Therefore, in step SE2, it is determined whether or not a maximum value / minimum value update process, which will be described later, has been performed on a predetermined number of time series data NoteGroup after the time series data NoteGroup designated by the pointer ngr.

If the maximum value / minimum value update processing for the predetermined number of time series data NoteGroup has not been completed, the determination result is “YES”, and the maximum value / minimum value update processing of steps SE3 to SE7 is performed for the predetermined number of time series. This is done for the data NoteGroup.
That is, in step SE3, when the keyboard coordinate maximum value iPosMax (nLast [i] .iPosMax) in the time-series data NoteGroup designated by the neighborhood data pointer nLast [i] is designated by the sound string analysis process. It is determined whether or not the keyboard coordinate maximum value iPosMax (ngr.iPosMax) in the series data NoteGroup is smaller.
The neighborhood data pointer nLast [i] is a pointer that is incremented corresponding to the search pointer i, and specifies time-series data NoteGroup after the time-series data NoteGroup specified by the pointer ngr.

  nLast [i]. iPosMax is ngr. If it is greater than iPosMax, the determination result is “NO”, and the process proceeds to step SE5. On the other hand, nLast [i]. iPosMax is ngr. If it is smaller than iPosMax, the determination result is “YES”, the process proceeds to step SE4, and the neighborhood data maximum value iNPosMax (nLast [i] .iNPosMax) in the time-series data NoteGroup designated by the neighborhood data pointer nLast [i]. Then, the keyboard coordinate maximum value iPosMax (ngr.iPosMax) in the time-series data NoteGroup designated in the sound string analysis process is stored, and the process proceeds to step SE5.

Next, in step SE5, when the keyboard coordinate minimum value iPosmin (nLast [i] .iPosmin) in the time series data NoteGroup designated by the neighborhood data pointer nLast [i] is designated by the sound string analysis processing. It is determined whether or not the keyboard coordinate minimum value iPosmin (ngr.iPosmin) in the series data NoteGroup is larger.
nLast [i]. iPosmin is ngr. If it is smaller than iPosmin, the determination result is “NO”, and the process proceeds to step SE7. On the other hand, nLast [i]. iPosMax is ngr. If it is larger than iPosMax, the determination result is “YES”, the process proceeds to step SE6, and the neighborhood data minimum value iNPosmin (nLast [i] .iNPosmin) in the time-series data NoteGroup designated by the neighborhood data pointer nLast [i]. In addition, the keyboard coordinate minimum value iPosmin (ngr.iPosmin) in the time-series data NoteGroup designated in the sound string analysis processing is stored.

  In step SE7, the search pointer i is incremented and incremented, and then the process returns to step SE2. Thereafter, the above steps SE3 to SE7 are repeated until the maximum value / minimum value update processing is completed for the predetermined number of pieces of time-series data NoteGroup. As a result, the keyboard coordinate maximum value iPosMax and keyboard coordinate minimum value iPosmin of the time series data NoteGroup in the vicinity after itself are registered in the time series data NoteGroup as the neighborhood data maximum value iNPosMax and the neighborhood data minimum value iNPosmin.

(6) Operation of Fingering Data Generation Process Next, the operation of the fingering data generation process will be described with reference to FIG. When this processing is executed via step SA3 (see FIG. 8) of the main routine described above, the CPU 1 proceeds to step SF1 shown in FIG. 13 and designates a pointer ngr for designating time-series data NoteGroup and note data Note. The pointer nTmp and the pointer phTmp specifying the phrase data Phase are reset to zero.
Subsequently, in step SF2, the keyboard coordinate minimum value iPosmin (phTmp.iPosmin) is subtracted from the keyboard coordinate maximum value iPosMax (phTmp.iPosMax) in the phrase data Phase specified by the pointer phTmp, and the keyboard coordinates in the current phrase section are subtracted. Is calculated and stored in the register pRange. Hereinafter, the content of the register pRange is referred to as the maximum / minimum width pRange.

Next, in step SF3, it is determined whether or not the maximum / minimum width pRange is smaller than a predetermined value NOMOVE. The predetermined value NOMOVE represents a width that allows the key operation without moving the hand. Therefore, in this step SF3, it is determined whether or not hand movement is necessary in the current phrase section.
When the maximum / minimum width pRange is larger than the predetermined value NOMOVE and the hand needs to be moved, the determination result in step SF3 is “NO”, and the process proceeds to step SF4. In step SF4, the neighborhood data maximum value iNPosMax (ngr.iNPosMax) and the neighborhood data minimum value iNPosmin (ngr.iNPosmin) in the time-series data NoteGroup designated by the pointer ngr are respectively set to the keyboard coordinate maximum in the hand state data Hand. After the value iPosMax (Hand.iPosMax) and the keyboard coordinate minimum value iPosmin (Hand.iPosmin) are registered, the process proceeds to step SF6.

On the other hand, when the maximum / minimum width pRange is smaller than the predetermined value NOMOVE and the movement of the hand is unnecessary, the determination result in Step SF3 is “YES”, and the process proceeds to Step SF5. In step SF5, the keyboard coordinate maximum value iPosMax (phTmp.iPosMax) and the keyboard coordinate maximum value iPosmin (phTmp.iPosmin) in the phrase data Phase specified by the pointer phTmp are respectively set to the keyboard coordinate maximum value in the hand state data Hand. After registering as iPosMax (Hand.iPosMax) and keyboard coordinate minimum value iPosmin (Hand.iPosmin), the process proceeds to step SF6.
In step SF6, hand movement processing is executed. In the hand movement process, as described later, the middle finger coordinates Hand.iPos are used as the hand position coordinates iPos (Hand.iPos). fig [2]. Set iPos. Thus, when the position of the first hand is determined, the CPU 1 repeats steps SF7 to SF22 until all the time-series data NoteGroup is read according to the increment of the pointer ngr.

  That is, first, in step SF8, a finger state confirmation process is executed. In the finger state confirmation process, as will be described later, when there is a finger being depressed, if the sound silence time of the sound being depressed by the finger has been exceeded, the finger is set to the mute state. Next, in step SF9, is the keyboard coordinate maximum value iPosMax (Hand.iPosMax) in the hand state data Hand smaller than the keyboard coordinate maximum value iPosMax (ngr.iPosMax) in the time series data NoteGroup designated by the pointer ngr? Or whether the keyboard coordinate minimum value iPosmin (Hand.iPosmin) in the hand state data Hand is greater than the keyboard coordinate minimum value iPosmin (ngr.iPosmin) in the time-series data NoteGroup specified by the pointer ngr, that is, Determine if hand movement is necessary.

If the hand movement is not necessary, the determination result is “NO”, and the process proceeds to step SF12 described later. However, if the hand movement is necessary, the determination result is “YES” and the process proceeds to step SF10. move on. In step SF10, the neighborhood data maximum value iNPosMax (ngr.iNPosMax) and the neighborhood data minimum value iNPosmin (ngr.iNPosmin) in the time-series data NoteGroup designated by the pointer ngr are respectively set to the keyboard coordinate maximum in the hand state data Hand. Store the value iPosMax (Hand.iPosMax) and the minimum keyboard coordinate value iPosmin (Hand.iPosmin).
Thereafter, a hand movement process is executed via step SF11, in response to updating of the keyboard coordinate maximum value iPosMax (Hand.iPosMax) and the keyboard coordinate minimum value iPosmin (Hand.iPosmin) in the hand state data Hand. Middle finger coordinates Hand.i that become the new hand position coordinates iPos (Hand.iPos). fig [2]. Set iPos.

  Next, in step SF12, the note data pointer NoteEv in the time series data NoteGroup designated by the pointer ngr is set to the pointer nTmp. Next, in steps SF13 to SF15, finger assignment processing is executed via step SF14 while stepping the pointer nTmp until there is no more note data Note specified by the pointer nTmp. In the finger assignment process, as will be described later, among the fingers specified by the assignment pointer idx, a finger whose finger position is equal to or less than the coordinates of the key to be played and which has not been pressed is defined as a finger to be played. Assign fingering.

When the fingering assignment is made in this way, the process proceeds to step SH16, where the start time lTime (phTmp.lTime) in the phrase data Phase specified by the pointer phTmp is the sound generation start time lTime (ngr.ngr.) In the next time-series data NoteGroup. next.lTime) is determined. That is, it is determined whether the next time-series data NoteGroup is before or after the break of the key operation.
Here, if the next time-series data NoteGroup is before the break of the key operation, the determination result is “NO”, the process proceeds to step SF22, and the pointer ngr is set so as to specify the next time-series data NoteGroup. Then, the process returns to step SF7 described above.

