JP2008299005A - Resonance adding apparatus and resonance adding program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To generate resonance having the reproducibility simillar to measured impulse response data by small amount of calculation, and reduce a data amount of the impulse response data. <P>SOLUTION: A resonance adding apparatus comprises: an input data buffer 22 in which a sequence of musical sound signal data on a time axis is stored as a delay memory value; a storage section 16 for storing the impulse response data 14, indicating an impulse response characteristic on the time axis; a resonance generating section 20 for generating a resonance data by convoluting a value of the impulse response data 14 and the delay memory value; and an impulse response generating section 18 in which an original impulse data 12 stored in the storage section 16 is taken out, and a maximum value and a minimum value which are larger or smaller than the former and latter values by a predetermined amount, are found, and in which the maximum value and the minimum value are stored as the value of the impulse response in the storage section 16, while for the value other than the maximum value and the minimum value, the value for indicating "0" as the value of the impulse response data is stored in the storage section 16. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a resonance addition apparatus and a resonance addition program for adding a resonance to a musical sound.

  Various devices for adding resonance to musical tone signals from electronic musical instruments and audio equipment are known. Here, the resonance sound includes a reverberation sound in a place where a musical sound is generated such as a hall, a resonance sound of the musical instrument itself, and the like.

In order to generate a resonance sound, the resonance sound adding device generally accepts a digital musical tone signal and performs a filtering process using a digital filter on the musical tone signal data. In the filter processing, FIR (Finite Impulse Response) filter or IIR (Infinite Impulse Response: Infinite Impulse)
Response) filter is used.

  When the FIR filter is used, the input tone signal data x (nk) and the impulse response h (k) obtained from the reverberation characteristics of the music hall are subjected to a convolution operation, so that the resonance sound yout = Σx Data of (n−k) × h (k) can be obtained. However, in the FIR filter, the ideal filter characteristic can be brought closer to the higher the number of impulse response data, that is, the order of the filter. On the other hand, there is a problem that the amount of calculation increases as the order of the filter increases.

There has been proposed a method capable of calculating a high-order impulse response by calculating an impulse response using FFT (Fast Fourier Transform). In Patent Document 1, a signal represented by a sample value sequence {x (n)} is input to a system having a characteristic in which a finite-length impulse response characteristic is represented by a sample value sequence {h (n)}. In this method, the sample value sequence {x (n)} is divided into small sections under a predetermined condition in a method of calculating the output {y (n)} using the convolution operation using the FFT hardware. The sample value sequence {h (n)} is also divided into small sections under a predetermined condition, and each small section is divided by the superposition addition method or the superposition hold method.
Japanese Patent Laying-Open No. 2005-215058 Japanese Patent Laid-Open No. 6-259087

  Various techniques have also been proposed that use an IIR filter to reduce the amount of computation (for example, Patent Document 2). In Patent Document 2, an all-band filter for scattering an input signal in the time axis direction is provided in a loop circuit of a comb filter, and a cutoff frequency of a low-pass filter in the comb filter is set as a loop circuit. It is determined based on the delay time of the internal delay circuit, and the output level of the resonance sound / reverberation sound is detected, and the level of the resonance sound / reverberation sound is controlled based on the output level. In Patent Document 2, the level control of resonance and reverberation is performed by controlling the level of a loop signal circulating in the loop circuit of the comb filter.

  However, when FFT is used, it is necessary to calculate an impulse response for each input in a predetermined range, so that there is a problem that processing in real time is basically difficult.

  Further, when the IIR filter is used, the calculation amount can be reduced, but there is a problem that it is difficult to reproduce the characteristic of the measured impulse response.

  The present invention can generate a resonance sound having the same reproducibility as the measured impulse response data with a small calculation amount, and can reduce the data amount of the impulse response data used for the filter calculation. An object of the present invention is to provide a resonance sound adding apparatus and a resonance sound adding program.

An object of the present invention is to provide an input data buffer that stores a series of musical tone signal data on a time axis as a delay memory value;
A storage unit storing impulse response data which is a value on the time axis representing the impulse response characteristics;
Resonance sound adding means comprising: a resonance sound generating means for generating a resonance sound data by convolving a value of the impulse response data and a delay memory value stored in an input data buffer,
The storage unit stores original impulse response data,
The original impulse data stored in the storage unit is taken out, and a local maximum value and a local minimum value that vary by a predetermined amount from the previous and subsequent values are found. Impulse response generation means for storing in the storage unit a value indicating “0” as a value of the impulse response data other than the found local maximum value and local minimum value as a value. This is achieved by a resonance sound adding device characterized in that it is provided.

  In a preferred embodiment, the resonance generating unit multiplies the value of the impulse response data by the value of the delay memory only when the value of the impulse response data is other than “0”. Configured to accumulate the values.

