JP2615720B2 - Automatic composer - Google Patents

Description

Description: TECHNICAL FIELD OF THE INVENTION The present invention relates to an automatic composer.

[Background] One of the important factors to consider regarding the quality of an automatic composer
One is whether the composer has the potential to create songs that humans have been accustomed to, in other words, songs that are not purely mechanical but rich in musicality.

For example, Japanese Patent Application No. 56-125603 (Japanese Patent Application No. 60-40027)
Is to randomly sample individual pitch data from a series of pitch data (for example, data of 12 scales), and if the sampled data satisfies a limited condition, it is adopted as a melody note and If the condition is not satisfied, an automatic composer is disclosed which does not adopt it as a melody note, resamples it again, and repeats the condition inspection. Therefore, the melody generation process of the automatic composer is basically a try-and-error method. At the stage where the pitch data is randomly sampled, a completely random sequence of pitches is created. With this chaotic pitch sequence, no melody can be realized at all (although a good melody may be possible due to astronomical contingencies). Therefore, in order to bring this disorder into some order, a kind of filtering (selection) called a condition check is performed. In this case, the degree of selection is an important factor. If the selection is too tight, the melody generated will be one-patterned; if too loose, the original disorder will be dominant.

The above-mentioned automatic composer is more suitable for composing a melody that is elusive in style than a melody that humans have become familiar with, and is effective mainly as a music creating device for listening sound training and performance practice (familiar) Novel songs without music are generally difficult to transcribe and play). In this sense, the abilities mentioned at the beginning are not combined.

In order to solve the above-mentioned problem, the applicant of the present application filed Japanese Patent Application
No. 86571 (filed on April 8, 1987), Japanese Patent Application No. 62-121037
No. (filed on May 20, 1987) proposes an automatic composer having various features. The automatic composer disclosed in these patent applications includes a chord progression providing means for providing a chord progression, a melody inputting means for inputting a melody (motif), and a feature parameter extracting means for analyzing the input melody and extracting feature parameters. And a feature parameter changing means for changing the extracted feature parameters for each section in accordance with music composition instruction information from the user, and a melody synthesizing means for synthesizing a melody based on the chord progression and the characteristic parameters. The melody synthesizing means includes a dispersive chord generating means for generating a dispersive chord (arpeggio) according to a chord progression, and a non-harmonic adding means for adding a non-harmonic to the generated dispersive chord. Therefore, these automatic composers grasp the melody as a sound sequence in which a chord sound and a non-harmonic sound are mixed as a basic approach of composition, and have completed a sound sequence of only a chord sound by a distributed chord generation means. Thereafter, the non-harmonic sound adding means adds the non-harmonic sound to complete the melody sound sequence. Therefore, there is a high possibility that a tune rich in musicality will be composed.

[Object of the Invention] The present invention is an improvement of the invention of the above patent application,
It is an object of the present invention to provide an automatic composer in which a user composes a song by making full use of a given chord progression to compose a song.

According to the present invention, in order to achieve the above object, a chord progression giving means for giving a chord progression of a music, and a feature parameter for generating a plurality of feature parameters for characterizing a melody to be synthesized Generating means, and a melody synthesizing means for synthesizing a melody composed of a mixture of harmony and non-harmonic sounds as a predetermined function based on the chord progression and the characteristic parameter, and the characteristic parameter generating means includes: By dividing the chord progression into a plurality of sections and determining the degree of coincidence of chord progressions between the divided sections, a music format extraction means for extracting a music format, and a music format from the music format extraction means Is received as a control input, and the characteristic parameter is reduced according to the format of the music so that the format of the music is reflected in the melody to be synthesized. And a feature parameter control means for controlling a part thereof.

As a result, the format (hierarchical structure) of the music hidden in the chord progression is reflected in the automatically generated melody, and the consistency and diversity of the melody are controlled.

In one configuration example, the song format extracting unit includes a matching score evaluating unit that evaluates a matching score of chord progressions between passages of a song, and a structure identifier assigning unit that assigns a structure identifier to each passage using the evaluated matching score. And means.

In one configuration example, the feature parameter control unit includes:
As at least a part of the characteristic parameters, a means for controlling a pattern of a dispersed chord included in the melody synthesized by the melody synthesizing means is included.

In one configuration example, the feature parameter control unit includes:
As at least a part of the characteristic parameter, a means for controlling a range of a melody generated by the melody synthesizing means is included.

Further, according to the present invention, a chord progression giving means for giving a chord progression of a music, a feature parameter generating means for generating a plurality of feature parameters characterizing a melody to be synthesized, and a chord progression means based on the chord progression and the feature parameter Melody synthesizing means for synthesizing a melody composed of a mixture of harmony and non-harmonic sounds as a predetermined function of the melody, wherein the feature parameter generating means includes a melody inputting means for inputting a melody, and a melody inputting means. A feature parameter extraction means for analyzing and extracting a plurality of feature parameters; and extracting the format of the music by dividing the chord progression into a plurality of sections and determining the degree of coincidence of the chord progressions between the divided sections. A melody to be synthesized by receiving, as a control input, a song format from the song format extracting unit and the song format from the song format extracting unit. And wherein the parameter changing means for changing at least part of the extracted feature parameters in accordance with the format of the music so that the format of the music is reflected in,
There is provided an automatic composer characterized by having the following.

Note that the extracted music format information (hierarchical structure data representing the structural relationship between music sections) can also be used to control characteristic parameters of other melodies, for example, rhythm parameters (eg, pulse scale). .

[Example] Hereinafter, an example of the present invention will be described. This automatic composition device employs an approach of composing a sound by dividing the sound into a harmony and a non-harmony. As the basic data for composition,
The chord progression information, the motif (melody input by the user), the pulse scale used for controlling the rhythm or pitch sequence of the melody to be generated, and the type of basic scale are given. Each sound included in the motif is identified as a harmony or a non-harmony by using chord information used in each section. The part of the motif excluding the non-harmonic is the arpeggio (dispersion chord) of the motif. From this arpeggio, features of the arpeggio and (characteristic elements included in the tone of the arpeggio) are extracted. In addition, for motifs that are distinguished between harmony and non-harmony, by using music knowledge for classifying non-harmony (stored in a production rule data memory described later), The type (characteristic) of each non-harmonic sound included in the motif can be extracted. That is, information (characteristics of non-harmonic sounds) indicating what non-harmonic sounds are distributed in the motif and how are obtained. Further, from the chord progression, the hierarchical structure and tonality structure of the music are extracted.

The generation of the melody includes an arpeggio generation step, a non-harmonic sound addition step, and a pitch sequence generation step. In the arpeggio generation step, arpeggio generation is controlled by the hierarchical structure extracted from the chord progression information. When a new arpeggio is generated according to the hierarchical structure, the arpeggio features are generated from the arpeggio features (features of the arpeggio extracted from the motif or modified versions thereof) and correspond to the generated arpeggio styles. By applying the chord, an arpeggio represented by a pitch sequence is generated. A non-harmonic tone is added to the arpeggio generated in this manner. The music knowledge described above is again used to add non-harmonic sounds. In the inference of adding a non-harmonic sound, it is assumed that the non-harmonic sound that can be added satisfies the characteristics of the non-harmonic sound and that it is a chromatic sound.
The scale note in this case is a note on a scale obtained by turning the principal note (key, tonality) of the basic scale according to the tonality structure extracted from the chord progression. Since inference is performed using common musical knowledge in the classification of non-harmonic sounds and the addition of non-harmonic sounds, "reversibility" is provided between the analysis and synthesis of the melody by the present apparatus. Complete reversibility means that when a certain melody is analyzed and a certain analysis result is obtained, and a melody is generated based on the analysis result, the generated melody matches the original melody. That is.
The pitch sequence of the melody is completed by adding a non-harmonic sound to the arpeggio. On the other hand, the melody note length sequence is obtained as follows. In other words, the basic rhythm (length sequence) is optimally combined or optimally divided using a pulse scale so as to have a target number of notes (for example, the total number of harmony and non-harmony). Which note is divided or combined at which position depends on the weight of each pulse point of the selected pulse scale. Therefore, consistent rhythm control is possible.