  On the other hand, if the next time-series data NoteGroup is after the break of the key operation, the determination result in step SF16 is “YES”, and the process proceeds to step SF17. In step SF17, the keyboard coordinate minimum value iPosmin (phTmp.iPosmin) is subtracted from the keyboard coordinate maximum value iPosMax (phTmp.iPosMax) in the phrase data Phase specified by the pointer phTmp, and the maximum / minimum of keyboard coordinates in the current phrase section is obtained. The minimum width pRange is calculated. Subsequently, in step SF18, it is determined whether or not the maximum / minimum width pRange is smaller than a predetermined value NOMOVE. The predetermined value NOMOVE represents a width that allows the key operation without moving the hand. Therefore, in step SF18, it is determined whether or not hand movement is necessary in the current phrase section.

  If the maximum / minimum width pRange is larger than the predetermined value NOMOVE and the hand needs to be moved, the determination result in step SF18 is “NO”, and the process proceeds to step SF19. In step SF19, the neighborhood data maximum value iNPosMax (ngr.next.iNPosMax) and neighborhood data minimum value iNPosmin (ngr.next.iNPosmin) in the next time-series data NoteGroup are respectively set to the maximum keyboard coordinate in the hand state data Hand. After registering the value iPosMax (Hand.iPosMax) and the keyboard coordinate minimum value iPosmin (Hand.iPosmin), the process proceeds to step SF21.

  On the other hand, if the maximum / minimum width pRange is smaller than the predetermined value NOMOVE and the movement of the hand is unnecessary, the determination result in Step SF18 is “YES”, and the process proceeds to Step SF20. In step SF20, the keyboard coordinate maximum value iPosMax (phTmp.iPosMax) and the keyboard coordinate maximum value iPosmin (phTmp.iPosmin) in the phrase data Phase designated by the pointer phTmp are respectively set to the keyboard coordinate maximum value in the hand state data Hand. After registering as iPosMax (Hand.iPosMax) and keyboard coordinate minimum value iPosmin (Hand.iPosmin), the process proceeds to step SF21.

  In step SF21, as in step SF6 described above, the middle finger coordinates Hand.iPos as the hand position coordinates iPos (Hand.iPos). fig [2]. A hand movement process (see FIG. 14) for setting iPos is executed. Thereafter, the process proceeds to step SF22, the pointer ngr is incremented so as to specify the next time-series data NoteGroup, and then the process returns to the above-described step SF7. Thereafter, steps SF7 to SF22 are repeated until all the time series data NoteGroup are read according to the progress of the pointer ngr, and when all the reading is completed, the determination result of step SF7 becomes “NO”, and this processing ends.

  Thus, in the fingering data generation process, first, the maximum / minimum width pRange of the keyboard coordinates in the current phrase section is calculated, and based on this, it is determined whether movement of the hand is necessary in the current phrase section. Is required, the keyboard coordinate maximum value iPosMax and the keyboard coordinate minimum value iPosmin in the hand state data Hand are updated based on the neighborhood data maximum value iNPosMax and the neighborhood data minimum value iNPosmin in the current time series data NoteGroup. , Middle finger coordinates Hand.iPos as first hand position coordinates iPos (Hand.iPos). fig [2]. Set iPos.

When the position of the first hand is determined, the presence or absence of the finger being pressed is determined, and if there is an applicable finger, the finger is muted when the mute time of the sound being pushed by that finger has passed The finger status confirmation process set to `` 1 '' is executed, and then, of the fingers of the key operated hand, the finger whose finger position is not more than the coordinate of the key to be played and which is not pressed is to be played. Assign fingering as a finger.
After performing fingering assignment, it is determined again whether the next time series data NoteGroup is before or after the break of the key operation, and if it is after the break of the key operation, it is necessary to move the hand. Judgment is made. Then, when it is necessary to move the hand, the keyboard coordinate maximum value iPosMax and the keyboard coordinates in the hand state data Hand based on the neighborhood data maximum value iNPosMax and the neighborhood data minimum value iNPosmin in the next time-series data NoteGroup. After updating the minimum value iPosmin, the middle finger coordinates Hand.iPos as the hand position coordinates iPos (Hand.iPos) are updated. fig [2]. Set iPos. Thereafter, such processing operation is repeated for all time series data NoteGroup.

(7) Operation of Hand Movement Process Next, the operation of the hand movement process will be described with reference to FIG. When this process is executed through steps SF6, SF11, and SF21 of the fingering data generation process described above, the CPU 1 proceeds to step SG1 shown in FIG. 14 and resets the search pointer ifig to zero. Thumb coordinates Hand. fig [0]. The minimum keyboard coordinate value iPosmin in the hand state data Hand is stored in iPos.
Subsequently, in step SG2, it is determined whether or not the identification flag iRL (Hand.iRL) in the hand state data Hand is “1”, that is, the left hand key operation. If it is a left-hand key operation, the determination result is “YES”, and the process proceeds to step SG3. On the other hand, if it is a right-hand key operation, the determination result is “NO”, and the process proceeds to step SG4.

In step SG3, the thumb coordinates Hand. fig [0]. The minimum keyboard coordinate value iPosMax in the hand state data Hand is stored in iPos. As described above, when the key is operated with the right hand, the keyboard coordinate minimum value iPosmin in the hand state data Hand is assigned to the thumb position. On the other hand, when the key operation is performed with the left hand, The keyboard coordinate maximum value iPosMax is assigned to the thumb position.
In step SG4, finger position designation processing is executed. As will be described later, in the finger position designation process, the hand width iRange obtained from the keyboard coordinate maximum value iPosMax (Hand.iPosMax) and the keyboard coordinate minimum value iPosmin (Hand.iPosmin) in the hand state data Hand, and the thumb Taking into account constants figtmp [0] to figtmp [4] representing the degree of separation of each finger from the first finger to the little finger. fig [1]. iPos-Hand. fig [4]. Set iPos.

  Thus, in step SG4, the coordinates Hand. fig [1]. iPos-Hand. fig [4]. When iPos is set, the process proceeds to step SG5, where the middle finger coordinates Hand. fig [2]. iPos is stored as hand position coordinates iPos (Hand.iPos) in hand state data Hand.

  As described above, in the hand movement process, when performing a key operation with the right hand, the keyboard coordinate minimum value iPosmin in the hand state data Hand is assigned to the thumb position, while when performing a key operation with the left hand, The keyboard coordinate maximum value iPosMax in the hand state data Hand is assigned to the position of the thumb, and further from the keyboard coordinate maximum value iPosMax (Hand.iPosMax) and the keyboard coordinate minimum value iPosmin (Hand.iPosmin) in the hand state data Hand. Considering the width iRange of the obtained hand and the constants figtmp [0] to figtmp [4] representing the degree of separation of each finger from the thumb to the little finger, the coordinates Hand. fig [1]. iPos-Hand. fig [4]. iPos is set and the middle finger coordinates Hand. fig [2]. iPos is set to the hand position coordinate iPos (Hand.iPos).

(8) Operation of Finger State Check Process Next, the operation of the finger state check process will be described with reference to FIG. When this process is executed via step SF8 (see FIG. 13) of the fingering data generation process described above, the CPU 1 proceeds to step SH1 shown in FIG. 15, and resets the search pointer i to zero. Subsequently, in step SH2, it is determined whether or not the search pointer i is smaller than “5”, that is, whether or not the state confirmation has been completed for all fingers. If the state has not been confirmed, the determination result is “YES”, and the flow proceeds to step SH3. In step SH3, the finger front state flag statprev (Hand.fig [i] .statprev) designated by the search pointer i in the hand state data Hand is reset to zero.

In step SH4, whether or not the note data event (Hand.fig [i] .event) being pressed by the finger specified by the search pointer i in the hand state data Hand is “NULL”, that is, Then, it is determined whether or not the finger specified by the search pointer i is being depressed. If the key is being depressed, the determination result is “NO”, the process proceeds to step SH7, the search pointer i is incremented and stepped, and then the process returns to step SH2.
On the other hand, if the key is not being depressed, the determination result is “YES”, and the flow proceeds to the next step SH5. In step SH5, the mute time (Hand.fig [i] .event.lTerm) of the sound being pressed by the finger specified by the search pointer i is the start time lTime in the time-series data NoteGroup specified by the pointer ngr. It is determined whether or not it is smaller than (ngr.lTime), that is, whether or not the mute time is exceeded.