  In another preferred embodiment, the impulse response generating means has a linearly decreasing value along the time axis corresponding to the position of the impulse response characteristic on the time axis of the original impulse response data. The threshold value is calculated so that the maximum value and the minimum value having a larger fluctuation than the threshold value are found from the previous and next values.

  In still another preferred embodiment, the impulse response generating means is on an exponential curve that monotonously decreases along the time axis corresponding to a position on the time axis of the impulse response characteristic of the original impulse response data. The threshold value is set to be a value, and the local maximum value and the local minimum value having a larger fluctuation than the threshold value are found from the previous and subsequent values.

Another object of the present invention is to provide an input data buffer that stores a series of musical tone signal data on the time axis as a delay memory value, and a storage unit that stores impulse response data that is a value on the time axis that represents impulse response characteristics. A computer comprising:
A resonance addition program for executing a resonance generation step for generating resonance data by convolving a value of the impulse response data and a delay memory value stored in an input data buffer,
The storage unit stores original impulse response data,
In the computer,
The original impulse data stored in the storage unit is taken out, and a maximum value and a minimum value having a predetermined fluctuation larger than the previous and subsequent values are found, and the found maximum value and minimum value are found in the impulse response data. An impulse response generating step of storing in the storage unit as a value and storing a value indicating “0” in the storage unit as a value of the impulse response data other than the found local maximum value and local minimum value This is achieved by a resonance addition program characterized by being executed.

In a preferred embodiment, in the resonance sound generation step,
Only when the value of the impulse response data is other than “0”, the step of multiplying the value of the impulse response data by the delay memory value and accumulating the multiplied values is executed.

In another preferred embodiment, in the impulse response generating step, the computer includes:
Calculating a threshold value corresponding to a position on the time axis of the impulse response characteristic of the original impulse response data so as to be a value on a straight line that decreases monotonously along the time axis;
A step of finding a maximum value and a minimum value having a fluctuation larger than the threshold value from previous and next values.

In still another preferred embodiment, in the impulse response generation step, the computer includes:
Calculating a threshold value corresponding to a position on the time axis of the impulse response characteristic of the original impulse response data so as to be a value on an exponential curve that monotonously decreases along the time axis;
A step of finding a local maximum value and a local minimum value that vary more than the threshold value from the previous and subsequent values.

  According to the present invention, it is possible to generate a resonance sound having the same reproducibility as the measured impulse response data with a small calculation amount, and to reduce the data amount of the impulse response data used for the filter calculation. It is possible to provide a possible resonance addition device and a resonance addition program.

  Embodiments of the present invention will be described below with reference to the accompanying drawings. FIG. 1 is a block diagram showing a configuration of a resonance adding apparatus according to an embodiment of the present invention.

  As shown in FIG. 1, the resonant sound adding apparatus according to the present embodiment includes a storage unit 16 that stores original impulse response data 12 and new impulse response data 14 that is calculated by a calculation that will be described later, and an original impulse. A musical tone signal is generated from an impulse response generation unit 18 that generates new impulse response data 14 from the response data 12 and stores the new impulse response data 14 in the storage unit 16, and an input data buffer 22 that stores a series of musical tone signal data. Receiving data, and convolution of musical tone signal data and new impulse response data to generate resonant tone data, and a series of musical tone signal data are received and these data are temporarily stored. An input data buffer 22 and resonance sound data for temporarily storing the output resonance sound data It includes a buffer 24, a.

  FIG. 2 is a block diagram showing a hardware configuration of the resonance adding apparatus according to the present embodiment. As shown in FIG. 2, the hardware of the resonance sound adding device includes a CPU 30, a ROM 32, a RAM 34, an input device 36, a display device 38, and a sound system 40. The CPU 30, ROM 32, RAM 34, input device 36, display device 38 and sound system 40 are connected by a bus 42.

  As can be understood from FIG. 2, the resonance sound adding device can be realized by an ordinary personal computer. The CPU 30 executes processing such as system control, generation of new impulse response data 14, and generation of image data to be displayed on the screen of the display device. The ROM 32 stores programs, constants used when the programs are executed, and the like. The RAM 34 temporarily stores variables, parameters, input data, output data, and the like necessary in the course of program execution.

  The input device 36 includes, for example, a keyboard and a mouse so that an operator can input a desired instruction. On the screen of the display device 38, instructions input by the operator and processing results can be displayed.

  The sound system 40 includes a tone generation circuit 44, a resonance tone generation unit 20, an amplifier (not shown), a speaker (not shown), etc., and generates predetermined tone signal data in accordance with instructions from the CPU 30, In addition, resonance sound data in which resonance sound is added to the musical sound signal data is generated, and an acoustic signal based on the generated resonance sound data is output.