<Overall Configuration> FIG. 1 shows an overall configuration diagram of the automatic music composer according to the present embodiment. The CPU 1 is a control device for realizing the automatic music function in the present device. From input device 2, motif (melody), chord progression, type of pulse scale to be used,
The type of scale to be used is input. The input motif is stored in the motif memory 3. The chord progression memory 4 is a memory for storing chord progression information. The information in the memory 4 is used by the CPU 1 when analyzing chord progression, extracting or generating an arpeggio, and the like. The scale data memory 5 is a memory for storing scale data representing various kinds of scales. Before composing, the user selects a specific scale as a scale to be used in the music from the scale set of the memory 5. Can be. The production rule data memory 6 stores music knowledge for classifying non-harmonic sounds. This musical knowledge is used when classifying non-harmonic sounds included in the motif, and when adding non-harmonic sounds to the arpeggio. The pulse scale memory 7 is a memory for storing various pulse scales (sets of pulse scales). At the start of composition, the user considers the characteristics of the rhythm to be given to the music and selects a desired one from the set of pulse scales. Can be selected. The selected pulse scale is used to generate the melody rhythm (length sequence). The melody data memory 8 stores the completed melody data.
The external storage device is used as a copy of the melody data stored in the melody data memory 8, another musical knowledge, and a resource for another music composition program. The work memory 10 stores various data used by the CPU 1 during operation, for example, a tonality structure, a hierarchical structure, and various variables. Monitor 11 is CRT12,
Stave printer 13, Musical tone formation circuit 14, Sound system
It is composed of 15 components and can display and output composition results and analysis results through these devices.

<Composition General Flow> FIG. 2 shows the overall flow (composition general flow) of the apparatus in the composition mode.

In the initial setting of 4-1, basic information for composing is input by the user to the automatic music composition machine. The information that the user informs the automatic composer includes (1) BEAT, (2)
The pulse scale type (3) scale (4) fully automatic or motif input is shown. BEAT is the length of one measure represented by the number of notes of the basic unit length (the shortest note), and thus defines the time signature of a song. For example, if the basic unit length of a note is a sixteenth note for a quadruple tune,
If BEAT = 16 is set, the length of one bar is 4 beats. 4-
The pulse scale selected in step 1 is information for temporarily controlling the rhythm of a song composed by the automatic composer. The pulse scale is a scale in which each pulse point having an interval of the basic unit length is weighted to indicate the ease of combining notes or dividing notes (see FIGS. 7 and 12). ),
The use of this pulse scale controls the melody tone train. Therefore, selecting the type of the pulse scale corresponds to selecting the rhythmic feature of the song composed by the automatic composer. The type of scale (for example, diatonic scale) selected in 4-1 is the scale used by the automatic composer in composing music. Further, in the initial setting 4-1, the user decides whether to perform the composition automatically or based on the motif. In the case of full automatic, as data necessary for composition,
(1) chord progression, (2) production rules (3)
The pulse scale is read into the work memory 10 (4-
3), (1) basic rhythm (tone length pattern),
An essence composed of (2) arpeggio features (PCi: see FIG. 5) and (3) non-harmonic features (RSi: see FIG. 5) is generated according to the user's instructions (4-4). On the other hand, in the composition mode using motifs, data reading 4-
Motif (input melody) other than the above data as 5
(1) Rhythm (2) as essence
Arpeggio pattern (3) Features of arpeggio pattern,
(4) Non-harmonic features are extracted from this motif (4-5). In particular, non-harmonic features are obtained by inference based on production rules. In each of the fully automatic mode and the motif use mode, chord progression evaluation 4-7 is performed, where (1) hierarchical structure (2) tonality structure (3) scale is extracted from chord progression information. This hierarchical structure expresses the consistency and diversity of the songs inherent in the chord progression. Further, the tonality structure defines a key (fundamental tone) of a scale used in each section. The process indicated by "scale" is for using a specific scale in a certain special chord section regardless of the initially set scale. With the processing up to 4-7, the "analytical work" for composition has been completed. For example, the characteristics of the arpeggio are information necessary for generating an arpeggio pattern, and the characteristics of the non-harmonic sound characterize the non-harmonic sound added to the arpeggio. The production rule is used to infer whether the non-harmonic sound added to the arpeggio is appropriate. The tonality structure also restricts the melody sound candidates in each section. The hierarchical structure can be used to determine whether to generate a new arpeggio pattern. The pulse scale is used for generating a rhythm. In the melody generation 4-8, (1) selective generation of arpeggio patterns (LLi: see FIG. 5), (2) setting of a range of arpeggio patterns (3) generation of arpeggios of pitch expression, and (4) non-harmonic sounds (5) Rhythm generation is performed.

<Variable list, data format> The list of main variables used in the flow described later
The data format is shown in FIG. 4 to FIG. The data format is merely an example, and any other appropriate data format can be used.

<Initial setting> Initial setting 4- in composition general flow (Fig. 2)
9 is illustrated in detail in FIG. Select with this initial setting
The meaning of BEAT, the type of pulse scale (PULS), the type of scale (ISCALE), and the meaning of fully automatic or motif input have been described with reference to FIG. The value of PULS serves as a pointer to a specific pulse scale stored in the pulse scale memory 7 (FIG. 1), and the value of ISCALE serves as a pointer to specific scale data stored in the scale data memory 5.

<Data Reading> As shown in the composition general flow of FIG. 2, after the initial setting, data reading is performed at 4-3 or 4-5. In the case of full automatic, motif data is not read because no motif is used as basic data for composition. The reading of each data will be described below.

FIG. 10 shows an example of chord progression data stored in the chord progression memory 4 (FIG. 1). FIG. 11 is a flowchart for loading the chord progression data stored in the chord progression memory 4. In the memory map shown in FIG. 10, the code type (CDi) is located at an even address, and the length of the code is located at the next address (odd address).
For example, CDi with hexadecimal value of the display 507 represents the code G _7th, CRi code length with a value of 10 indicates that a 16 times the fundamental time length (e.g., sixteenth note) .

In FIG. 11, the register CDi contains the code appearing at the i-th position of the song to be composed, and CRi contains the length thereof.
CDNO contains the total number of codes. The other points are apparent from the description of FIG. 11, and thus the description is omitted.

FIG. 12 shows an example of pulse scale data stored in the pulse scale memory 7 (FIG. 1). FIG. 13 is a flowchart for loading the pulse scale of the type selected in the initial setting from the pulse scale memory 7. In this example, the pulse scale type (PUL) selected in the initial setting to select the rhythm characteristics of the song to be composed
S) indicates a specific address (for example, 0) in the pulse scale memory 7, and the address contains the start address of the selected pulse scale data. The start address stores the number of sub-scales (scales having only weights of 0 and 1) constituting the pulse scale, and data of each sub-scale is stored in the subsequent address. For example, the normal pulse scale has five sub-scales FFFF, 5555, 1111, 0101, and 0001.
(Hexadecimal representation) and the corresponding binary representation is shown in FIG. In the case of the normal pulse scale, the first pulse point (the rightmost position in FIG. 7) has a maximum weight of 5, which means that the rhythm generated when the normal pulse scale is selected. Indicates that a note is most likely to be present at the first position of each section (measure).

FIG. 14 shows the production rule data memory 6 (first
2) shows an example of production rule data stored in FIG. FIG. 15 is a flowchart for reading the data stored in the memory 6. The entire production rule expresses musical knowledge for classifying non-harmonic sounds included in the melody, and each production rule data includes lower limit data Li and a function type as data that prescribes a premise of the rule. Function instruction data X to indicate
i, upper limit data Ui, and data Y as the conclusion of the rule
It has i and Ni. The function is a numerical representation of the feature of the melody to be analyzed, and an example is shown in FIG. 31 described later.
It is a premise (proposition) of the production rule that the value Fxi of the function represented by the data Xi is equal to or more than Li and equal to or less than Ui (Li ≦ Fxi ≦ Ui), and the conclusion when this premise is satisfied is data It is indicated by Yi, and the conclusion when this premise is not satisfied is indicated by data Ni. When the data Yi or Ni has a positive value, the value indicates the number of the next production rule to be referred in forward inference,
When it has a negative value, the type of the non-harmonic sound is represented by its absolute value. Forward inference always starts with one rule, and this rule is called a root. Forward finding ends when it finds a negative conclusion Yi or Ni.

In the case of the address assignment of the production rule data shown in FIG. 14, the data of each production rule is stored in five consecutive addresses starting from the address of the lower limit data Li. For details, Li is an address divisible by 5.
Xi is stored at the address of remainder 1 divided by 5, Ui is stored at the address of remainder 2, Yi is stored at the address of remainder 3, and Ni is stored at the address of remainder 4.

In FIG. 15, RULENO is set with the total number of production rules. The other points are clear from the above description and the description of the flow.