  If the mute time is not exceeded, the determination result is “NO”, the search pointer i is incremented via step SH7, and the process returns to step SH2. On the other hand, if the mute time is exceeded, the determination result is “YES”, and the process proceeds to step SH6. In step SH6, the finger state flag (Hand.fig [i] .status) designated by the search pointer i in the hand state data Hand is set to “0” representing the mute state, and the search pointer i The designated finger front state flag statprev (Hand. Fig [i]. Statprev) is set to “1”. Further, “NULL” is set to the note data event (Hand.fig [i] .event) being pressed by the finger specified by the search pointer i.

Then, after the search pointer i is incremented and stepped at step SH7, the process is returned to step SH2. Thereafter, the above steps SH2 to SH7 are repeated until the state confirmation is completed for all the fingers. When the state confirmation is completed for all the fingers, the determination result in step SH2 is “NO”, and this process is completed.
As described above, in the finger state confirmation process, if there is a finger being pressed, whether the sound muted time of the sound being pressed by the finger (the sound of the time-series data NoteGroup specified by the pointer ngr) has been exceeded. If the mute time is exceeded, the finger is set to the mute state.

(9) Operation of Finger Assignment Process Next, the operation of the finger assignment process will be described with reference to FIG. When this process is executed via step SF14 (see FIG. 13) of the fingering data generation process described above, the CPU 1 proceeds to step SJ1 shown in FIG. 16 and resets the search pointer i to zero. Subsequently, in step SH2, it is determined whether or not the search pointer i is smaller than “5”, that is, whether or not all the fingers have been allocated. If the allocation has not been completed, the determination result is “YES”, and the flow proceeds to step SJ3.

In steps SJ3 to SJ5, the allocation pointer idx is initialized according to the hand operating the key and the allocation direction. That is, if the hand operating the key is assigned with the right hand in order from the little finger to the thumb or if the hand operating the key is assigned in the order with the left hand from the little finger to the thumb, the determination in step SJ4 The result is “YES”, “4-i” is set to the allocation pointer idx (step SJ5), and “i” is set to the allocation pointer idx otherwise (step SJ3).
Next, in step SJ6, the finger coordinates iPos (Hand.fig [idx] .iPos) designated by the assignment pointer idx in the hand state data Hand are the keyboard coordinates in the note data Note designated by the pointer nTmp. iPos (nTmp.iPos) or less, and the finger state flag status (Hand.fig [idx] .status) specified by the assignment pointer idx in the hand state data Hand is “0”, that is, in the mute state. Determine if there is.

If the determination condition is not met, the determination result is “NO”, the process proceeds to step SJ7, the search pointer i is incremented, and the process returns to step SJ2.
On the other hand, if the position of the finger specified by the assigned pointer idx is equal to or less than the coordinates of the key to be played and the finger is not pressed, the determination result in step SJ6 is “YES”, and the process returns to step SJ8. Then, the pointer nTmp is stored as the note data event (Hand. Fig [idx] .event) of the finger specified by the allocation pointer idx in the hand state data Hand.

Next, in step SJ9, the allocation pointer idx is stored in the fingering number cfig (nTmp.iPos) in the note data Note designated by the pointer nTmp. As a result, the fingering number cfig representing the finger to be played is determined. In step SJ10, the allocation pointer idx is stored in the register ifig, and then the finger position designation process (see FIG. 17) is executed via step SJ11.
As described above, in the finger assignment process, among the fingers designated by the assignment pointer idx, the finger whose finger position is equal to or less than the coordinate of the key to be played and which is not pressed is operated as the finger to be played. The finger is assigned.

  In the finger position designation process executed through step SJ11, the hand coordinates obtained from the keyboard coordinate maximum value iPosMax (Hand.iPosMax) and the keyboard coordinate minimum value iPosmin (Hand.iPosmin) in the hand state data Hand. Taking into account the width iRange and constants figtmp [0] to figtmp [4] representing the degree of separation of each finger from the thumb to the little finger, the index finger to the little finger on the basis of the “finger assigned finger” in the finger assignment process Each finger coordinate Hand. fig [1]. iPos-Hand. fig [4]. iPos is reset.

(10) Operation of Finger Position Specification Process Next, the operation of the finger position specification process will be described with reference to FIG. When this process is executed through step SG4 (see FIG. 14) of the hand movement process described above, the CPU 1 proceeds to step SK1 shown in FIG. 17 and stores “1” in the register iCoef. Next, in step SK2, it is determined whether or not the identification flag iRL (Hand.iRL) in the hand state data Hand is “1”, that is, the key operation of the left hand. If it is a left-hand key operation, the determination result is “YES”, the process proceeds to step SK3, and “−1” is stored in the register iCoef. On the other hand, if the right-hand key operation is performed, the determination result is “NO”, and the flow proceeds to Step SK4. Thus, “1” is stored in the register iCoef when the right hand key is operated, and “−1” is stored in the register iCoef when the left hand key is operated.

  In step SK4, the keyboard coordinate minimum value iPosmin (Hand.iPosmin) is subtracted from the keyboard coordinate maximum value iPosMax (Hand.iPosMax) in the hand state data Hand to calculate the hand width, and this is stored in the register iRange. . Hereinafter, the content of the register iRange is referred to as a hand width iRange. Subsequently, in steps SK5 to SK8, the spacing ratio between the fingers expressed by constants figtmp [0] to figtmp [4] representing the degree of separation of each finger from the thumb to the little finger is multiplied by the hand width iRange. Thus, temporary coordinate positions figtmp [1] to [4] of each finger from the index finger to the little finger excluding the thumb are generated.

  Thereafter, in Steps SK9 to SK13, “0” is set to the search pointer ifig in the above-described hand movement process (see FIG. 14), so the index finger excluding the thumb specified by the search pointer ifig is used. Each finger coordinate Hand. fig [1]. iPos-Hand. fig [4]. iPos is calculated using the temporary coordinate positions figtmp [1] to [4] of each finger from the index finger to the little finger excluding the thumb generated in the above-described steps SK5 to SK8.

For example, the index finger coordinates Hand. fig [1]. In order to obtain iPos, the already set thumb coordinate Hand. fig [0]. iPos is added with the temporary coordinate position figtmp [1] of the index finger, and the added value is multiplied by the value of the register iCoef. The middle finger coordinates Hand. fig [2]. In order to obtain iPos, the index finger coordinates Hand. fig [1]. iPos is added with the temporary coordinate position figtmp [2] of the middle finger, and the added value is multiplied by the value of the register iCoef.
In this way, the coordinates of each finger from the index finger to the little finger except the thumb Hand. fig [1]. iPos-Hand. fig [4]. When iPos has been generated, the determination result in step SK10 is “NO”, and the process ends.

  In this way, in the finger position designation process, the hand width iRange obtained from the keyboard coordinate maximum value iPosMax (Hand.iPosMax) and the keyboard coordinate minimum value iPosmin (Hand.iPosmin) in the hand state data Hand is determined from the thumb. The temporary coordinate position of each finger from the index finger to the little finger excluding the thumb by multiplying the separation ratio between the fingers expressed by constants figtmp [0] to figtmp [4] representing the degree of separation of each finger up to the little finger figtmp [1] to [4] are generated, and these temporary coordinate positions figtmp [1] to [4] are already set. fig [0]. iPos is sequentially added to the coordinates Hand. fig [1]. iPos-Hand. fig [4]. iPos is set.

  As described above, in the first embodiment, a sound that is simultaneously pronounced is searched from the music data MidiEvent, the corresponding sounds are grouped together, and a time series including attributes representing the sound generation / mute timing and pitch relationship is provided. While generating the data NoteGroup, in addition to generating the note data Note representing the music data MidiEvent corresponding to the time series data NoteGroup, the start / interval of the section delimited by the rest of the key operation from the music data MidiEvent After generating the phrase data Phase representing the end time, etc., the maximum and minimum of pitch change are determined according to the pitch difference (maximum value difference iDH / minimum value difference iDL) and the flag ifig between adjacent time series data NoteGroup. Detect or detect the maximum / minimum value of nearby data The processing operation is performed to obtain the maximum neighboring data iNPosMax, the minimum neighboring data iNPosmin, the differential change continuation value iTendCont, and the differential change continuation step iTend of each time series data NoteGroup, and the maximum keyboard coordinate of the corresponding phrase data Phase. The value iPosMax and the keyboard coordinate minimum value iPosmin are generated.

  Thereafter, it is first determined whether or not a hand movement is necessary in the current phrase section, and if a hand movement is necessary, based on the neighborhood data maximum value iNPosMax and neighborhood data minimum value iNPosmin in the current time series data NoteGroup. After updating the keyboard coordinate maximum value iPosMax and the keyboard coordinate minimum value iPosmin in the hand state data Hand, the position of the first hand (middle finger coordinates Hand.fig [2] .iPos) is set. Then, when the position of the first hand is determined, among the fingers of the hand to be operated by the key, the finger whose position is not more than the coordinate of the key to be played and that is not pressed is operated as a finger to be played. Make an assignment.