  The tone generation circuit 44 reads out the tone waveform from the ROM 32 and generates tone signal data of a designated pitch. The musical tone signal data is temporarily stored in the input data buffer 22 as shown in FIG. The resonance generating unit 20 is an FIR filter, which reads out musical tone signal data as input data from the input data buffer 22 and performs a convolution operation on the musical tone signal data and new impulse response data read out from the storage unit 14. The resonance sound data is generated and stored in the resonance sound data buffer 24.

  The function of the impulse response generator 18 shown in FIG. 1 is realized by the CPU 30. In FIG. 2, the resonance generator 20 is illustrated as an element in the sound system 40, but the resonance generator 20 is not limited to being realized by hardware such as a digital filter circuit, The function of the resonance generator 20 can be realized by the CPU 30.

  Moreover, the memory | storage part 16, the input data buffer 22, and the resonance sound data buffer 24 of FIG. 1 are implement | achieved by RAM34, for example.

  In the resonance sound adding apparatus according to the present embodiment, for example, a program stored in the ROM 32 causes the computer to function as the impulse response generation unit 18. Further, the program stored in the ROM 32 can cause the computer to function as the resonance generator 20.

  The original impulse response data 12 is data obtained by measuring the reverberation characteristics of a music hall and the like and based on the measured reverberation characteristics. In the present embodiment, the original impulse response data 12 is stored in the storage unit 16 of the resonant sound adding device, and new impulse response data 14 is generated based on the original impulse response data 12 by the impulse response generation unit 18. The new impulse response data 14 is stored in the storage unit 16. Once the new impulse response data 14 is generated, only the new impulse response data 14 is used for the resonance sound generation thereafter, and the original impulse response data 12 is not used. Accordingly, the original impulse response data 12 only needs to be stored in the storage unit 16 only when new impulse response data 14 is generated.

  Therefore, the resonant sound adding apparatus according to the present embodiment executes an impulse response data generation process for generating new impulse response data as a pre-process for the resonant sound generation process for generating the resonant sound data.

  FIG. 3 is a flowchart showing an example of impulse response data generation processing according to the present embodiment. The storage unit 16 stores original impulse response data Iro [n] (n = 0 to nTap−1) according to the order of the filter. In the present embodiment, in the original impulse response data, a local maximum value and a local minimum value that have a predetermined variation larger than the previous and subsequent values are found, and the found local maximum value and local minimum value are determined with respect to the original impulse response data. The value of the response data is held as a new impulse response data value. On the other hand, in other cases, “0” is held as the value of the new impulse response data. As a result, it is possible to reduce the amount of calculation in a resonance generation process described later.

  As shown in FIG. 3, the impulse response generator 18 initializes a calculation parameter to “n = 0” (step 301). The parameter “n” specifies the original impulse response data Ipo [n] and new impulse response data Ipg [n] to be processed. “N” corresponds to a value on the time axis of the impulse response.

  The impulse response generation unit 18 executes the processing from step 303 onward until n ≧ nTap (Yes in step 302).

  The impulse response generator 18 sets “0” to the n-th new impulse response data Irg [n] (step 303). If the parameter “n” is “0” (Yes in Step 304), the impulse response generator 18 increments the parameter “n” (Step 310) and returns to Step 302.

  On the other hand, if the parameter “n” is not “0” (No in step 304), the impulse response generator 18 stores the original impulse response data Iro [n−1], Iro [n], Iro from the storage unit 16. [N + 1] is read and dp = Iro [n] −Iro [n−1] and dn = Iro [n] −Iro [n + 1] are calculated (steps 305 and 306). “Dp” is the difference between the original impulse response data Iro [n] to be processed and the previous original impulse response data Iro [n−1], and “dn” This is the difference between the target original impulse response data Iro [n] and the next original impulse response data Iro [n + 1].

  If both “dp” and “dn” are “+ (minus)”, the original impulse response data Iro [n] is maximal. On the other hand, if both “dp” and “dn” are “− (minus)”, the original impulse response data Iro [n] is minimal.

  In the present embodiment, when the original impulse response data Ipo [n] is a local maximum value that is larger than a predetermined threshold Th than the previous and subsequent values, that is, when dp ≧ Th and dn ≧ Th ( Yes in step 307) Or, if the original impulse response data Ipo [n] is a minimum value that is smaller than a predetermined negative threshold value -Th from the previous and subsequent values, that is, dp≤-Th and dn≤ When it is -Th (Yes in Step 308), the impulse response generation unit 18 stores the original impulse response data Ipo [n] as new impulse response data Ipg [p] in the storage unit 16 ( Step 309).

  Accordingly, when it is determined Yes in step 307 or step 308, the impulse response generation unit 18 stores new impulse response data Irg [n] = Iro [n] in the storage unit 16, otherwise. , Irg [n] = 0 is stored in the storage unit 16.

  Next, the impulse response generator 18 increments the parameter “n” (step 310) and returns to step 302.