FIG. 16 shows an example of motif data (melody data) stored in the motif memory 3. FIG. 17 is a flow chart for reading motif data which is the basis of composition.
In the case of FIG. 16, the pitch data MDi of the note is stored at the even address, and the pitch data MRi of the note is stored at the next odd address. The number of notes of the motif is set in MDNO in FIG.

 This concludes the description of data reading.

<Generation of Essence> In the fully automatic composition mode using no motif, after reading data, rhythm, arpeggio pattern features, and non-harmonic features are generated as the essence of the song (4-4 in FIG. 2). FIG. 18 shows a flow chart of this essence generation. These essences are specified by the user or generated automatically. For example, the setting of the reference rhythm pattern in 22-1 is performed when automatic rhythm pattern generation means is selected, for example, when the time signature is 4/4 time and the pulse scale is normal. Is automatically generated as a reference rhythm pattern or the user inputs a favorite rhythm pattern. 22-2 Arpeggio pattern feature setting and 22
The feature setting of the non-harmonic tone of -3 is also performed automatically or by user input. FIG. 19 illustrates a flowchart for automatically setting the features of the arpeggio pattern by random number generation and the like, and FIG. 20 illustrates a flowchart for setting the features of the non-harmony by inputting by the user.

PC in feature setting of arpeggio pattern (Fig. 19)
_{1 to} PC ₅ are the number of harmony to form an arpeggio in a section (for example, a bar) of a predetermined length, the highest harmony, the lowest harmony, the maximum value of the difference between adjacent harmony, the adjacent sum. The minimum value of the difference between voices is shown (see FIG. 5). Each PC
Can be generated for each section, and can be obtained by setting upper and lower limits of possible values and generating a random number therebetween. Alternatively, a series of PCs for the progress of the music may be prepared in a database, and a desired PC series may be selected.

In the non-harmonic feature setting shown in Fig. 20,
Displaying the keyword corresponding to each non-harmonic tone type a,
The user is prompted for input (24-2). The sequence of the non-harmony identifier a input by the user is entered in the RSi array (24−
3, 24-6, 24-7). When the code EOI indicating the end of the input is called, the number of non-harmonics is put in RSNO and the flow exits (24-8).

<Extraction of Essence> In the composition mode using the motif, after reading the data, the essence (rhythm, arpeggio pattern, features of the arpeggio pattern, features of the non-harmonic tone) of the song is extracted from the motif (FIG. 2, 4- 6).

The rhythm evaluation of the motif is illustrated in FIG. 21, the arpeggio pattern extraction is illustrated in FIG. 25, the arpeggio pattern feature extraction is illustrated in FIG. 28, and the non-harmonic feature extraction is illustrated in FIG. 29. In these flows, each essence is performed for each section (measure).

In the rhythm evaluation of FIG. 21, Ps in 25-1 contains positional information indicating the number of the note at the beginning of the measure of the target bar, and Pss at the beginning of the bar indicated by Ps. Length of note protruding into previous bar (basic time expression)
, And Pe contains the positional information of the last note of the target bar (the note immediately preceding the first note of the next bar). Rr shown in 25-2 is a 16-bit register for storing the rhythm pattern of the target bar. If the length of one bar is 16, the first bit position of the register rr indicates the first basic time of the bar. Similarly, the Nth bit position represents the Nth basic time from the beginning of the bar. The processing from 25-3 to 25-9 is
In this process, the positions of the notes from the note Ps to the note Pe of the motif are obtained using the motif note length data MRi, and are written in the corresponding bit positions of the register rr. For example, if a result of 0001000100010001 is obtained as rr, this pattern rr indicates that a sound is generated at the first beat, second beat, third beat, and fourth beat of the target bar.

Details of the calculation of Ps, Pss, Pe, and Pee are shown in FIGS. Pee represents the length of the note following Pe, that is, the length of the note at the beginning of the next bar interrupting the target bar.

In the flow of calculating Ps and Pss in FIG. 23, beat is the length of one measure (basic time length expression), and bar is the number of the target measure (representing the measure number specified by the user. The designated measure number is 1). If it is less than or greater than the number of bars in the song (nmo), it is an input error.
Ps = 1 and Pss = 0 are set (27-4, 27-5). The reason for setting Ps = 1 is that in the case of the first measure, the first note of the measure is the first note of the song or the first note of all motif data, and the reason for setting Pss = 0 is the preceding measure. Is not present. A ₁ obtained in 27-2 is the length from the beginning of the music to the bar at the front of the target bar, and this length a ₁ is the length obtained by accumulating the motif duration data MRi from the beginning. S (27-7, 27-8, 27-10, 27-1
2). When S = a ₁ holds, the next note of the i-th pitch data finally accumulated in S starts from the beginning of the target bar. Therefore, Ps = i + 1 and Pss = 0 (27−
9). On the other hand, when S> a ₁ holds, the note having the note length data added last to S, that is, the i-th note is the first note of the target bar. Therefore, Ps = i. The Pss = MRi-S + a ₁ to (27-9).

The Pe and Pee calculation flow shown in FIG. 24 performs processing very similar to that of FIG. However the length of the beginning of the song to the rear bar line of the target bar enters the a _1, the description thereof is omitted for other points.

In the arpeggio pattern extraction flow shown in FIG. 25, the arpeggio pattern {LLi} is extracted from the motif of the target bar. An outline of the processing is as follows. For the measure indicated by Ps and Pe, the corresponding chord in the chord progression information is used to determine whether the motif data is a harmony, and the sound determined to be a harmony is determined. On the other hand, the corresponding note that constitutes the chord is searched for from the chord, and the data in the form of LL is obtained. To put it in detail, the first note (Ps) to be evaluated is also selected from the motif data. The last note (Pe) is obtained (29-1). Next, constituent sound data is generated from the chord data (29-2, FIG. 26, FIG. 27).
Figure). As shown in FIG. 26, the chord constituent sound data memory stores chord constituent sounds for each type of chord whose root is C.
It is stored in the lower 12 bits of 16 bits. Each bit position represents each note name, and the lowest bit position is C (C). For example, cc = 0091 (hexadecimal) has "1" in the bit positions of "do", "mi" and "so", and represents a major constituent sound of C. Now, assuming that the code of the target section is Gmaj, the CD is
0007 (hexadecimal). From the chord configuration sound data memory,
The major chord constituent sound data cc (= 0091) at the address specified by the upper 8 bits of the CD is read out, and the lower 12 bits are replaced by the root value indicated by the lower 8 bits of the CD as shown in FIG. By turning to the left, the bit of "1" is moved to bit positions 7, 11, and 2 representing S, S, and L, and the chord constituting sound of Gmaj is expressed. In this way, chord constituent sound data is generated from the chord of the target section. Next, the scale counter i and the harmony sound counter k are initialized (29-3, 29-4). The process of 29-5 is a process of converting the pitch data MDi of the motif into the same data formation as the chord configuration sound data cc. For example, the sound of “G” is converted to data mm having “1” in bit position 7.

At 29-6, it is checked whether or not this pitch data mm is a chord constituent sound. This can be determined by taking the logical product (mm∧cc) of the pitch data mm and the chord constituent sound data cc. In 29-7 to 29-13, it is checked which of the bits “1” of the chord constituent sound data cc matches the bit “1” of the pitch data mm of the motif, and as a result c To the arpeggio pattern data LLk. At 29-15, the counter i is advanced to the next note, and LL is calculated until the note number reaches Pe (29-16). The LLNO of 29-17 contains the number of chords (length of the arpeggio pattern) in the target section.

The features of the arpeggio pattern in FIG. 28 are derived from the arpeggio pattern extraction results {LLi} and LLNO in FIG.

In the feature extraction of the non-harmonic sound shown in FIG. 29, a pattern of the type of the non-harmonic sound distributed in the motif of the target section is obtained. Set the non-harmonic counter and note counter (33
-2, 33-3), when the note of interest is a non-harmonic tone (33-4), a function F representing the characteristic element of the motif centered on the note is calculated, and forward inference by the production rule is performed. By executing, the type of non-harmonic sound is obtained and substituted into RSj (33-5 to 33-8). By performing this non-harmonic classification processing until Pe is reached, the arrangement of the types of non-harmonic sounds of the motif of the target section is set in the array {RSj}. The total number of non-harmonic tones in the target section is entered in the PSNO of 33-11.

The details of the process for determining whether or not the MDi shown in 33-4 is a non-harmonic tone are shown in FIG. This determination process is similar to the process of determining whether or not the note of interest is a harmony in the extraction of the arpeggio pattern (FIG. 25), and focuses on the constituent sounds of the chord in the target section. It can be determined based on whether or not the note name of the note that is present is included.