  After the fingering assignment, it is determined again whether the next time series data NoteGroup is before or after the break of the key operation, and if it is after the break of the key operation, it is determined whether or not the hand needs to be moved. If it is necessary to move the hand, the keyboard coordinate maximum value iPosMax and the keyboard coordinates in the hand state data Hand are based on the neighborhood data maximum value iNPosMax and the neighborhood data minimum value iNPosmin in the next time-series data NoteGroup. After updating the minimum value iPosmin, the position of the next hand (middle finger coordinates Hand.fig [2] .iPos) is set. As a result, it is possible to generate fingering information for fingering that is easy to play while taking into account the position of the hand moving as the music progresses.

D. Modification of First Embodiment Next, an operation of “finger assignment processing” according to a modification of the first embodiment will be described with reference to FIG. As in the first embodiment described above, when this process is executed via step SF14 (see FIG. 13) of the fingering data generation process, the CPU 1 proceeds to step SL1 shown in FIG. Ifig is reset to zero, and the maximum value is stored in the register iInt. The maximum value here refers to the distance between the finger that can be operated by the key and the key.

Next, in steps SL2 to SL4, the order of fingering assignment fingers is determined according to whether the hand operating the key is the right hand or the left hand. That is, first, “0” is set in the flag iDest (step SL2), and then it is determined whether or not the identification flag iRL in the hand state data Hand is “0”, that is, the right hand key operation ( Step SL3). If the left-hand key operation is performed, the determination result in step SL3 is “NO”, and the flag iDest remains “0”. On the other hand, if it is a right-hand key operation, the determination result in step SL3 is “YES”, the process proceeds to step SL4, and the flag iDest is “1”.
The flag iDest is a flag indicating the direction of fingering assignment. When the flag is “0”, the fingering assignment from the right side is indicated. When the flag is “1”, the fingering assignment from the left side is indicated. Therefore, if the hand operating the key is the right hand, fingering is assigned in order from the thumb to the little finger. On the other hand, if the hand operating the key is the left hand, fingering is assigned in order from the thumb to the little finger.

In step SL5, it is determined whether or not the search pointer i is smaller than “5”, that is, whether or not all the fingers have been allocated. If the allocation has not been completed, the determination result is “YES”, and the flow proceeds to step SL6. In steps SL6 to SL8, the allocation pointer idx is initialized according to the key operating hand and the allocation direction.
That is, if the hand that operates the key is assigned to the thumb from the little finger in order with the right hand or the hand that performs the key operation is assigned in order from the little finger to the thumb with the left hand, the determination result in step SL7 is “YES”. "4-i" is set to the allocation pointer idx (step SL8), otherwise "i" is set to the allocation pointer idx (step SL6).

  Next, in step SL9, the finger coordinate iPos (Hand.fig [idx] .iPos) specified by the assignment pointer idx in the hand state data Hand and the keyboard coordinate iPos in the note data Note specified by the pointer nTmp are used. The difference absolute value (separation distance between the finger and the key) from (nTmp.iPos) is stored in the register iIntTmp. Subsequently, in step SL10, whether or not the distance between the finger and the key stored in the register iIntTmp is smaller than the maximum value (the distance between the finger and the key that can be operated by the key) stored in the register iInt. It is determined whether or not the key can be operated with a finger.

If it is possible to operate the key with the currently designated finger, the determination result is “YES”, and the process proceeds to step SL11 where the assigned pointer idx representing the currently designated finger is stored in the register ifig and the register iIntTmp. Is updated and registered in the register iInt as a new maximum value for the distance between the finger and the key stored in step S12, and the process proceeds to step SL12.
On the other hand, when the key cannot be operated with the currently designated finger, the determination result in step SL10 is “YES”, the process proceeds to step SL12, and the search pointer i is incremented and stepped. The process returns to step SL5. Thereafter, the above-described steps SL5 to SL12 are repeated until all the fingers have been allocated. As a result, the assignment pointer idx representing the finger with the shortest distance from the key is stored in the register ifig, while the determination result in step SL5 becomes “NO”, and the flow proceeds to step SL13.

  In step SL13, the pointer nTmp is stored as the note data event (Hand.fig [idx] .event) of the finger specified by the allocation pointer idx in the hand state data Hand. Next, in step SJ9, the allocation pointer idx is stored in the fingering number cfig (nTmp.iPos) in the note data Note designated by the pointer nTmp. As a result, the fingering number cfig representing the finger to be played is determined.

In step SL15, the allocation pointer idx is stored in the register ifig, and then the finger position designation process (see FIG. 17) is executed via step SL16. In the finger position designation processing, the hand coordinate iRange obtained from the maximum keyboard coordinate value iPosMax (Hand.iPosMax) and the minimum keyboard coordinate value iPosmin (Hand.iPosmin) in the hand state data Hand, and each of the thumb to the little finger In consideration of the constants figtmp [0] to figtmp [4] representing the degree of finger separation, in the finger assignment process, the coordinates Hand. fig [1]. iPos-Hand. fig [4]. After resetting iPos, this process is terminated.
As described above, in the finger assignment process according to the modification, among the fingers specified by the assignment pointer idx, the finger having the shortest distance from the key to be pressed is assigned to be fingered as the finger to be played. It has become.

[Second Embodiment]
Next, a second embodiment will be described with reference to FIGS. Since the configuration of the second embodiment is the same as that of the first embodiment described above, description thereof is omitted. The second embodiment is different from the first embodiment described above in that motion data (described later) indicating the movement position of the hand necessary for the performance of music is generated, and the position of the hand defined by this motion data and the movement position. Evaluate “difficulty to play” from the fingering data generated in consideration of the corresponding finger position, and adjust the fingering data so that the evaluated “difficulty to play” becomes an index value below a certain level. It is to obtain fingering data that is easy to play. Hereinafter, the configuration of the operation data used in the second embodiment and the operation of the second embodiment will be described.

(1) Configuration of Operation Data FIG. 19 is a diagram showing a configuration of operation data provided in the data area of the RAM 3. The action data HandPos represents the movement position of the hand necessary for playing the music, and is composed of a start time ITime, an end time lTerm, a keyboard coordinate maximum value iPosMax, a keyboard coordinate minimum value iPosmin, a pointer next, and a pointer prev. The pointer next and the pointer prev are pointers that specify the next operation data and the previous operation data, respectively.

(2) Operation of Main Routine Next, the operation of the main routine according to the second embodiment will be described with reference to FIG.
When an event for instructing the CPU 1 to execute the main routine is supplied from the input unit 4, the CPU 1 executes the main routine shown in FIG. 20 and proceeds to step SM 1 to execute time-series data generation processing. The time-series data generation process is the same as that in the first embodiment described above. The sound that is simultaneously pronounced is searched from the music data MidiEvent, the corresponding sounds are grouped together, and the pronunciation / mute timing and pitch relationship are determined. While generating time-series data NoteGroup having attributes to represent, while generating note data Note representing music data MidiEvent corresponding to the time-series data NoteGroup, rests that are key operations of music data MidiEvent Phrase data Phase representing the start / end time of the section to be divided is generated.

  Next, in step SM2, a sound string analysis process is executed. The sound string analysis process is the same as that in the first embodiment described above, and the pitch change is determined according to the pitch difference (maximum value difference iDH / minimum value difference iDL) between the adjacent time series data NoteGroup and the flag ifig. Processing for detecting the maximum and minimum values, or detecting the maximum value / minimum value of the neighborhood data is performed, whereby the neighborhood data maximum value iNPosMax, the neighborhood data minimum value iNPosmin, and the difference change continuation value iTendCont of each time series data NoteGroup are performed. In addition to obtaining the difference change continuation step iTend, the keyboard coordinate maximum value iPosMax and keyboard coordinate minimum value iPosmin of the corresponding phrase data Phase are generated.

  Subsequently, in step SM3, a counter iRetry for counting the number of times of performing fingering data evaluation described later is reset to zero. Next, in step SM4, an operation data generation process is executed. In the operation data generation process, as will be described later, the time series data NoteGroup is referred to and a section from the extreme point to the extreme point at which the pitch change of the song changes from “maximum to minimum” or “minimum to maximum” is searched. In such a section, an optimal hand is set so that the key operation allowable range determined by the width of the player's hand falls within the key operation range determined by the maximum keyboard coordinate value iPosMax and the minimum keyboard coordinate value iPosmin defined by the time series data NoteGroup. The movement data representing the movement position of the hand is generated.