  3, when the original impulse response data Ipo [n] is a local maximum value that is larger than a predetermined threshold value Th than the previous and subsequent values, or the original impulse response data Ipo [n] When the value is a minimum value smaller than a predetermined threshold value -Th from the previous and subsequent values, new impulse response data that matches the value of the original impulse response data is generated and stored in the storage unit 18. In other cases, new impulse response data having a value “0” is generated and stored in the storage unit 18. In the present embodiment, the number of data of the original impulse response data Iro [n] and the new impulse response data Irg [n] itself is the same, but the amount of calculation can be reduced as will be described later.

  FIG. 4 is a diagram for explaining generation of new impulse response data according to the present embodiment. For example, when the original impulse response data Iro [s + 1] (reference numeral 401) is the processing target Iro [n], dp = Iro [s + 1] −Iro [s] ≧ Th and dn = Iro [s + 1] − It is assumed that Iro [s + 2] ≧ Th. In this case, Iro [s + 1] is stored in the corresponding new impulse response data Irg [s + 1] (reference numeral 411).

  When Iro [s + 2] to Iro [s + t] are set as processing target Iro [n], dp ≧ Th and dn ≧ Th, or dp ≦ −Th and dp ≦ −Th are established in the processing of FIG. If not, the corresponding Irg [s + 2] to Irg [s + t] are each “0”.

  Further, when the original impulse response data Iro [s + t + 1] (reference numeral 402) is the processing target Iro [n], dp = Iro [s + t + 1] −Iro [s + t] ≦ −Th and dn = Iro [s + t + 1] It is assumed that −Iro [s + t + 2] ≦ −Th. In this case, Iro [s + t + 1] is stored in the corresponding new impulse response data Irg [s + t + 1] (reference numeral 412).

  Using the new impulse response data Irg (hereinafter simply referred to as “impulse response data”) generated in this manner and stored in the storage unit 18, a convolution operation is executed by the resonance generating unit 20. Thus, resonance data is generated.

  5 and 6 are flowcharts showing examples of processing executed by the resonance generator 20 according to the present embodiment. In the process of FIG. 5, the tone signal data and the impulse response data are convolutionally calculated. In the processing of FIG. 6, the value of the input data buffer 22 (delay memory value DM) is shifted.

  As shown in FIG. 5, the resonance generator 20 initializes a parameter for calculation to “k = 0” (step 501). The parameter “k” specifies the delay memory value DM [k] in the input buffer 22 and the impulse response data Irg [k] in the storage unit 16.

  The resonance generation unit 20 sets the accumulated value “acc = 0” (step 502) and sets the leading delay memory value DM [0] = xin (step 503). xin is the latest musical tone signal data. As will be described later, the input data buffer 22 according to the present embodiment stores musical sounds from the latest musical tone signal data DM [0] to musical tone signal data DM [nTap-1] which is a sample nTap before in the time axis direction. A data string of signal data can be stored. That is, the input data buffer is used as an nTap stage delay memory. The delay memory value DM [k] stored in the input data buffer 22 will be described in detail later.

  Next, the resonance generator 20 performs the following processing until k ≧ nTap (Yes in step 504). The resonance generator 20 determines whether the impulse response data Irg [k] is “0” (step 505). When it is determined No in step 505, the resonance generating unit 20 calculates an accumulated value acc = acc + Irg [k] × DM [k] (step 506). That is, the resonance generator 20 adds the product of the kth impulse response data Irg [k] and the kth delay memory value DM [k] to the accumulated value acc. Thereafter, the resonance generator 20 increments the parameter “k” (step 507).

  On the other hand, when Irg [k] = 0 (Yes in Step 505), the resonance generating unit 20 does not update the accumulated value and increments the parameter “k” (Step 507). That is, in the present embodiment, when Irg [k] = 0, the calculation of the accumulated value can be omitted. As a result, it is possible to reduce the amount of calculation when generating the resonance sound data.

  When the convolution calculation is completed (Yes in step 504), the resonance generator 20 shifts the delay memory value stored in the input data buffer 22. As shown in FIG. 6, the resonance generator 20 initializes the parameter k to “nTap−1” (step 601), and executes the following processing until k = 0 (Yes in step 602). .

  The resonance generator 20 updates the value of the input data buffer 22 so that the delay memory value DM [k−1] is set as the delay memory value DM [k] in the input data buffer 22 (step 603). Thereafter, the resonance generating unit 20 decrements the parameter k (step 604).

  As shown in FIG. 7, the input data buffer 22 stores the latest tone signal data x (t) at time “t” in DM “0”, DM [1], DM “2”,. In the order of DM [nTap-1], past musical sound signals x (t-1), x (t-2), ..., x (t- (nTap-1)) are stored ( Reference numeral 700). In step 603 of FIG. 6, as indicated by reference numeral 701, the input data buffer 22 is updated so that DM [k] = DM [k−1]. As a result, a new value can be input to the first delay memory value DM [0]. In step 503 in FIG. 5, the latest musical tone signal data xin is stored as DM [0].