In the calculation of the function F in 33-6, in forward inference, a condition or a factor of a motif (melody) necessary for classifying a non-harmonic tone is calculated. FIGS. 31 to 39 show specific examples. In this example, as the function F, F ₁ : the number of the note (non-harmonic) to which the note of interest is located (the position of the rear chord) F ₂ : the number of the note before the note of interest F ₃ : Number of non-harmonic tones from forward to backward harmonic F ₄ : Pitch difference between forward and backward harmonic F ₅ : Non-harmonic pitch distribution between forward and backward harmony F ₆ : Whether the pitch of the melody from front harmony to backward harmony changes monotonously F ₇ : backward harmony F ₈ : Calculates the pitch difference between the preceding chord and the preceding chord and the pitch difference between the preceding chord and the preceding chord. (Fig. 31). In addition, information indicating whether the beat is a weak beat or a strong beat, and information for distinguishing a sound duration may be added to the set of functions F. The flowchart for calculating each function F is clear from the description of the function itself, so the description is omitted.

Details of the forward inference in 33-7 are shown in FIG. First, the rule number pointer P is set to "1" indicating the rule that is the root of the production rules (44-1). Thereafter, it is checked whether or not the prerequisite part (Lp ≦ FxP ≦ Up) of the rule indicated by the rule number pointer P is satisfied, and when it is satisfied, the data Yp of the positive conclusion part of the rule is used as a pointer to the next rule. If not, the data Np of the negative conclusion part of the rule is used as a pointer to the next rule. However, when the data Yp and Np are negative values, the final conclusion has been reached, and the absolute values (−Yp and −Np) are set in the conclusion register as identifiers of the non-harmonic tone types. According to the flow, when the condition Lp> Fxp of 44-3 or the condition Fxp> Up of 44-5 is satisfied, the precondition Lp ≦ Fxp ≦ Up of the rule P is not satisfied, so the data Np of the negative conclusion part of the rule is not satisfied. Is substituted into a (44-4, 44-6). In other cases, since the premise is satisfied, the data Yp of the positive conclusion part of the rule P is entered in a (44-2). This a is substituted into P (44-7). When P is a positive value, the process returns to the next rule check as the next rule number pointer, and when P is negative, -P is set to the non-harmonic classification. The result is (44-8, 44-9).

As an example of the classification of non-harmonics, in the calculation of the function F, F ₁ = 1: the rear harmonics are one after the non-harmonics of interest F ₂ = −1: the forward harmonics are focused on F ₃ = 1 in front of the non-harmonic to be played, the number of notes between the preceding and following harmony is one F ₄ = 8: The pitch difference between the preceding and following harmony is 8 F ₅ = 2 : The non-harmonic between the preceding and following harmony is distributed in the middle of the pitch of the preceding and following harmony. F ₆ = 1: The melody from the front harmony to the rear harmony has a monotonous change in pitch. F ₇ = 1: Proceed with a pitch difference of 1 to the backward harmony F ₈ = 7: Proceed with a pitch difference of 7 from the forward harmony
Let's make an inference using the data shown in Figure 14.

First, when P = 1 (root), the prerequisite 0 ≦ F ₂ ≦ 0 is not satisfied because F ₂ = −1. Therefore, the negative conclusion part N ₁ = 3 of the root becomes the pointer of the rule to be checked next.

At P = 3, the prerequisite 0 ≦ F ₁ ≦ 0 of Rule 3 is not satisfied because F ₁ = 1. Therefore, N ₃ =
5 becomes the pointer of the next rule.

At P = 5, the premise 0 ≦ F ₄ ≦ 0 of Rule 5 does not hold because F ₄ = 8. Therefore, N ₅ = 6
Becomes P.

At P = 6, the premise 1 ≦ F ₆ ≦ 1 of rule 6 holds because F ₆ = 1. Therefore, Rule 6
Positive conclusion part of the data Y ₆ = 7 next the pointer P of the access rules of.

At P = 7, the premise 3 ≦ F ₈ ≦ ∞ of Rule 7 holds because F ₈ = 7. Here, Y ₇ = −2 (negative). Therefore, the conclusion = 2 (the identifier of the classified non-harmonic sound).

As can be seen from this example, for any kind of non-harmonic tone, a finite number of propositions are satisfied (the fact that the premise is not satisfied is equivalent to the proposition that makes the premise false).
It can be identified by the musical knowledge of doing. To express this knowledge, a function F has been calculated and a production rule has been created. That is, the function F is information on the check items of the melody used in the knowledge for classifying the non-harmonic sounds, and the production rule data is obtained by connecting the columns of rules up to the result of classification of each non-harmonic sound with a pointer. It was done.

<Evaluation of Chord Progression> One feature of the apparatus of the present embodiment is that the chord progression is maximally utilized for composing music. That is, the second
In the chord progression evaluation shown in 4-7 of the composition general flow in the figure, the hierarchical structure and tonality structure of the music are obtained using the given chord progression as a clue. The hierarchical structure relates to the consistency and diversity of the music, and is used for controlling the generation of arpeggios in melody generation described later. On the other hand, the tonality structure represents a change in tonality (key) as the music progresses, and is used to select a scale key used in each section in melody generation described later. Further, in the chord progress details, a process of planning the use of a special scale for a section of the special code is also executed.

Hereinafter, the extraction of the hierarchical structure will be described in detail with reference to FIGS. 41 to 43.

The flow shown in FIG. 41 is a flow for calculating the similarity of the chord progression between blocks in units of blocks having a length such as a passage.

First, the length SUM of the song is calculated by accumulating the length CRi of each chord in the chord progression information (45-1), and the length of the block indicated by barno (number of measures) is converted to the basic tone length expression. After conversion, the block length is set to 1 (45-2), and the music length SUM is divided by the block length 1 to calculate the number m of blocks included in the music (45-3). The counter i for the reference number of the block to be compared is initialized to "0" (45-4).

In steps 45-8 to 45-18, the code similarity Vij between the i-th block and the j-th block (j ≧ i) is calculated. As a function of similarity, You are using Where l is the length of the block, Vs
Represents the number of matching codes obtained when the code of the i-th block and the code of the j-th block are compared for each reference tone length. The similarity function Vij takes a value from 0 to 100. When the similarity function Vij is 100, the chord progression of the two blocks completely matches (100%), and when 0, the chord progression completely does not match.

The calculation of the similarity between the i-th block and the j-th block starts from the position of j = i (45-6), and every time the similarity is obtained, the similarity with the next block is calculated by j = j + 1. (45-20, 45-7) When the operation is performed until the final block is reached (45-19), the i-th block is shifted (45-22, 45-5) by i = i + 1, and i is the final block. Repeat the process until.

As a result, as the similarity Vij of the code of the j-th block to the i-th block, Is obtained. Note that Vij = Vij, that is, the code similarity of the j-th block to the i-th block is equal to the code similarity of the i-th block to the j-th block. Vii = 100.

Calculation result of code coincidence between blocks in Fig. 40 ｛Vi
j｝ is used in the generation of the hierarchical structure data in FIG.

In FIG. 42, c is a counter for calculating the hierarchical structure, and the hierarchical structure identifier of the j-th block is set in Hj. Hj takes an integer value of 0, 1, 2,... As a value. This is a, a'b, b 'in ordinary expressions.
(See HIEi in FIG. 6). In the flow shown in FIG. 42, a block having the same value (even value) as that of the reference block is attached to a block having a 100% code match with a certain reference block (46-10, 46-1).
1) A block having a code progression that is a modification of the code progression of the reference block is assigned a hierarchical structure identifier of a value obtained by adding 1 to the hierarchical structure identifier of the reference block, as a block having a code progression modified from the code progression of the reference block (1). 46-12, 46-13). A block having a similarity of less than 70% is treated as a block having a hierarchical structure independent of the reference block. The first block of the music is selected as the first reference block (46-2), and the blocks that match 100% or 70 to 100% with this reference block have Hj = 0 and Hj = 1, respectively. The flag flj of these blocks is set to "1" in order to indicate the evaluation value and indicate the completion of the evaluation. Of the blocks of the song whose evaluation has not been determined in the first evaluation loop (46-2 to 46-15), the youngest block becomes the reference block in the next evaluation loop (46-46).
3, 46-4, 46-6), and the hierarchical structure identifier of this reference block is 2. Hereinafter, the same processing is repeated. As a result, all blocks of the song have the hierarchical structure identifier Hj.