Next, in step SM5, fingering data generation processing is executed. In the fingering data generation process, as will be described later, first, the position of the hand is determined with reference to the operation data HandPos, and the finger position of each finger at the position of the hand is below the coordinates of the key to be played, In addition, a finger that has not been pressed is assigned as a finger to be played, and each time a key operation is interrupted, the position of the hand is determined with reference to the operation data HandPos and assigned. .
In step SM6, fingering data evaluation processing is executed. In the fingering data evaluation process, as described later, the difference between the coordinates of the key to be played and the coordinates of the finger assigned to the fingering is accumulated, and a value representing “difficulty to play” is stored in the counter iCost.

  Next, in step SM7, the average value average (iCost) of “difficulty to play” obtained by dividing the value of the counter iCost by the number of notes subjected to the fingering data evaluation in step SM6 is calculated from the allowable range value ARROWEDCOST. It is determined whether the number of evaluations is smaller or the number of evaluations counted by the counter iRetry is smaller than the maximum number of re-evaluation MAXRETRY. Here, if any one of the conditions is met, the determination result is “YES”. If not, the determination result is “NO”, and the process proceeds to step SM8. In step SM8, the number of evaluations counted by the counter iRetry is incremented and stepped. In subsequent step SM9, the half value iHandHalf of the hand width is changed by a random number, and the process is returned to the above-described step SM4. Based on the changed half-width iHandHalf of the hand width, the motion data HandPos representing the movement position of the hand necessary for playing the music is regenerated.

  Thereafter, fingering data is generated taking into consideration the position of the hand defined by the regenerated motion data HandPos and the position of the corresponding finger, and the “difficulty to play” of the generated fingering data is evaluated. To do. The fingering data is adjusted until the number of evaluations exceeds the maximum number of re-evaluation MAXRETRY or until the evaluated “difficulty to play” (average value (iCost)) falls within the allowable range value ARROWEDCOST. Get finger data.

(3) Operation Data Generation Process Operation Next, the operation data generation process operation will be described with reference to FIG. When this process is executed via step SM4 (see FIG. 20) of the main routine described above, the CPU 1 proceeds to step SN1 shown in FIG. 21, and resets the pointer ngr specifying the time-series data NoteGroup to zero. Next, in step SN2, the pointer ngr is stored in the register ngrSt. Subsequently, in step SN3, it is determined whether or not the time-series data NoteGroup designated by the pointer ngr is “NULL”, that is, whether or not the generation of operation data has been completed. When the generation of the operation data is completed, the determination result is “NO”, and this process is completed. Otherwise, the determination result is “YES”, and the process proceeds to step SN4.

  In step SN4, the difference change continuation value iTendCont (ngr.iTendCont) in the current time series data NoteGroup specified by the pointer ngr and the difference change continuation value iTendCont (ngr.next.iTendCont) in the next time series data NoteGroup are set. It is determined whether or not the product is “0” or less, that is, whether it is an extreme value. If both the difference change continuation value iTendCont in the current time series data NoteGroup and the difference change continuation value iTendCont in the next time series data NoteGroup are both of the same polarity, the determination result is “NO” because it is not an extreme value. After proceeding to step SN8 and incrementing the pointer ngr, the process returns to step SN3 to detect the extreme value again.

In this way, when the extreme value determination is advanced based on the product of the difference change continuation value iTendCont in the current time series data NoteGroup and the difference change continuation value iTendCont in the next time series data NoteGroup, one extreme value is different from the other. Is detected, the decision result in step SN4 becomes “YES”, and the flow proceeds to step SN5.
In step SN5, the difference change continuation value iTendCont (ngr.iTendCont) in the current time series data NoteGroup is divided by the absolute value (abs (ngr.next.iTendCont) of the difference change continuation value iTendCont in the next time series data NoteGroup. The value is stored in the register iTend, where the value of the register iTend indicates “maximum” if the value is positive, and the value indicates “minimum” if the value is negative.

Next, the movement position specifying process is executed via step SN6. In the movement position specifying process, as will be described later, the keyboard coordinates defined by the time series data NoteGroup in the interval from the extreme point to the extreme point where the pitch change of the song changes from “maximum to minimum” or “minimum to maximum”. An operation that sets the optimal hand position so that the key operation allowable range determined by the width of the player's hand falls within the key operation range determined by the maximum value iPosMax and the keyboard coordinate minimum value iPosmin, and represents the movement position of the hand Generate data.
Next, in step SN7, the pointer ngr is stored again in the register ngrSt in response to the setting of the optimum hand position in the section from the extreme point to the extreme point, and in the subsequent step SN8, the pointer ngr is incremented. Then, the process returns to step SN3 described above. Thereafter, operation data is generated by repeating steps SN3 to SN8 until the time-series data NoteGroup designated by the pointer ngr reaches “NULL”.

  As described above, in the operation data generation process, the time series data NoteGroup is referred to, and the section from the extreme point to the extreme point where the pitch change of the music changes from “maximum to minimum” or “minimum to maximum” is searched and applicable. In the interval, the optimal hand is set so that the key operation allowable range determined by the width of the player's hand falls within the key operation range determined by the maximum keyboard coordinate value iPosMax and the minimum keyboard coordinate value iPosmin defined by the time series data NoteGroup. A position is set, and motion data representing the moving position of the hand is generated.

(4) Operation of Movement Position Identification Process Next, the movement position identification process will be described with reference to FIG. When this process is executed via step SN6 (see FIG. 21) of the operation data generation process described above, the CPU 1 proceeds to step SO1 shown in FIG. In step SO1, the identification flag iRL (Hand.iRL) in the hand state data Hand is “0” and the value of the register iTend is positive, or the identification flag iRL (in the hand state data Hand) Hand.iRL) is “1”, and it is determined whether the value of the register iTend is negative. That is, it is determined whether the position is “maximum position by right-hand key operation” or “minimum position by left-hand key operation”.

If it is “maximum position by right hand key operation” or “minimum position by left hand key operation”, the determination result is “YES”, the process proceeds to step SO2, and “0” is set to the search flag idest. The search flag idest is a flag indicating the search direction. When “0”, the forward search is indicated, and when “1”, the backward search is indicated. In step SO2, the value of the register ngrSt is set in the search pointer ngrprog, and the pointer ngr is stored in the register ngrterm.
On the other hand, in the case of “minimum position by right-hand key operation” or “maximum position by left-hand key operation”, the determination result in step SO1 is “NO”, and the process proceeds to step SO3 to indicate a flag value indicating backward search. “1” is set in the search flag ids, the pointer ngr is set in the search pointer ngrprog, and the value of the register ngrSt is stored in the register ngrterm.

  Next, in step SO4, the search pointer ngrprog is stored in the register ngrsls. Next, in step SO5, the keyboard coordinate maximum value iPosMax (ngrprog.iPosMax) and the keyboard coordinate minimum value iPosmin (ngrprog.iPosmin) in the time-series data NoteGroup specified by the search pointer ngrprog are stored in the registers iPosMax and iPosmin, respectively. To do. In step SO5, an initial allowable maximum width iRngMax obtained by adding the keyboard coordinate average value ((ngrprog.iPosMax + ngrprog.iPosmin) / 2) and the half value iHandHalf of the player's hand width and the keyboard coordinate average value ((nggrprog.iPosMaxprog + ng .IPosmin) / 2), the initial allowable minimum width iRngmin is calculated by subtracting the half value iHandHalf of the player's hand width.

  Next, in step SO6, it is determined whether or not the value of the search pointer ngrprog matches the register ngrterm, that is, whether or not the movement position has been specified within the interval from the extreme point to the extreme point. If the movement position has been specified, the determination result is “NO”, and the present process ends. If not, the determination result is “YES” and the process proceeds to step SO7.

  In steps SO7 to SO9, the search pointer ngrprog is incremented (at the time of forward search) or decremented (at the time of backward search) according to the value of the search flag idest. Next, in step SO10, the keyboard coordinate maximum value iPosMax (ngrprog.iPosMax) and the keyboard coordinate minimum value iPosmin (ngrprog.) In the time-series data NoteGroup specified by the search pointer ngrprog updated for forward search (or backward search). iPosmin) is stored in registers itmpPosMax and itmpPosmin, respectively, while the keyboard maximum coordinate value ((ngrprog.iPosMax + ngrprog.iPosmin) / 2) plus the maximum allowable width itmpRngMax obtained by adding the half value iHandHalf of the player's hand width, The half value iHandHalf of the player's hand width is subtracted from the coordinate average value ((ngrprog.iPosMax + ngrprog.iPosmin) / 2). Calculating the allowable minimum width itmpRngmin was.