  If it is determined Yes in step 602, the resonance generation unit 20 multiplies the accumulated value acc by a predetermined correction value constA to generate resonance sound data yout (step 605). The generated resonance sound data yout is stored in the resonance sound data buffer 24. The resonance data stored in the resonance data buffer 24 is read out at a predetermined timing, DA-converted, amplified as an acoustic signal, and emitted from a speaker or the like.

  FIG. 14A is a graph showing an example of impulse response characteristics based on the original impulse response data, and FIGS. 14B and 14C are impulses based on the impulse response data generated according to the first embodiment. It is a graph which shows the example of a response characteristic. FIG. 14B shows the result of calculation with Th = 0.0001, and FIG. 14C shows the result of calculation with Th = 0.002. In the graph, the horizontal axis is the time axis of impulse response, and the vertical axis is the value of impulse response data.

  Compared with FIG. 14A, the impulse response data value “0” appears in FIG. 14B and FIG. 14C, indicating that the data amount is reduced.

  According to the present embodiment, in the impulse response waveform, the values of the maximum point and the minimum point corresponding to the point that particularly reproduces the characteristic of the reflected sound among resonance sounds are held as impulse response data. A convolution operation using the impulse response data thus performed is executed. Thereby, it is possible to more faithfully reproduce the reverberation of the resonance sound while reducing the amount of calculation.

  Further, in the present embodiment, the amount of data is reduced by setting “0” for the minimum value and the original impulse response data other than the minimum value whose fluctuations are larger than the threshold value compared to the previous and next values. The minimum value and the maximum value are considered to represent the characteristics of the reflected sound transmitted by reflecting off the wall or the like among the resonance sounds. Only the maximum and minimum values whose fluctuations are larger than the predetermined value are stored as impulse response data, and the others are set to “0”, thereby reducing the amount of data and improving reproducibility. It becomes possible to realize a resonant sound.

  Further, according to the present embodiment, the convolution calculation is performed only for the new impulse response data that actually has a value (that is, the value that is not “0”), so that the convolution for generating the resonance sound is performed. The amount of calculation can be reduced.

  Next, a second embodiment of the present invention will be described. In the first embodiment, the threshold value Th for determining the maximum value and the minimum value held as impulse response data is a fixed value. In the second embodiment, the threshold value is changed according to the time axis of the impulse response characteristic.

  FIG. 8 is a flowchart illustrating an example of impulse response data generation processing according to the second embodiment of the present invention. Also in the second embodiment, as in the first embodiment, the impulse response generation unit 18 reads the original impulse response data 12 stored in the storage unit 16, and in the original impulse response data 12, Find a local maximum value that is larger than a predetermined threshold value and a local minimum value that is smaller than a predetermined negative threshold value before and after the previous and next values, and for the local maximum value and local minimum value, the value of the original impulse response data Is held as the value of the new impulse response data 14. On the other hand, in other cases, “0” is held as the value of the new impulse response data.

  In the second embodiment, the threshold value Thnew when finding the minimum value and the maximum value is calculated so as to be a linear line that monotonously decreases along the time axis of the impulse response characteristic, as will be described later.

  As shown in FIG. 8, the impulse response generator 18 initializes a calculation parameter to “n = 0” (step 801). The parameter “n” specifies the original impulse response data Ipo [n] and new impulse response data Ipg [n] to be processed. The parameter “n” corresponds to a value on the time axis of the impulse response characteristic.

The impulse response generation unit 18 executes the processing from step 803 onward until n ≧ nTap (Yes in step 802).
The impulse response generator 18 sets “0” to the nth new impulse response data Irg [n] (step 803). If the parameter “n” is “0” (Yes in Step 804), the impulse response generator 18 increments the parameter “n” (Step 811) and returns to Step 802.

  On the other hand, if the parameter “n” is not “0” (No in Step 804), the impulse response generator 18 calculates a new threshold value Thnew such that the threshold value Thnew = Th−Th × n / nTap ( Step 805). Here, the original threshold value Th is a predetermined constant. If the parameter “n” is “0”, the threshold value Thnew = Th. If the parameter “n” is “nTap”, the threshold value Thnew = 0. That is, the threshold value Thnew is Thnew = Th when the parameter “n” corresponding to the time axis of the impulse response characteristic is “0”, Thnew = 0 when the parameter “n” is “nTap”, and the parameter “n” is When “0 <n <nTap”, it is one point on a straight line connecting two points ((0, Th) and (nTap, 0)).

  In the second embodiment, as the value of the impulse response characteristic on the time axis increases, the impulse response data at the point where the change is smaller can be ignored by linearly decreasing the threshold value Thnew. It can be taken in without being. Thereby, it is possible to reproduce a resonance sound having a longer reverberation.