The processing in FIG. 43 is processing for converting the hierarchical structure in block units obtained in FIG. 42 into hierarchical structure data in measure units. That is, the hierarchical structure identifier for the a-th measure is set in HIEa in FIG.

Next, the extraction of the tonality structure will be described with reference to FIGS. 44 to 47. In order to extract the tonality structure from the chord progression, the present embodiment takes into account the properties of the tongue structure of general music. The characteristics are as follows: (a) The tonality tends to maintain the same tonality rather than changing frequently in the progress of the music.

(B) The constituent sounds of a chord are on a musical scale of a specific tonality.

(C) When transposition occurs, it is easier to turn to a close relative such as a genus key or a subordinate key than to an unrelated key.

It is.

In order to provide the tonality structure to be extracted with the above properties, in the present embodiment, a tonality distance is defined between the chords, and if the chord in the current section has a tonality of a predetermined distance from the tonality in the previous section. The tonality of the current section is considered to be the same as the tonality of the previous section.

FIG. 47 illustrates the tonality distance between the chords. As can be seen from this figure, codes having a parallel tone relationship (for example, Am
And C) are zero, and thus have the same tonality (C). In addition, the tonality distance with respect to a chord that is completely 5 degrees below or completely 5 degrees is 2 or −2. Now Key C Datonic Scale (Doremi Fasoraside)
, The six chords C, Am, G, Em, F, and Dm within the tonality distance of ± 2 from chord C all have their chord constituent sounds on the diatonic scale of key C. As will be described later, in the present embodiment, the tonality is maintained for a chord change within the tonality distance ± 2.

In FIG. 44, in the processing from 48-1 to 48-5, tonality distance data is assigned to each code in the chord progression according to the definition of tonality distance illustrated in FIG. That is, set to "0" as the tonality KEY ₁ for the first chord within 48-1 in 48-2～48-5, the first code tonality of CD ₁ tonality KEYi subsequent encoding CPi It is calculated by calculating the distance from KEY ₁ . 48-3
The tonality of this is shown in FIG.

CDi∧ooff in 50-1 is an extract of the root data of the i-th code CDi (see FIG. 4), the result is a ₁ and a ₂
Is assigned to On the other hand root data of the first code CD ₁ enters in st. As shown in 50-5, root data a ₁ 50-
Each time to go around the loop of 3～50-6 is turn on 5 degrees, root data a ₂ is to be turn under 5 degrees (about 47 counterclockwise the ring shown in FIG., Or clockwise Equivalent). In 50-3, a ₁ = st holds only when CDi
Is obtained when the root sound data i is turned up 5 degrees, and 50-
In a 4, a ₂ = st is satisfied because the root data of CDi is i
Is turned 5 times downward. Therefore, for the former, i × (−2) is inserted into x as the tonality distance (50−
7) For the latter, insert i × 2 into x. From 50-9
50-17 is, and code CDi of interest as the first code CD ₁ is, both or major system or minor system, by or not, is where you are converting the x. For example, CD ₁ is Am
If CDi is Gmaj, x = + 4 by 50-7 (for comparison between root sounds A and G). This must be x = -2 according to FIG. In this case, in FIG. 46, the process proceeds from 50-10 to 50-11 and 50-13, and x = -2 is obtained by x = x-6. Also CD ₁
Is Cmaj and CDi is Bmin, x = -10 by 50-8
It has become. This must be x = −4 according to the definition of the tonality distance in FIG. In this case, the 46th
In the figure, 50-14 advances to 50-15, 50-17, and x = x
By +6, x = -4 is obtained. Calculation result x in Fig. 46
Is transferred to KEYi.

An example of the processing of 48-1 to 48-5 is shown in (1) of FIG.
Chord progression _{C, C, F, G 7} , B, b, F, with respect to G _7, c, as tonality distance _{{KEY}, KEY 1 = 0} , KEY 2 = 0, KEY
₃ = +2, KEY ₄ = -2, KEY ₅ = +4, KEY ₆ = +2, KEY ₇
= -2, KEY ₈ = 0.

The tonality distance {KEY} obtained in this way is the following 48
In the processing from −6 to 48−14, conversion is performed so as to have the tonality property described above. In other words, the tonality data immediately before
When the tonality data of the current chord is located within ± 2 from the immediately preceding tonality data skey, the tonality data of the current code is converted to the immediately preceding tonality data to maintain the tonality. , Is regarded as modulation only when the distance exceeds ± 2, and the value obtained by ± 2 from the tonality data of the current code is used as final tonality data.

The processing side from 48-6 to 48-14 is shown in FIG. 45 (2).
Chord progression _{C, C, F, G 7} , Bb, F, as tonality for _{G 7, C {KEY},} 0,0,0,0,2,2,0,0 is obtained.

In this manner, a tonality structure having a desired property as a musical piece is extracted in the data format of the distance expression.

In FIG. 44, from 48-15 to 48-25, the tonality structure data of the distance expression is being converted into the pitch name expression representing the root of the scale. In this tone name expression, C is assigned a numerical value of “0”, C # is assigned a numerical value of “1”,. For example, assume that the first chord of a song is Cmaj, the i-th chord is Fmaj, and the tonality of this Fmaj is "2" in the distance expression. The corresponding pitch name expression is “5”. For this conversion, the process proceeds with 48-15 than 48-16,48-17, where _{a 1 = KEY 1 -KEYi × 7} /2 is performed, KEY ₁ = 0, KEYi =
Since at 2 a ₁ = -7 next, a ₁ = 5 next by the processing of 48-18,48-19, which is KEYi (48-20). If the first chord of the song is a major chord, KEY ₁ = 00
ff∧CD ₁ gives the root of the scale of the first chord section, but in the case of a minor system, according to the relationship of Am = C,
KEY ₁ = (00ff∧CD ₁ +3) mod12 is executed to obtain the root note of the scale of the first chord section (48-16, 48-21 to 48
-23).

FIG. 45 (3) shows an example of processing from 48-15 to 48-25.
When chord progression is _{C, C, F, G 7} , Bb, F, G 7, C, scale of the keys used in each code section (tonic)
Becomes C, C, C, C, F, F, C, C.

As will be described later, each tone of the melody generated in each chord section is selected from a scale using the tonality structure data extracted by the above processing as the main tone.

Next, the scale evaluation will be described with reference to FIG. The purpose of this processing is to use a special scale as a scale for melody generation for a section where a special code is used. In Figure 48, ISCA
LE is the scale selected in the initial setting 4-1 (FIG. 2). If the code CDi is the deminish code "dim", set the combination deminish scale as the scale SCACEi to be used in that section, and set the code CDi
When i is an augment code "aug", set the whole tone scale as the scale, and when code CDi is the seventh code "7th", dominant as the scale
7th scale is set. As the tones of these chord sections, the root note of the chord is used instead of the tonality data obtained in the tonality structure extraction processing. Therefore, in a section other than these exceptional chord sections, a scale of the type selected in the initial setting is used as a scale, and its tonic is determined by tonality data obtained by the above-described tonality structure extraction processing.

<Melody Generation> The apparatus according to the present embodiment is provided with data serving as a basis for music composition from the outside, analyzes and evaluates the basic data internally, and then proceeds to a melody generation operation.

FIG. 49 shows a schematic flow of the melody generation shown in 4-8 of the composition general flow (FIG. 2). In FIG. 49, HIEi is hierarchical structure data for each code section extracted in the preceding chord progress evaluation, and as shown in 53-2 to 53-4, this hierarchical structure data HIEi is an arpeggio pattern (L
L) is used for generation control. Details of this control will be described later. Further, the hierarchical structure data can be used to control the range of the arpeggio pattern (LL) as shown in 53-5 and 53-6.

The arpeggio pattern forms the basic skeleton of the melody sequence, and the range of the arpeggio pattern basically regulates the range of the melody. In this embodiment, a hierarchical structure obtained from the chord progression is used for the control, which is also one of the features of the embodiment. However, it is not necessary to limit the control factors of the arpeggio pattern only to the information of the hierarchical structure extracted from the chord progression. For example, weighting is applied to each of the hierarchical structure and random numbers, and the arpeggio pattern is controlled by the weighted sum of both data. And the weight may be specified by the user. In short, it can be modified so that the user's intention in composition is reflected in the generation of the arpeggio.

The arpeggio pattern (LL) is converted to a pitch expression format, that is, a melody data format (arpeggio) by using the chord data CDi (53-7). Then, a non-harmonic tone is added to this arpeggio in accordance with the production rules (53-8). The production rules used for adding the non-harmonic sounds are the same as those used for classifying the non-harmonic sounds included in the motif, and therefore, the reversibility is established with respect to the analysis and synthesis of the melody.