  Next, in step SO11, the smaller one of the initial allowable maximum width iRngMax and the allowable maximum width itmpRngMax is greater than the keyboard coordinate maximum value iPosMax stored in the register iPosMax, or the initial allowable minimum width iRngmin and the allowable maximum It is determined whether the larger one of the small widths itmpRngmin is smaller than the keyboard coordinate minimum value iPosmin stored in the register iPosmin. That is, it is determined whether a hand movement is necessary. If the movement of the hand is unnecessary, the determination result is “NO”, the process proceeds to step SO15, and the registers iPosMax and iPosmin, the initial allowable maximum width iRngMax, and the initial allowable minimum width iRngmin are updated.

  That is, in step SO15, the larger one of the register iPosMax and the allowable maximum width itmpRngMax is stored in the register iPosMax. Further, the smaller one of the register iPosmin and the allowable minimum width itmpRngmin is stored in the register iPosmin. Further, the smaller one of the initial allowable maximum width iRngMax and the allowable maximum width itmpRngMax is registered as the initial allowable maximum width iRngMax, and the larger of the initial allowable minimum width iRngmin and the allowable minimum width itmpRngmin is initially set. Register as the allowable minimum width iRngmin. Thereafter, the process is returned to the above-described step SO6, and it is determined again whether or not the movement position has been specified within the section from the extreme point to the extreme point.

  On the other hand, if it is necessary to move the hand, the determination result in step SO11 is “YES”, the process proceeds to step SO12, and operation data insertion processing for registering operation data HandPos representing the currently specified hand position is performed. Execute. Next, in step SO13, the search pointer ngrprog is stored in the register ngrsls. In step SO14, the value of the register itmpPosMax is updated to the register iPosMax, the value of the register itpposmin is updated to the register iPosmin, the allowable maximum width itmpRngMax is updated to the initial allowable maximum width iRngMax, and the allowable minimum width itmpRngmin is updated to the initial allowable minimum width iRngmin. sign up. Thereafter, the process is returned to the above-described step SO6, and it is determined again whether or not the movement position has been specified within the section from the extreme point to the extreme point.

  As described above, in the movement position specifying process, the keyboard coordinate maximum defined by the time-series data NoteGroup in the interval from the extreme point to the extreme point where the pitch change of the music changes from “maximum to minimum” or “minimum to maximum”. Motion data representing the movement position of the hand by setting the optimal hand position so that the key operation allowable range determined by the width of the player's hand is within the key operation range determined by the value iPosMax and the keyboard coordinate minimum value iPosmin. Is generated.

(5) Operation of Operation Data Insertion Processing Next, the operation of operation data insertion processing will be described with reference to FIG. When this process is executed through step SO12 (see FIG. 22) in the above-described movement position specifying process, the CPU 1 proceeds to step SP1 shown in FIG. 23 to determine the empty position of the operation data HandPos (see FIG. 19). Set to pointer hpIns. Subsequently, in step SP2, the values of the registers iPosMax and iPosmin are stored as the maximum keyboard coordinate value iPosMax and the minimum keyboard coordinate value iPosmin in the operation data HandPos specified by the pointer hpIns. In step SP3, it is determined whether or not the search flag idest is “0”, that is, whether or not forward search is being performed.

  If the forward search is being performed, the determination result is “YES”, the process proceeds to step SP4, and the sound generation in the time series data NoteGroup specified by the pointer (pointer ngr specifying the start of the extreme point) stored in the register ngrlsls is started. The time ITime (ngrsls.lTime) is registered as the start time ITime in the operation data HandPos specified by the pointer hpIns, and further, the pronunciation in the time series data NoteGroup immediately before the time series data specified by the search pointer ngrprog The start time ITime (ngrprog.prev.lTime) is registered as the end time ITTerm in the operation data HandPos specified by the pointer hpIns.

  On the other hand, if the backward search is being performed, the determination result in step SP3 is “NO”, and the process proceeds to step SP5, where the sounding start time ITime (in the time series data NoteGroup next to the time series data designated by the search pointer ngrprog ngrprog.next.lTime) is registered as the start time ITime in the operation data HandPos specified by the pointer hpIns, and the pointer stored in the register ngrlsls (pointer ngr specifying the start of the extreme point) is specified. The sound generation start time ITime (ngrsls.lTime) in the data NoteGroup is registered as the end time ITterm in the operation data HandPos specified by the pointer hpIns.

  Next, in steps SP6 to SP9, after setting a pointer value specifying the first operation data HandPos to the search pointer hpTmp, the search pointer hpTmp is incremented until the pointer hpIns-1 is reached. Then, when the search pointer hpTmp reaches one point before the pointer hpIns, the determination result in step SP8 becomes “YES”, the process proceeds to step SP9, and the pointer next (hpTmp.hd) in the operation data HandPos specified by the search pointer hpTmp. next) stores the pointer hpIns for specifying the newly inserted operation data, and stores the search pointer hpTmp in the pointer prev (hpIns.prev) in the operation data HandPos specified by the pointer hpIns. Finish.

(6) Operation of Fingering Data Generation Process Next, the operation of the fingering data generation process will be described with reference to FIG. When this process is executed via step SM5 (see FIG. 20) of the main routine described above, the CPU 1 proceeds to step SQ1 shown in FIG. 24, and specifies the pointer ngr and note data Note for specifying the time-series data NoteGroup. The pointer nTmp and the pointer hpTmp specifying the operation data HandPos are reset to zero.
Subsequently, in step SQ2, the keyboard coordinate maximum value iPosMax (hpTmp.iPosMax) in the operation data HandPos designated by the pointer hpTmp is stored in the keyboard coordinate maximum value iPosMax (Hand.iPosMax) in the hand state data Hand. At the same time, the keyboard coordinate minimum value iPosmin (hpTmp.iPosmin) in the operation data HandPos specified by the pointer hpTmp is stored in the keyboard coordinate minimum value iPosmin (Hand.iPosmin) in the hand state data Hand.

  Next, the hand movement process shown in FIG. 14 is executed via step SQ3. As described above, in the hand movement process, the middle finger coordinates Hand.iPos are used as the hand position coordinates iPos (Hand.iPos). fig [2]. Set iPos. Thus, when the position of the first hand is determined, the process proceeds to step SQ4, and the pointer hpTmp is incremented. In steps SQ5 to SQ15, finger state confirmation processing is performed in accordance with the progress of the pointer ngr, while fingering assignment is performed based on the note data Note while moving the position of the hand with reference to the operation data HandPos. .

That is, first, in step SQ5, it is determined whether the time-series data NoteGroup designated by the pointer ngr is “NULL”, that is, whether or not the fingering data has been generated. Until the fingering data has been generated, the determination result here is “YES”, and steps SQ5 to SQ15 are repeated.
Next, in step SQ6, the finger state confirmation process shown in FIG. 15 is executed. As described above, in the finger state confirmation process, when there is a finger being pressed, if the sound muting time of the sound being pressed by the finger has passed, the finger is set to the mute state. In step SQ7, the note data pointer NoteEv in the time series data NoteGroup specified by the pointer ngr is set to the pointer nTmp.

Next, in steps SQ8 to SQ10, the “finger assignment process” shown in FIG. 16 is executed via step SQ9 while stepping the pointer nTmp until there is no more note data Note specified by the pointer nTmp. As described above, in the finger assignment process, among the fingers specified by the assignment pointer idx, a finger whose finger position is equal to or less than the coordinate of the key to be played and which is not pressed is defined as a finger to be played. Assign fingering.
When fingering assignment is thus performed, the process proceeds to step SQ11, where the start time lTime (hpTmp.lTime) in the operation data HandPos specified by the pointer hpTmp is the sound generation start time lTime (ngr) in the next time-series data NoteGroup. .Next.lTime). That is, it is determined whether the next time-series data NoteGroup is before or after the break of the key operation.

Here, if the next time-series data NoteGroup is before the break of the key operation, the determination result is “NO”, the process proceeds to step SQ15, and the pointer ngr is set so as to specify the next time-series data NoteGroup. After stepping, the process returns to step SQ5 described above.
On the other hand, if the next time-series data NoteGroup is after the break of the key operation, the determination result in step SQ11 is “YES”, and the flow proceeds to step SQ12. In step SQ12, the keyboard coordinate maximum value iPosMax (hpTmp.iPosMax) in the operation data HandPos specified by the pointer hpTmp is stored in the keyboard coordinate maximum value iPosMax (Hand.iPosMax) in the hand state data Hand, The keyboard coordinate minimum value iPosmin (hpTmp.iPosmin) in the operation data HandPos designated by the pointer hpTmp is stored in the keyboard coordinate minimum value iPosmin (Hand.iPosmin) in the hand state data Hand.