  Next, the impulse response generation unit 18 reads the original impulse response data Iro [n−1], Iro [n], Iro [n + 1] from the storage unit 16, and dp = Iro [n] −Iro [n−1]. And dn = Iro [n] −Iro [n + 1] is calculated (steps 806 and 807). “Dp” and “dp” are the same as in the first embodiment. If both “dp” and “dn” are “+ (minus)”, the original impulse response data Iro [n] is It will be maximal. On the other hand, if both “dp” and “dn” are “− (minus)”, the original impulse response data Iro [n] is minimal.

  When the original impulse response data Ipo [n] is a local maximum value that is larger than the threshold value Thnew than the previous and subsequent values, that is, when dp ≧ Thnew and dn ≧ Thnew (Yes in step 808), If the impulse response data Ipo [n] is a local minimum value that is smaller than the negative threshold value −Thnew, that is, dp ≦ −Thnew and dn ≦ −Thnew (Yes in step 809). The impulse response generator 18 stores the original impulse response data Ipo [n] as new impulse response data Ipg [p] in the storage unit 16 (step 810).

  Therefore, if it is determined Yes in step 808 or step 809, the impulse response generation unit 18 stores new impulse response data Irg [n] = Iro [n] in the storage unit 16, otherwise. , Irg [n] = 0 is stored in the storage unit 16.

  Next, the impulse response generator 18 increments the parameter “n” (step 811) and returns to step 802.

  Also in the second embodiment, the generation of resonance data is the same as that in the first embodiment shown in FIGS. That is, the resonance generation unit 20 reads out the new impulse response data 14 from the storage unit 16 and generates the resonance data by performing a convolution operation on the delay memory value stored in the input data buffer 22 and the impulse response data. is doing. Further, the resonance generation unit 20 shifts the delay memory value of the input data buffer 22 every time one piece of resonance data is generated (see FIG. 6).

  In this way, also in the second embodiment, the resonance generator 20 generates the resonance data yout and stores it in the resonance buffer 24. The resonance data stored in the resonance data buffer 24 is read out at a predetermined timing, DA-converted, amplified as an acoustic signal, and emitted from a speaker or the like.

  FIGS. 15A to 15C show original impulse response data, new impulse response data generated by the first embodiment, and new impulse generated by the second embodiment, respectively. It is a graph which shows the example of the impulse response characteristic based on the impulse response data based on response data. In the graphs shown in FIGS. 15B and 15C, Th = 0.002.

  Comparing FIG. 15 (b) and FIG. 15 (c), the second embodiment (FIG. 15 (c)) also shows a larger value on the time axis of the impulse response characteristic than “ It can be seen that there are impulse response data values other than "0". That is, it is shown that a resonance sound having a longer reverberation can be reproduced.

  According to the second embodiment, as the value of the impulse response characteristic on the time axis increases, the threshold value Thnew is decreased, so that the impulse response data at a smaller change point is not ignored. It can be imported. Thereby, it is possible to appropriately reproduce a resonance sound having a longer reverberation.

  Next, a third embodiment of the present invention will be described. In the second embodiment, as the value of the impulse response characteristic on the time axis increases, the threshold value Thnew is linearly reduced, so that the impulse response data at the point where the change is smaller is not ignored. To be able to capture. In the third embodiment, the threshold value Thnew is reduced according to an exponential function instead of a straight line.

  FIG. 9 and FIG. 10 are flowcharts showing impulse response data generation processing according to the third embodiment of the present invention.

  Also in the third embodiment, as in the first and second embodiments, the impulse response generation unit 18 reads the original impulse response data 12 stored in the storage unit 16, In the original impulse response data 12, find a local maximum value that is larger than the threshold value Thnew from the previous and subsequent values, and a local minimum value that is smaller than the negative threshold value -Thnew from the previous and subsequent values. Holds the value of the original impulse response data 12 as the value of the new impulse response data 14. On the other hand, in other cases, “0” is held as the value of the new impulse response data 12.

  In the third embodiment, the threshold value Thnew when determining the minimum value and the maximum value is calculated so as to be an exponential curve that decreases along the time axis of the impulse response, as will be described later.

  As shown in FIG. 9, the impulse response generator 18 sets the value when n = nTap, and Rpow = specified value which is a parameter for determining the shape of the curve, particularly the degree of constriction (step 901), and Rrange = 10 ^ (-Rpow) is calculated (step 902). Rpow is input by the operator in advance using the input device 36, stored in the RAM 34, and the impulse response generator 18 may read it from the RAM 34 in step 901.

  Next, the impulse response generation unit 18 calculates an exponential exponent A = log (Rrange) / (nTap × log (Base)) with a radix Base = 2 (steps 903 and 904).