By adding a non-harmonic tone to the arpeggio, the pitch sequence of the melody is completed. After completing the melody pitch line,
This is the generation of a melody pitch sequence (rhythm pattern) (53
-9). Here, a basic rhythm pattern (Essence generation 4-4 or Essence extraction 4
The pitch sequence determined in -6) is transformed by the pulse scale selected in the initial setting 4-1 and converted into a pitch sequence having the same number of notes as the pitch sequence of the melody.

The generation of the arpeggio, the addition of the non-harmonic sound, and the generation of the duration data are executed for each chord section in the flow of FIG. Therefore, in 53-10, the melody data generated in a certain section is moved to the continuous area.

FIG. 50 is a detailed flowchart of generation, saving, and loading of an arpeggio pattern (sound pattern) (53 in FIG. 49).
-2, 53-3, 53-4). In this example, the arpeggio pattern LL is controlled by the hierarchical structure data HIEi as follows. First, it is determined whether or not the focused phrase is a section structurally different from the past phrase by comparing the hierarchically structured data of the focused phrase with the past hierarchically structured data. A new arpeggio pattern LL is generated only for a passage recognized as a section having a different structure. This generation is performed based on the feature parameter PC of the arpeggio pattern described above. A new arpeggio pattern will be added to passages recognized as having the same structure.
LL is not generated. Instead, of the arpeggio patterns generated in the past, an arpeggio pattern generated in a section having the same structure as the section of interest is used.

For example, suppose a tune composed of four passages, and assume that the structures of these four passages are a, b, c, and a, respectively. Since the structure a of the first phrase is a structure not seen in the past, an arpeggio pattern is generated according to the feature parameters of the arpeggio pattern. Similarly, since the second and third passages also have new structures b and c which have not existed in the past, arpeggio patterns are independently generated. However, the final passage has the same structure a as the first passage of the song. Therefore, the arpeggio pattern generated for the first phrase is used as it is as the arpeggio pattern for the final phrase.

Generating a new arpeggio pattern for a phrase having a new structure means that another motif is generated from the phrase having the new structure. If the arpeggio pattern generated for the first measure of a passage is repeatedly used for subsequent measures of the passage, a motif having a length of one measure will be recognized. Generally, the length of a motif is one to several measures, and the length of the motif often changes in the middle of a song. In consideration of this, in the example of FIG. 50, when a phrase having a new structure is detected, one or two measures can be used as the length of the motif in the phrase. When a two-bar motif is selected, an arpeggio pattern is generated independently for the first bar and the second bar of the passage, and the odd-numbered bars that follow use the arpeggio pattern of the first bar and the even bars that follow. The second measure uses the arpeggio pattern of the second measure.

A sound (LL) data buffer is prepared for referencing the hierarchical structure data in the past section and repeating the arpeggio pattern in the past section. FIG. 51 shows an example of the sound data buffer.

Referring to FIG. 50, a bar counter in a passage (a section for each barno shown in FIG. 41) is set to "1" at 54-1. In 54-2, the hierarchical structure data HIEi of the current measure is compared with the hierarchical structure data HIEi-1 of the immediately preceding measure, whereby
Check whether the passage has started. For example, | HIEi-HIE
When i−1 | ≧ 2 holds, the passage is started. If it is determined that the passage has started, the bar counter in the passage is reset to "1" (54-3). Subsequently, the sound type data buffer is searched to determine whether the current phrase is a phrase for which an arpeggio pattern should be newly generated (54-4). The search of the sound data buffer is performed as follows. First, data at address 0 of the sound pattern data buffer (data indicating how many sets of sound patterns have already been generated) is read, and data indicated by subsequent addresses 1 to N as addresses (each data). The header information of the sound pattern is sequentially read, and the hierarchical structure data indicated by the upper 8 bits is compared with the hierarchical structure data HIEi of the current bar. When there is no hierarchical structure data (for example, data having the same value as HIEi or a value of (HIEi-1)) similar to the hierarchical structure data HIEi of the current bar in the sound type data buffer, the current bar newly sets an arpeggio pattern. This is the first measure of the passage to be generated. When a header having the same hierarchical structure data is found, the following arpeggio pattern is loaded as the arpeggio pattern of the current bar. In the case of a new passage, first determine how many measures the motif is composed of (54-5). This determination can be realized by random number generation, for example. When a two-bar motif is reached, the flag fl is set to "1" (54-7, 54-
8) An arpeggio pattern is newly generated for the next bar (the second bar of the passage). Then, an arpeggio pattern is generated (see FIG. 52) and saved in the sound pattern data buffer (54-9). See HI
A header is created by Ei × 0100 + measure counter value × 0010 + the number of measures of the motif, the number N of the sound group at address 0 of the sound data buffer is incremented, the address of the header is written to the address N, and from that address. writes header, LLNO (length of the generated arpeggio _{pattern), LL 1, LL 2 ......} LL LLNO (data of the generated arpeggio pattern). Thereafter, other melody generation processing is performed (54-10), and the bar counter is incremented (54-11).

If it is found in step 54-2 that the phrase has not changed, the flag fl is checked (54-13). When fl = 1, the current measure is 2 in the phrase that generates a 2-bar motif.
Since this is the second measure, an arpeggio pattern is generated again, loaded into the sound data buffer (54-15), and the flag fl is reset to "0" (54-16). When fl = 0, the header corresponding to the hierarchical data HIEi of the current bar is searched from the buffer, and when the length information of the motif indicated by the header is one bar, the sound pattern data following the header is searched. When the motif is two measures long, the remainder of the measure counter is compared with the measure number of the header, and if they match, the tone data following the header is loaded as the arpeggio pattern of the current measure.

Details of the generation of the arpeggio pattern (sound pattern) executed in 54-9 and 54-15 in FIG. 50 are shown in FIG. 56-1 ck
"no" indicates the number of chord components. The number of chord constituent sounds is obtained by counting the number of "1" in the 16 bits of chord constituent sound data (see FIG. 26). In the example of 52 view, and the control parameters of the arpeggio pattern that generates a PC ₁ to PC _5. r1 takes a random value in the range of ₁ to ckno, and means a chord component sound number (56-4). r ₂ is PC ₃
Take the random value of the octave code of (lowest note of the arpeggio pattern) ~ PC ₂ (highest note of the arpeggio pattern)
Indicates the octave number of the LL to be generated (56-5). a =
LL candidates generated by r ₁ + r ₂ × 0100 are calculated (56−
7) When this candidate a satisfies the condition of PC, the candidate a
Is adopted as LL (56-8, 56-12, 56-14). However, depending on the value of PC, the preceding LL (for example,
After LL ₁ ) has been determined, subsequent LL ₂ candidates may not permanently satisfy the PC requirements. For example, PC ₂ = 501 (the highest note of the arpeggio is the first chord component of the fifth octave), PC ₃ = 401 (the lowest note of the arpeggio is the first chord component of the fourth octave), and PC ₄ = 3 (the neighbor When PC ₅ = 3 (the minimum difference between adjacent LLs is three chord constituent sounds), LL ₁ is assumed as LL ₁ and LL ₁ = 403 (first). 's LL to match the fourth when the first chord member octave) is to obtain PC _4, PC ₅ conditions, when LL ₂ = 503 or 303 (constituting note number 3), which is PC ₂ Does not meet the requirements of PC ₃ . To prevent this, prepare a loop counter LOOPC and set the loop counter L
When OOPC exceeds a certain value (for example, 100), candidate a is forcibly adopted as LL (56-9, 56-10, 56-1).
1).

FIG. 53 shows the details of the check 56-8 in FIG. 52. LLi
In order for the candidate a to satisfy the condition of PC, (a) a ≦ PC ₂ (must be lower than the highest note) (b) a ≧ PC ₃ (must be higher than the lowest note) (c) | a−LLi −1 | ≧ PC ₄ (The difference from the previous LL is the maximum value PC ₄
(D) | a−LLi−1 | ≦ PC ₅ (the difference from the immediately preceding LL is the minimum value PC ₅
Must be satisfied). In the flow of FIG. 53, when these conditions are not satisfied, the flag OK is set to “0” (olda in the figure represents the immediately preceding LL; see 56-13).