  Thereafter, the process proceeds to step SQ13, and the pointer hpTmp is incremented. In the subsequent step SQ14, the middle finger coordinates Hand.iPos are set as the hand position coordinates iPos (Hand.iPos) as in step SQ3 described above. fig [2]. A hand movement process (see FIG. 14) for setting iPos is executed. Then, the process proceeds to step SQ15, the pointer ngr is incremented so as to designate the next time-series data NoteGroup, and the process returns to the above-described step SQ5.

  As described above, in the fingering data generation process, the position of the hand is first determined with reference to the motion data HandPos, and then the finger position is less than or equal to the coordinates of the key to be played among the fingers specified by the assignment pointer idx. A finger that is not pressed is assigned as a finger to be played, and each time a key operation is interrupted, the position of the hand is determined with reference to the operation data HandPos. The finger is assigned.

(7) Operation of Fingering Data Evaluation Process Next, the operation of the fingering data evaluation process will be described with reference to FIG. When this process is executed via step SM6 (see FIG. 20) of the main routine described above, the CPU 1 proceeds to step SR1 shown in FIG. 25, and specifies a pointer ngr and note data Note for specifying time-series data NoteGroup. The pointer nTmp and the pointer hpTmp specifying the operation data HandPos are reset to zero.
Subsequently, in step SR2, the counter iCost that accumulates the difference between the coordinates of the key to be played and the coordinates of the finger assigned to fingering is reset to zero. Note that the value of the counter iCost represents “difficulty to play” with respect to fingering data, as will be described later. In other words, if the difference between the coordinates of the key to be played and the coordinates of the finger assigned to fingering is small (difference accumulated value), the finger movement is small and the fingering is easy to play. When the arithmetic value is large, the finger moves with a large amount of movement and difficult to play.

  Next, in step SR3, the keyboard coordinate maximum value iPosMax (hpTmp.iPosMax) in the operation data HandPos specified by the pointer hpTmp is stored in the keyboard coordinate maximum value iPosMax (Hand.iPosMax) in the hand state data Hand. At the same time, the keyboard coordinate minimum value iPosmin (hpTmp.iPosmin) in the operation data HandPos designated by the pointer hpTmp is stored in the keyboard coordinate minimum value iPosmin (Hand.iPosmin) in the hand state data Hand. Thereafter, the hand movement process shown in FIG. 14 is executed through step SR4, and the middle finger coordinates Hand.iPos are set as the hand position coordinates iPos (Hand.iPos). fig [2]. Set iPos. Thus, when the position of the first hand is determined, the process proceeds to step SR5, and the pointer hpTmp is incremented.

In step SR6, it is determined whether or not the time series data NoteGroup designated by the pointer ngr is “NULL”, that is, whether or not the fingering data has been evaluated. Until the fingering data is completely evaluated, the determination result here is “YES”, and steps SR7 to SR16 described later are repeated.
In step SR7, the note data pointer NoteEv in the time series data NoteGroup designated by the pointer ngr is set to the pointer nTmp. Subsequently, in steps SR8 to SR11, the pointer nTmp is incremented until it reaches “NULL”, and the fingering number cfig (fingering data) in the note data Note designated by the incremented pointer nTmp is stored in the register ifig. The finger coordinates iPos (Hand.fig [ifig] .iPos) in the hand state data Hand corresponding to the fingering number cfig stored in the register ifig and the keyboard coordinates in the note data Note specified by the pointer nTmp The absolute difference from iPos (nTmp.iPos) is accumulated and stored in the counter iCost.

  Thus, when the value (difference accumulated value) representing “difficulty to play” is stored in the counter iCost based on all fingering data, the determination result in step SR8 becomes “NO”, and the process proceeds to step SR12. In step SR12, whether or not the start time lTime (hpTmp.lTime) in the operation data HandPos specified by the pointer hpTmp is earlier than the sound generation start time lTime (ngr.next.lTime) in the next time-series data NoteGroup. Determine whether. That is, it is determined whether the next time-series data NoteGroup is before or after the break of the key operation.

Here, if the next time-series data NoteGroup is before the break of the key operation, the determination result is “NO”, the process proceeds to step SR16, and the pointer ngr is set so as to specify the next time-series data NoteGroup. After stepping, the process returns to step SR6 described above.
On the other hand, if the next time-series data NoteGroup is after the break of the key operation, the determination result in step SR12 is “YES”, and the flow proceeds to step SR13. In step SR13, the keyboard coordinate maximum value iPosMax (hpTmp.iPosMax) in the operation data HandPos specified by the pointer hpTmp is stored in the keyboard coordinate maximum value iPosMax (Hand.iPosMax) in the hand state data Hand, The keyboard coordinate minimum value iPosmin (hpTmp.iPosmin) in the operation data HandPos designated by the pointer hpTmp is stored in the keyboard coordinate minimum value iPosmin (Hand.iPosmin) in the hand state data Hand.

Thereafter, the process proceeds to step SR14, and the pointer hpTmp is incremented. In the subsequent step SR15, the middle finger coordinates Hand.iPos are set as the hand position coordinates iPos (Hand.iPos) as in step SR4 described above. fig [2]. A hand movement process (see FIG. 14) for setting iPos is executed. Then, the process proceeds to step SR16, the pointer ngr is incremented so as to designate the next time-series data NoteGroup, and the process returns to the above-described step SR6.
As described above, in the fingering data evaluation process, the difference between the coordinates of the key to be played and the coordinates of the finger assigned to the fingering is accumulated, and a value representing “difficulty to play” is stored in the counter iCost. ing.

  As described above, in the second embodiment, after generating motion data representing the movement position of a hand necessary for playing a song, the position of the hand defined by the generated motion data HandPos and the corresponding finger position are generated. In consideration of the above, fingering data is generated, and “flicking difficulty” of the generated fingering data is evaluated. Then, the half width iHandHalf of the hand whose random number is changed until the number of evaluations exceeds the maximum value MAXRETRY of the re-evaluation number or until the evaluated “difficulty to play” (average value average (iCost)) falls within the allowable range value ARROWEDCOST. Based on the movement data HandPos, the fingering data is generated and evaluated accordingly to obtain fingering data that is easy to play. Fingering information for easy fingering can be generated.

  In the second embodiment, the position of the hand is determined with reference to the operation data HandPos, and the finger position is equal to or less than the coordinates of the key to be played, and the key is pressed. A finger that is not to be played is assigned as a finger to be played, but instead, the modification of the first embodiment described above is applied, the position of the hand is determined with reference to the operation data HandPos, and the hand Of these fingers, the finger having the shortest distance from the key to be pressed may be assigned as a finger to be played.

It is a block diagram which shows the structure of 1st Embodiment by this invention. 3 is a diagram showing a configuration of on-buffer data provided in a work area of a RAM 3. FIG. It is a figure which shows the structure of the music data provided in the data area of RAM3. FIG. 3 is a diagram showing a configuration of time series data provided in a data area of a RAM 3. 3 is a diagram showing a configuration of note data provided in a data area of a RAM 3. FIG. It is a figure which shows the structure of the phrase data provided in the data area of RAM3. It is a figure which shows the structure of the state data of the hand provided in the work area of RAM3. It is a flowchart which shows operation | movement of the main routine by 1st Embodiment. It is a flowchart for demonstrating operation | movement of the time series data generation process by 1st Embodiment. It is a flowchart for demonstrating operation | movement of the sound string analysis process by 1st Embodiment. It is a flowchart for demonstrating operation | movement of the maximum / minimum value process by 1st Embodiment. It is a flowchart for demonstrating the operation | movement of the neighborhood data processing by 1st Embodiment. It is a flowchart for demonstrating operation | movement of the fingering data generation process by 1st Embodiment. It is a flowchart for demonstrating operation | movement of the movement process of the hand by 1st Embodiment. It is a flowchart for demonstrating operation | movement of the finger state confirmation process by 1st Embodiment. It is a flowchart for demonstrating operation | movement of the finger | toe allocation process by 1st Embodiment. It is a flowchart for demonstrating operation | movement of the position specification process of the finger | toe by 1st Embodiment. It is a flowchart for demonstrating operation | movement of the finger | toe allocation process by the modification of 1st Embodiment. It is a figure which shows the structure of the operation data provided in the work area of RAM3. It is a flowchart for demonstrating operation | movement of the main routine by 2nd Embodiment. It is a flowchart for demonstrating operation | movement of the operation | movement data generation process by 2nd Embodiment. It is a flowchart for demonstrating operation | movement of the specific process of the movement position by 2nd Embodiment. It is a flowchart for demonstrating operation | movement of the operation | movement data insertion process by 2nd Embodiment. It is a flowchart for demonstrating operation | movement of the fingering data generation process by 2nd Embodiment. It is a flowchart for demonstrating operation | movement of the fingering data evaluation process by 2nd Embodiment.