  In addition, the impulse response generator 18 initializes the calculation parameter to “n = 0” (step 905). The parameter “n” specifies the original impulse response data Ipo [n] and new impulse response data Ipg [n] to be processed. The parameter “n” corresponds to a value on the time axis of the impulse response characteristic.

The impulse response generation unit 18 executes the processing from step 1002 onward until n ≧ nTap (Yes in step 1001).
The impulse response generator 18 sets “0” to the n-th new impulse response data Irg [n] (step 1002). If the parameter “n” is “0” (Yes in Step 1003), the impulse response generator 18 increments the parameter “n” (Step 1010) and returns to Step 1001.

  On the other hand, if the parameter “n” is not “0” (No in step 1003), the impulse response generator 18 calculates a new threshold value Thnew such that the threshold value Thnew = Th × Base ^ (A × n). (Step 1004).

The original threshold Th is a predetermined constant. If the parameter “n” is “0”, the threshold Thnew = Th × Base ^ 0 = Th, and if the parameter “n” is “nTap”, the threshold Thnew. = Th * Base ^ (A * nTap) = Th * 2 ^ (logRrange / log2) = Th * Rrange.
That is, the threshold value Thnew is Thnew = Th when the parameter “n” corresponding to the time axis of the impulse response is “0”, Thnew = Th × Rrange when the parameter “n” is “nTap”, and the parameter “n”. However, when “0 <n <nTap”, it is a point on the exponentially decreasing exponential function connecting two points ((0, Th) and (nTap, Th × Range).

  11 to 13 are graphs showing changes in the threshold value Thnew. 11 is a graph when Rpow = 1 (Rrange = 0.1), FIG. 12 is a graph when Rpow = 2 (Rrange = 0.01), and FIG. 12 is a graph when Rpow = 3 (Rrange = 0.001). is there. In each graph, Th = 1. In the graph, the vertical axis represents the Thnew value, and the horizontal axis represents the time axis of the impulse response characteristics. As shown in FIGS. 11 to 13, in the third embodiment, as Rpow increases, the degree of constriction increases (the initial decrease becomes significant), and the value when n = nTap is as follows. It is getting smaller. In this way, by changing Rpow, it is possible to change the degree of change of the threshold when determining the maximum value and the minimum value as desired.

  FIGS. 16A to 16C are graphs showing examples of impulse response characteristics based on new impulse response data generated by the third embodiment. 16A to 16C calculate new impulse response data with Rpow = 1, Rpow = 2, and Rpow = 5, respectively.

  According to the third embodiment, as the value of the impulse response characteristic on the time axis increases, the threshold value Thnew is decreased, so that the impulse response data at a smaller change point is not ignored. It can be imported. Thereby, it is possible to appropriately reproduce a resonance sound having a longer reverberation. In particular, exponentially, when the value on the time axis is relatively small, the threshold is decreased relatively steeply, and when the value on the time axis is relatively large, the degree of decrease in the threshold is reduced. As a result, it is possible to obtain more appropriate local maximum and minimum values.

  The present invention is not limited to the above embodiments, and various modifications can be made within the scope of the invention described in the claims, and these are also included in the scope of the present invention. Needless to say.

  For example, in the second embodiment, on the time axis of the impulse response characteristic, a value on a linear line that monotonously decreases, such as a predetermined threshold Th when n = 0 and 0 when n = nTap. The impulse response generator 18 calculates the threshold value Thnew according to the value of n. However, the linear line is not limited to that described above, and the threshold value Thnew may be calculated according to the value of n as a value smaller than Th when n = nTap.

  Further, in the third embodiment, a predetermined threshold value Th when n = 0, and a monotonically decreasing value on the exponential function that becomes a set value Th × Range when n = nTap Thus, the impulse response generator 18 calculates the threshold value Thnew according to the value of n. However, it is not limited to an exponential function that takes the above-described values. Furthermore, another function that decreases monotonously as the value of the impulse response characteristic on the time axis increases, such as decreasing the threshold Thnew, can be used to calculate the threshold Thnew.