FIG. 54 is a detail of 53-7 in FIG. The purpose is to convert the format of the arpeggio pattern LL indicated by (octave number + chord component number) to the format of melody pitch data indicated by (octave number + note name number) using the chord component sound data cc. And store it in MEDi.
The processing of 58-5 and 58-6 is performed by the chord number of LLi (LLi
When {00ff) is greater than the number of chord constituent tones (CKNO) of the chord in the current section, the LLi chord constituent note number is changed to the highest chord constituent note number in the chord constituent sounds in the current section. . In the figure, c is a counter of chord constituent sounds, LL
i∧ff00 is the octave number of LLi, and j is a note name counter.

FIGS. 55 and 56 show the details of the non-harmonic sound addition in 53-8 in FIG. 49. The purpose of this processing is to add a desired non-harmonic sound to the arpeggio to complete the pitch sequence of the melody. For the addition of non-harmonic tones, the above-mentioned non-harmonic features {RSi}, tonal structure obtained from chord progression evaluation ｛KEY
i｝, a production rule expressing knowledge for classifying non-harmonic sounds is used. The added non-harmonic tone must satisfy the following conditions.

(B) The sound must be within a predetermined range. (B) The sound must be on a scale with the KEYi obtained in the chord progression evaluation as the main tone. (C) It must be a sound outside the chord structure. In FIG. 55, the loop outside 59-4 to 59-18 is a loop that repeats for the number of planned non-harmonic identifiers RSi. The loop from -5 to 59-16 repeats the number of notes in the arpeggio. In 59-8 to 59-14, each pitch data k in the range from the lower limit lo to the upper limit up is sequentially examined as non-harmonic candidates (see FIG. 57). When the pitch data k is a scale tone and a non-chord-structured sound, (59-8,
59-9), calculate the function F (59-10), perform forward inference based on the production rules (59-11), and check whether the conclusion matches the planned non-harmonic identifier RSi. (59-11). When they match, the pitch data k satisfies all of the above-mentioned conditions for non-harmonic sounds. Therefore, the non-chord tone counter nctct for counting the number of non-harmonics to be added is incremented, the pitch data k of the found non-harmonics is put in VMnctct, and the addition position j of the non-harmonics is set in POSTnctct. , The associated flag flj is set to "1" (59-19 to 59-22). In this example, at most one non-harmonic sound is added between the harmonic sounds, and flj = 0 indicates that no non-harmonic sound has been added between the harmonic sounds MEDj and MED _{j + 1.} Show.

Conclusion at 59-12 = When the condition of RSi is not satisfied,
Since the pitch data k of interest does not satisfy the condition as a non-harmonic tone, the pitch data k is incremented (59
-13), repeat the process. When k> UP is satisfied in 59-14, it means that a non-harmonic tone has not been added between the harmonics MEDj and MED _{j + 1} . Therefore, j is incremented (59-15), and the process proceeds to a check as to whether a non-harmonic sound can be added between the next harmonic sounds.

Details of the setting of candidate sounds in 59-6 are shown in FIG. In this example, the pitch is searched from 5 semitones above the higher tone of the preceding and following harmony notes MEDi and MED _{i + 1} to 5 semitones below the lower tone (62-5 to 62-7). ). However, when i = 0, that is, when an attempt is made to add a non-harmonic sound before the first harmonic sound in the section of interest, the pitch range from 5 semitones to 5 semitones below the first harmonic sound is set. (62-1, 2), when i = Vmedno, that is, when an attempt is made to add a non-harmonic tone after the last harmonic tone in the section of interest, a fifth semitone to a fifth semitone below the last harmonic tone Up to the pitch range (62-3, 4).

The details of checking whether or not the pitch data k in 59-8 is a scale tone are shown in FIG. SCALEi in the figure represents the type of the scale used in the section i, and is an address pointer of the scale data memory 5 as shown in FIG. The 12-bit scale data * SCALEi at this address is rotated by the KEYi obtained in the chord progression evaluation described above (65-
2). For example, when SCALEi is “0” (diatonic scale), the data represents Doremifasoraside having C as a main tone. When KEYi is “5” (F), the data
By turning it, it is converted into scale data a having F as the main tone. 65-3 is a process of converting the pitch data k (indicated by MD in the figure) into the same data format as the scale data, and as a result, the logical product of the b and the scale data a is "0"
Then, it is concluded that the pitch data k is not a scale note, and when the logical product is not "0", it is concluded that the pitch data k is a scale note (64-5-64-).
7).

Details of the calculation of F in 59-10 are shown in FIG. In this example, since only one non-harmonic sound is added between the preceding and succeeding harmonic sounds, some functions (F _{1 to} F _{3 in the} figure) are set to predetermined values.

Details of the forward inference of 59-11 are shown in FIG. 40 described above.

When the processing in FIG. 55 is completed, the total number of added non-harmonic sounds is stored in nctct, and the i-th in the array {Vi} is
The pitch data of the i-th non-harmonic tone added in the processing of FIG. 55 is stored, and the 55th is stored in the i-th of the array {POSTi}.
The position information of the i-th non-harmonic sound added in the processing of the figure is stored.

These data are converted into the melody pitch sequence {VMEDi} by the processing of FIG. 56. Array ｛VME
Di｝ is initially set to arpeggio {MEDi}. 60
-2 to 60-9 are arrays {POSTi}, {V
Mi｝ This is the process of sorting. In 60-10 to 60-19,
Non-harmonic pitch data VMi is inserted at the position indicated by the position data POSTi.

In this example, only one non-harmonic sound can be added between the harmonious sounds, but the processing may be changed so that a plurality of non-harmonic sounds can be added.

At this point, the pitch sequence of the melody is completed. The remaining processing is generation of a melody duration sequence.

FIG. 62 shows a flow of generating a melody pitch sequence (53
-9 details). First, the number of notes of the reference rhythm pattern obtained by generation or extraction of the essence is compared with the number of notes Vmedno (the number of data in the pitch sequence of the melody) generated in the section of interest, and the difference a between them is calculated. (66-1). When the number of generated notes is smaller than the number of notes in the reference rhythm pattern (when a> 0), the optimal combination of notes by the pulse scale is repeatedly executed by the number of differences (66-2 to 66-).
6). When the number of generated notes is larger than the number of notes in the reference rhythm pattern (when a> 0), the optimum division of the notes is repeatedly executed by the difference (66-7 to 66-11). In this example, 16-bit data is used as the rhythm pattern data format, and each bit position is assigned to each timing.
Since it indicates that sound is generated at the bit position having the value of “1”, it is finally converted to the MER data format (66-1
2).

Details of the combining process are shown in FIG. In the figure, PSCALEj represents the j-th component scale of the pulse scale to be used, and RR is a rhythm pattern to be processed. Notes are combined by setting the point with the smallest pulse scale weight to "0" in the bit of RR "1". For example, if the reference rhythm pattern is And if one note is combined using the normal no pulse scale (see FIG. 1), the result is Becomes

 This is obtained as follows.

First, RR is initially 0001 0001 0101 0001. On the other hand, the normal pulse scale is 1213 1214 1213 1215. The point where the normal pulse scale has the minimum weight among the bits “1” of the RR is the seventh position from the right end. The bit at this position becomes “0”. Therefore, the resulting RR is 0001 0001 0001 0001, which is Is represented.

Details of the dividing process are shown in FIG. The division is performed by setting the point at which the weight of the pulse scale is maximum to "1" among the bits of RR "0". For example, rhythm pattern On the other hand, when dividing notes with the normal pulse scale, the result is Becomes

Details of conversion 66-12 to MER data format are shown in FIG. In the figure, c ₁ is the counter of a note, c ₂ is a counter that measures the sound length of each note. In this example, MERo has a length until the first "1" appears from the RR, so it is possible to process notes that cross the section boundary (bar line) (measures against syncopation).

FIG. 66 shows the details of the data movement 53-10. First, MERo
(The blank portion at the beginning of the current generation section) is added to the duration data MELRmeldno of the last generated note. Here, meldno represents the number of notes already generated. The pitch sequences VMED _{1 to} VMEDvmedno generated this time are moved to MELD, and the pitch sequences MER ₁ to MERvmedno generated this time are moved to MELR (70-2 to 70-
6). Update meldno and finish (70-7).

<Summary of Composer> As is clear from the above description, this device as an automatic composer has various features, some of which are described below.

(A) A production system for performing inference using music knowledge in melody analysis and synthesis is incorporated.

(B) a process of classifying non-harmonic sounds included in the melody;
Since the process of adding the non-harmonic sound to the arpeggio is performed based on the production rule data expressing the same musical knowledge, both processes are reversible.

(C) A song is planned by analyzing the chord progression given as a composition material and extracting the hierarchical structure and tonality structure of the song.