Explanation of symbols

1 CPU
2 ROM
3 RAM
4 Input section 5 Display section 6 MIDI interface 7 Electronic musical instrument

Claims (14)

Phrase data generating means for detecting a break of an operation of performing a key operation from music data representing each sound constituting a song, and generating phrase data specifying each section delimited by the detected break;
For each section specified by the phrase data generated by the phrase data generating means, a setting means for setting an optimal hand position for key operation;
Fingering data generating means for generating fingering data assigned to the finger to be played among the fingers to be operated by keys corresponding to the position of the hand set by the setting means; A fingering information generation device characterized by: Phrase data generating means for detecting a break of an operation of performing a key operation from music data representing each sound constituting a song, and generating phrase data specifying each section delimited by the detected break;
For each section specified by the phrase data generated by the phrase data generating means, a hand corresponding to the operation range determined by the key position of the highest pitch and the key position of the lowest pitch operated in that section. Setting means for setting the position of
Fingering data generating means for generating fingering data assigned to the finger to be played among the fingers to be operated by keys corresponding to the position of the hand set by the setting means; A fingering information generation device characterized by: Phrase data generating means for detecting a break of an operation of performing a key operation from music data representing each sound constituting a song, and generating phrase data specifying each section delimited by the detected break;
For each section specified by the phrase data generated by the phrase data generating means, a hand corresponding to the operation range determined by the key position of the highest pitch and the key position of the lowest pitch operated in that section. Setting means for setting the position of
Of the fingers that are key-operated corresponding to the position of the hand set by the setting means, the finger position is positioned on the lower side than the key to be played and a finger that is not pressed is assigned to the finger to be played. A fingering information generation device comprising fingering data generation means for generating fingering data. Phrase data generating means for detecting a break of an operation of performing a key operation from music data representing each sound constituting a song, and generating phrase data specifying each section delimited by the detected break;
Motion data generating means for generating motion data representing the position of the hand performing the music from the music data;
For each section specified by the phrase data generated by the phrase data generating means, the finger position is lower than the key to be played out of each finger key-operated at the position of the hand represented by the operation data corresponding to the section. And a fingering data generating unit configured to generate fingering data allocated to a finger that is positioned and to which a finger to be played is not pressed. Phrase data generating means for detecting a break of an operation of performing a key operation from music data representing each sound constituting a song, and generating phrase data specifying each section delimited by the detected break;
Motion data generating means for generating motion data representing the position of the hand performing the music from the music data;
For each section specified by the phrase data generated by the phrase data generation means, the finger closest to the key to be played should be played out of the fingers operated by keys at the position of the hand represented by the motion data corresponding to the section. And a fingering data generating means for generating fingering data assigned to the finger. Phrase data generating means for detecting a break of an operation of performing a key operation from music data representing each sound constituting a song, and generating phrase data specifying each section delimited by the detected break;
Motion data generating means for generating motion data representing the position of the hand performing the music from the music data;
For each section specified by the phrase data generated by the phrase data generating means, the finger position is lower than the key to be played out of each finger key-operated at the position of the hand represented by the operation data corresponding to the section. Fingering data generating means for generating fingering data assigned to a finger that is to be positioned and to which a finger not to be pressed is to be played;
Fingering evaluation means for evaluating the difficulty of playing the finger according to the distance between the finger specified by the fingering data generated by the fingering data generation means and the key to be played;
Optimizing means for optimizing the motion data so that the difficulty of fingering evaluated by the fingering evaluation means falls within a preset allowable range. Generator. Phrase data generating means for detecting a break of an operation of performing a key operation from music data representing each sound constituting a song, and generating phrase data specifying each section delimited by the detected break;
Motion data generating means for generating motion data representing the position of the hand performing the music from the music data;
For each section specified by the phrase data generated by the phrase data generation means, the finger closest to the key to be played should be played out of the fingers operated by keys at the position of the hand represented by the motion data corresponding to the section. Fingering data generation means for generating fingering data assigned to the finger;
Fingering evaluation means for evaluating the difficulty of playing the finger according to the distance between the finger specified by the fingering data generated by the fingering data generation means and the key to be played;
Optimizing means for optimizing the motion data so that the difficulty of fingering evaluated by the fingering evaluation means falls within a preset allowable range. Generator. Phrase data generation processing for detecting a break in the operation of key operation from music data representing each sound constituting the song, and generating phrase data specifying each section delimited by the detected break,
For each section specified by the phrase data generated by the phrase data generation process, a setting process for setting an optimal hand position for key operation;
A fingering data generation process for generating fingering data assigned to the finger to be played among the fingers to be operated by keys corresponding to the position of the hand set by the setting process; A fingering information generation processing program that is executed by Phrase data generation processing for detecting a break in the operation of key operation from music data representing each sound constituting the song, and generating phrase data specifying each section delimited by the detected break,
For each section specified by the phrase data generated by the phrase data generation process, a hand corresponding to the operation range determined by the key position of the highest pitch and the key position of the lowest pitch operated in that section. Setting processing to set the position of
A fingering data generation process for generating fingering data assigned to the finger to be played among the fingers to be operated by keys corresponding to the position of the hand set by the setting process; A fingering information generation processing program that is executed by Phrase data generation processing for detecting a break in the operation of key operation from music data representing each sound constituting the song, and generating phrase data specifying each section delimited by the detected break,
For each section specified by the phrase data generated by the phrase data generation process, a hand corresponding to the operation range determined by the key position of the highest pitch and the key position of the lowest pitch operated in that section. Setting processing to set the position of
Of the fingers that are key-operated corresponding to the position of the hand set by the setting process, the finger position is positioned on the lower side than the key to be played and a finger that is not pressed is assigned to the finger to be played. A fingering information generation processing program for causing a computer to execute fingering data generation processing for generating fingering data. Phrase data generation processing for detecting a break in the operation of key operation from music data representing each sound constituting the song, and generating phrase data specifying each section delimited by the detected break,
Action data generation processing for generating action data representing the position of a hand performing a song from the song data;
For each section specified by the phrase data generated by the phrase data generation process, the finger position of the finger operated at the position of the hand represented by the operation data corresponding to that section is lower than the key to be played. A fingering information generation processing program for causing a computer to execute fingering data generation processing for generating fingering data assigned to a finger to be played that is positioned and a finger that has not been pressed. Phrase data generation processing for detecting a break in the operation of key operation from music data representing each sound constituting the song, and generating phrase data specifying each section delimited by the detected break,
Action data generation processing for generating action data representing the position of a hand performing a song from the song data;
For each section specified by the phrase data generated by the phrase data generation process, the finger closest to the key to be played should be played out of each finger that is key-operated at the position of the hand represented by the motion data corresponding to that section. A fingering information generation processing program for causing a computer to execute fingering data generation processing for generating fingering data assigned to a finger. Phrase data generation processing for detecting a break in the operation of key operation from music data representing each sound constituting the song, and generating phrase data specifying each section delimited by the detected break,
Action data generation processing for generating action data representing the position of a hand performing a song from the song data;
For each section specified by the phrase data generated by the phrase data generation process, the finger position of the finger operated at the position of the hand represented by the operation data corresponding to that section is lower than the key to be played. Fingering data generation processing for generating fingering data assigned to a finger to be played that is positioned and a finger that is not pressed
A fingering evaluation process for evaluating the difficulty of fingering according to the separation distance between the finger specified by the fingering data generated by the fingering data generation process and the key to be played;
An optimization process for optimizing the motion data is executed by a computer so that the difficulty of fingering evaluated by the fingering evaluation process falls within a preset allowable range. Finger information generation processing program. Phrase data generation processing for detecting a break in the operation of key operation from music data representing each sound constituting the song, and generating phrase data specifying each section delimited by the detected break,
Action data generation processing for generating action data representing the position of a hand performing a song from the song data;
For each section specified by the phrase data generated by the phrase data generation process, the finger closest to the key to be played should be played out of each finger that is key-operated at the position of the hand represented by the motion data corresponding to that section. Fingering data generation processing for generating fingering data assigned to the finger;
Fingering evaluation means for evaluating the difficulty of playing the finger according to the distance between the finger specified by the fingering data generated by the fingering data generation process and the key to be played;
An optimization process for optimizing the motion data is executed by a computer so that the fingering difficulty evaluated by the fingering evaluation means falls within a preset allowable range. Finger information generation processing program.

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