FIG. 1 is a block diagram showing a configuration of a resonance adding apparatus according to an embodiment of the present invention. FIG. 2 is a block diagram showing a hardware configuration of the resonance adding apparatus according to the present embodiment. FIG. 3 is a flowchart showing an example of impulse response data generation processing according to the present embodiment. FIG. 4 is a diagram for explaining generation of new impulse response data according to the present embodiment. FIG. 5 is a flowchart showing an example of processing executed by the resonance generating unit according to the present embodiment. FIG. 6 is a flowchart illustrating an example of processing executed by the resonance generating unit according to the present embodiment. FIG. 7 is a diagram illustrating an example of the configuration of the input data buffer according to the present embodiment. FIG. 8 is a flowchart illustrating an example of impulse response data generation processing according to the second embodiment of the present invention. FIG. 9 is a flowchart showing an impulse response data generation process according to the third embodiment of the present invention. FIG. 10 is a flowchart showing a process of generating impulse response data according to the third embodiment of the present invention. FIG. 11 is a graph showing an example of the threshold value Thnew in the resonance adding apparatus according to the third embodiment of the present invention. FIG. 12 is a graph showing an example of the threshold value Thnew in the resonance adding apparatus according to the third embodiment of the present invention. FIG. 13 is a graph showing an example of the threshold value Thnew in the resonance adding apparatus according to the third embodiment of the present invention. FIG. 14A is a graph showing an example of impulse response characteristics based on the original impulse response data, and FIGS. 14B and 14C are impulses based on the impulse response data generated by the first embodiment. It is a graph which shows the example of a response characteristic. FIGS. 15A to 15C show original impulse response data, new impulse response data generated by the first embodiment, and new impulse generated by the second embodiment, respectively. It is a graph which shows the example of the impulse response characteristic based on the impulse response data based on response data. FIGS. 16A to 16C are graphs showing examples of impulse response characteristics based on new impulse response data generated by the third embodiment.

Explanation of symbols

12 Original impulse response data 14 New impulse response data 16 Storage unit 18 Impulse response generation unit 20 Resonance sound generation unit 22 Input data buffer 24 Resonance sound data buffer 30 CPU
32 ROM
34 RAM
36 Input device 38 Display device 40 Sound system 44 Music generation circuit

Claims (8)

An input data buffer storing a series of musical tone signal data on the time axis as a delay memory value;
A storage unit storing impulse response data which is a value on the time axis representing the impulse response characteristics;
Resonance sound adding means comprising: a resonance sound generating means for generating a resonance sound data by convolving a value of the impulse response data and a delay memory value stored in an input data buffer,
The storage unit stores original impulse response data,
The original impulse data stored in the storage unit is taken out, and a local maximum value and a local minimum value that vary by a predetermined amount from the previous and subsequent values are found, and the found local maximum value and local minimum value are found in the impulse response data. Impulse response generation means for storing in the storage unit a value indicating “0” as a value of the impulse response data other than the found local maximum value and local minimum value as a value. A resonance sound adding device comprising:   The resonance generating means multiplies the value of the impulse response data by the delay memory value and accumulates the multiplied value only when the value of the impulse response data is other than “0”. The resonant sound adding apparatus according to claim 1, wherein the resonant sound adding apparatus is configured as described above.   The impulse response generation means calculates a threshold value corresponding to a position on the time axis of the impulse response characteristic of the original impulse response data so as to be a value on a straight line that decreases monotonously along the time axis. The resonance addition apparatus according to claim 1 or 2, wherein a maximum value and a minimum value having a fluctuation larger than the threshold value are found from values before and after.   The impulse response generating means calculates a threshold value corresponding to a position on the time axis of the impulse response characteristic of the original impulse response data so as to be a value on an exponential curve that monotonously decreases along the time axis. The resonance addition apparatus according to claim 1, wherein the resonance value adding device is configured to find a local maximum value and a local minimum value that are larger than the threshold value from previous and subsequent values. In a computer comprising: an input data buffer that stores a series of musical sound signal data on a time axis as a delay memory value; and a storage unit that stores impulse response data that is a value on the time axis representing an impulse response characteristic. On the computer,
A resonance addition program for executing a resonance generation step for generating resonance data by convolving a value of the impulse response data and a delay memory value stored in an input data buffer,
The storage unit stores original impulse response data,
In the computer,
The original impulse data stored in the storage unit is taken out, and a local maximum value and a local minimum value that vary by a predetermined amount from the previous and subsequent values are found, and the found local maximum value and local minimum value are found in the impulse response data. An impulse response generating step of storing in the storage unit as a value and storing a value indicating “0” in the storage unit as a value of the impulse response data other than the found local maximum value and local minimum value A resonance addition program characterized by being executed. In the resonance sound generation step,
Only when the value of the impulse response data is other than “0”, the step of multiplying the value of the impulse response data by the delay memory value and accumulating the multiplied values is executed. The resonance sound adding program according to claim 5. In the impulse response generation step, the computer
Calculating a threshold value corresponding to a position on the time axis of the impulse response characteristic of the original impulse response data so as to be a value on a straight line that decreases monotonously along the time axis;
The resonance sound adding program according to claim 5 or 6, wherein a step of finding a local maximum value and a local minimum value having a fluctuation larger than the threshold value from previous and subsequent values is executed. In the impulse response generation step, the computer
Calculating a threshold value corresponding to a position on the time axis of the impulse response characteristic of the original impulse response data so as to be a value on an exponential curve that monotonously decreases along the time axis;
The resonance sound adding program according to claim 5 or 6, wherein a step of finding a local maximum value and a local minimum value having a fluctuation larger than the threshold value from previous and subsequent values is executed.