(D) The extracted tonality structure defines the scale key used in each section. As a result, a song with a natural sound rich in tonality is guaranteed.

(E) The extracted hierarchical structure is used for arpeggio generation control. As a result, diversity and consistency can be incorporated into the generated music.

The above-described embodiments are merely examples, and various modifications, changes, and improvements are possible. For example, in the embodiment described above, the feature PC of the arpeggio pattern extracted from the motif
Is used as control data in generating the arpeggio pattern LL, but the feature PC of the arpeggio pattern may be changed as the music progresses. This can be realized, for example, by means of calculating a function using the progress position of the music or the hierarchical structure as a variable.

Similarly, the non-harmonic feature {RSi} can be changed as the music progresses. For example, one non-harmonic identifier among the non-harmonic features extracted from the motif is replaced with another non-harmonic identifier. This can be realized by randomly selecting one from a set of non-harmonic tone identifiers.

In the above embodiment, the rhythm is controlled by combining and dividing notes using a pulse scale. However, a dominant mini rhythm pattern including a motif is extracted, and the pitch of a melody generating the rhythm is generated. You may make it incorporate in a row.

[Effects of the Invention] As is apparent from the above description, the automatic composer according to the present invention (the first to fourth aspects) changes the characteristic parameters of the melody generated by the melody synthesizing means as the music progresses. For this purpose, the music format (hierarchical structure representing the structural relationship between music sections) is extracted from the given chord progression,
The feature parameters of the melody are controlled using the format of the extracted music. Therefore, the chord progression information is fully utilized, and a melody that is well suited to changes in chord progression can be generated. Further, it is not necessary for the user to give detailed instructions based on musical knowledge in order to make the automatic composer compose music. Further, according to the present invention (Section 5), the characteristics of the input melody can be reflected in the generated melody, and the flow can be controlled according to the format of the music extracted from the chord progression.

[Brief description of the drawings]

FIG. 1 is an overall configuration diagram of an automatic composer according to one embodiment of the present invention, FIG. 2 is a flowchart showing overall operation in a composer mode, and FIG. 3 is a list of main variables used in the processing. , FIG. 4, FIG. 5, FIG. 6, FIG.
FIG. 8, FIG. 8 shows a format of data used, FIG. 9 is a flowchart of initialization, FIG. 10 shows an example of chord progress data stored in a chord progress memory, and FIG. Flowchart of reading progress data, twelfth
FIG. 13 is a diagram exemplifying pulse scale data stored in a pulse scale memory, FIG. 13 is a flowchart of reading pulse scale data, FIG. 14 is a diagram exemplifying production rule data stored in a production rule data memory, FIG. 15 is a flowchart for reading production rule data, FIG. 16 is a diagram illustrating melody data (motif data) stored in the motif memory, FIG. 17 is a flowchart for reading melody data, and FIG. 18 is a flowchart for generating essence. flowchart,
19 is a flowchart for setting the characteristics of the arpeggio pattern, FIG. 20 is a flowchart for setting the characteristics of the non-harmonic sound, FIG. 21 is a flowchart for evaluating the rhythm of the motif for each section, and FIG. 22 is Ps, Pe, Pss , Pee calculation flowchart, FIG. 23 is a flowchart for calculating Ps and Pss, FIG. 24 is a flowchart for calculating Pe and Pee, FIG. 25 is a flowchart for extracting an arpeggio pattern of a motif, and FIG. 26 is each code A diagram showing an example of the constituent sound data of
FIG. 27 is a flowchart for generating constituent sound data from chord data, FIG. 28 is a flowchart for extracting arpeggio pattern features, FIG. 29 is a flowchart for extracting non-harmonic features, and FIG. 30 is based on chords Flow chart for classifying melody sounds into harmonies and non-harmonys,
31 Figure is a flowchart for calculating the function F representing the status of the analyte melody, the flow chart of FIG. 32 calculates functions F _1, FIG. 33 is a flowchart of the calculation of the function F _2, 34
Figure is a flow chart of the calculation of the function F _3, the flow chart of FIG. 35 calculates the function F _4, Figure 36 is a flow chart for calculating the function F _5, Figure 37 is a flow chart for calculating the function F _6, the
38 is a flowchart for calculating the functions F ₇ and F ₈ , FIG. 39 is a flowchart for temporarily storing the calculated function F, FIG. 40 is a flowchart for inferring the type of non-harmonic sound, and FIG. 41 is a code between blocks. 42 is a flowchart for calculating the degree of coincidence of progress, FIG. 42 is a flowchart for generating hierarchical structure data from the calculated degree of coincidence, FIG. 43 is a flowchart for converting hierarchical structure data of a block into hierarchical structure data for each code section, 44 Figure is a flow chart for extracting a chord progression color tonality structure, FIG. FIG. 45 is an example of the extraction process of tonality structure, FIG. 46 is first code CD ₁ and the i-th code CDi
47 is a flowchart showing the definition of a tonal distance between chords, FIG. 48 is a flowchart showing processing of a scale (scale), FIG. 49 is a flowchart of melody generation, and FIG. Figure 50 is a flowchart showing the generation, saving, and loading of sound patterns (arpeggios).
51 is a diagram illustrating a sound type data buffer, FIG. 52 is a flowchart of arpeggio pattern generation, FIG. 53 is a flowchart of a check in arpeggio pattern generation, FIG. 54 is a flowchart of converting an arpeggio pattern into a melody data format, 55 and 56 are flowcharts for adding a non-harmonic tone to an arpeggio, FIG. 57 is a diagram showing the order of non-harmonic tone addition processing, and FIG. 58 is a diagram showing a range of pitches to be candidates for non-harmonic tone FIG. 59 is a flowchart of the calculation of the function F, FIG. 60 is a diagram showing an example of scale data stored in the scale data memory, FIG. 61 is a flowchart of the identification of scale notes, and FIG. FIG. 63 is a flowchart for optimally combining notes, FIG. 64 is a flowchart for optimally dividing notes, and FIG. 65 is a flowchart for generating note length data. ME rhythm pattern
FIG. 66 is a flow chart for converting the generated melody data to a continuous area. 1 ... CPU, 2 ... input device, 3 ... motif memory,
4 chord progression memory, Vij chord progression coincidence data, HIEi hierarchical structure data, LLi arpeggio pattern.

Claims (5)

(57) [Claims] 1. A chord progression providing means for giving a chord progression of a music, a feature parameter generating means for generating a plurality of feature parameters characterizing a melody to be synthesized, and a predetermined parameter based on the chord progression and the feature parameter Melody synthesizing means for synthesizing a melody composed of a mixture of harmony and non-harmonic sounds as a function of, wherein the feature parameter generating means divides the chord progression into a plurality of sections, and By calculating the degree of coincidence of chord progression in
Music format extraction means for extracting a music format; and a music format from the music format extraction means as a control input, and the characteristic parameter according to the music format such that the music format is reflected in a melody to be synthesized. And a feature parameter control means for controlling at least a part of the automatic music machine. 2. The automatic music composer according to claim 1, wherein said music format extracting means evaluates a coincidence of the chord progression between musical passages, and said coincidence evaluation. And a structure identifier assigning means for assigning a structure identifier to each passage according to the degree of coincidence evaluated by the means. 3. The automatic composer according to claim 1, wherein said characteristic parameter control means includes, as at least a part of said characteristic parameters, a pattern of a dispersed chord included in a melody synthesized by said melody synthesis means. An automatic composer comprising means for controlling the automatic music machine. 4. The automatic composer according to claim 1, wherein said characteristic parameter control means controls, as at least a part of said characteristic parameters, a range of a melody generated by said melody synthesizing means. An automatic composer characterized by including. 5. A chord progression providing means for providing a chord progression of a music, a feature parameter generating means for generating a plurality of feature parameters characterizing a melody to be synthesized, and a predetermined parameter based on the chord progression and the feature parameter. Melody synthesizing means for synthesizing a melody composed of a mixture of harmony and non-harmonic sounds as a function of melody, wherein the feature parameter generating means analyzes the melody input with melody input means for inputting the melody. Feature parameter extraction means for extracting a plurality of feature parameters by dividing the chord progression into a plurality of sections, and determining a degree of coincidence of chord progressions between the divided sections.
A music format extraction unit for extracting a music format; and a music format from the music format extraction unit as a control input, and the extraction feature according to the music format such that the music format is reflected in a melody to be synthesized. An automatic composer, comprising: feature parameter changing means for changing at least a part of a parameter.