JP3138612B2 - Electronic musical instrument - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an electronic musical instrument which stores a waveform compressed by a differential PCM method or an adaptive differential PCM method and performs repeated reading, and requires a device for resetting a decoding device at a leading read portion. The present invention relates to an electronic musical instrument capable of repeatedly reading out without being read.

[0002]

2. Description of the Related Art An important issue in electronic musical instruments is how to generate musical tones that approximate natural sounds.
In recent years, the PCM system in which a natural sound is sampled and stored, and a tone is generated by reading the sampled sound from a stored waveform memory has become mainstream.

However, the waveform of a natural sound is different for each pitch and volume, and in order to generate a musical tone similar to a more natural sound by the PCM system, a different waveform for each pitch and volume is generated. It is necessary to prepare it, and the waveform memory for storing it is enormous.

Therefore, as a method of compressing the memory, a differential PCM method (hereinafter referred to as a DPCM method) for storing a difference value from a prediction value using a prediction filter or an adaptive difference P
The CM system (hereinafter referred to as ADPCM system) is used.

In the PCM system, not all data from the start to the end of the sounding of a natural sound is stored, but a sounding start part and a part of the subsequent waveform are stored, and the sounding start part is reproduced. Later, memory is saved by using a method of forming a musical tone by repeatedly reproducing a part of the stored waveform.

However, these DPCM systems and AD
In the PCM method, repeated reading of a waveform is considered to be an effective means, but has a drawback that errors are accumulated because data is encoded and processed using a prediction filter.

In order to repeatedly read a waveform, it is necessary that the contents of the delay register of the prediction filter match each time at the beginning of the repetition.

Therefore, in the conventional electronic musical instrument, to prevent accumulation of errors and to return to the same original waveform every time at the beginning (loop top) of the repeated reading, the contents of the delay register are re-read at the beginning of the repeated reading. Set-up measures have been taken and equipment has been provided for this.

As described above, in order to repeatedly read a waveform in a conventional electronic musical instrument, a special device for resetting is required, so that there is a disadvantage that the structure is complicated and expensive, and a countermeasure is required. I was

[0010]

SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, and in an electronic musical instrument that stores a waveform compressed by the DPCM system or the ADPCM system, decoding is performed at the loop top when repeatedly reading. It is an object of the present invention to provide an electronic musical instrument capable of repeatedly reading without requiring a device for resetting the device.

[0011]

SUMMARY OF THE INVENTION The present invention provides a second order differential P
In an electronic musical instrument that repeatedly reads and decodes a waveform encoded by the CM method or the adaptive difference PCM method, a prediction filter means for sampling an original waveform and compression-encoding the sampled original waveform data; Encoding means comprising: a predictive filter coefficient calculating means for calculating a filter coefficient, wherein the predictive filter coefficient is set such that an impulse response of the predictive filter is shorter than a repetitive read interval of a waveform to be repeatedly read. Encoding means for generating compression-encoded data corresponding to the prediction filter coefficient, prediction filter coefficient storage means for storing the prediction filter coefficient, and storing the generated compression-encoded data. Compression encoding data storage means, and a prediction filter from the prediction filter coefficient storage means. A predictive filter coefficient reading means for reading the number, a compressed waveform data reading means for reading the compressed waveform data from the compressed and coded data storage means, and a filter means having a decoding register. A decoding means for decompressing and decoding the compressed and coded data read from the coded data storage means, wherein the contents of the decoding register match each time at the beginning of repeated reading. It is.

[0012]

[0013]

[0014]

According to the present invention, in an electronic musical instrument in which a waveform is compressed by the DPCM system or the ADPCM system and the waveform is repeatedly read, the prediction is repeatedly performed by using a filter coefficient with high convergence and high stability. The error can be absorbed up to the end part (loop end) of.

For this reason, in the present invention, for example, an optimal waveform and a filter coefficient are obtained in advance by simulation using a general-purpose computer, and the waveform data and prediction filter coefficient obtained as a result of the simulation are mounted on an electronic musical instrument. It is.

As a result, the contents of the delay register always have the same value at the beginning (loop top) of the repetitive reading. Therefore, when shifting from the end (loop end) to the beginning (loop top) of the repeating reading, This eliminates the need for a device for resetting the new value, and can provide a low-cost electronic musical instrument with a simple structure, excellent compression efficiency.

[0017]

DESCRIPTION OF THE PREFERRED EMBODIMENTS First, prediction filter coefficients will be described.
FIG. 8 is a diagram illustrating the relationship between the value of the prediction filter coefficient and the stability. 8A shows an example of a primary prediction filter, FIGS. 8B and 8C show an example of an impulse response of an unstable filter, and FIG. 8D shows a highly stable filter. 3 shows an example of the impulse response of FIG.

For example, assume that data of impulse 1, 0, 0 is input. At this time, it is assumed that the filter coefficient of the prediction filter in FIG.

In this case, 1 is input at first and 1 is output, but 0 is input at the second and subsequent times, and a value a times the previous output value is added from the filter. Therefore, FIG.
As shown in B, 1 is always output from the filter.

Further, for example, in the case of a = 2, the output values become 1, 2, and 4, and as shown in FIG. 8C, the output diverges rapidly, causing a failure such as overflow.

In order to make the impulse response converge within the loop period of the waveform to be repeatedly read, for example, when a = 0.1 is used as the filter coefficient, the output value is as shown in FIG. , 1, 0.1, 0.01, 0.00
It becomes 1 and rapidly converges to the input value 0.

For this reason, errors in repeated reading of a waveform are not accumulated at the loop end, and the value of the loop top is correctly set at the time of reading the next waveform.

FIG. 9A is a diagram showing an example of errors accumulated when the same waveform is repeatedly read. As shown in the figure, when errors accumulate, the amplitude of the waveform at the loop end is read by adding the error, and this affects the amplitude of the loop top of the next read waveform.

For this reason, as exemplified in FIG.
Each time the reading is repeated, the error is accumulated and the waveform is shifted upward as shown in the figure. If the waveform is repeated many times, the waveform may cause a trouble such as overflow.

FIG. 9B is a diagram showing an example of an output when a filter having high stability is used. As shown in the figure, the error at the loop end is absorbed by the loop end of the next repetitive reading, so that the error is not accumulated every time the reading is repeated.

For this reason, it is possible to repeatedly read the same waveform stably as shown in FIG. 9B, and a device for resetting a new value at the loop top becomes unnecessary.

The present invention has been made by paying attention to this point. When repeatedly reading out a waveform compressed by the DPCM method, a filter having fast convergence and high stability is used, so that a loop within a loop section can be obtained. This is to prevent errors from accumulating.

An embodiment in which the present invention is applied to the DPCM system will be described below.

In the above description, since a first-order prediction filter was used, convergence was possible if the prediction filter coefficient was -1 <a <1.

However, the shapes of actually input waveforms vary widely, and it is necessary to use second-order, third-order, and higher-order filters in order to increase the accuracy of the filters and reduce noise. Therefore, the prediction filter coefficients cannot be simply determined.

Therefore, in the present invention, a waveform compressed in advance by the DPCM method or the ADPCM method and an optimum prediction filter coefficient corresponding to the waveform are simulated using, for example, a general-purpose computer or the like, and the waveform data and the used data are used. A prediction filter coefficient is obtained in advance, and the waveform is mounted on an electronic musical instrument for use.

FIG. 2 is a diagram for explaining a procedure for preparing a prediction filter coefficient and a compressed waveform in advance using, for example, a general-purpose computer. Hereinafter, a procedure of generating waveform data of a compressed waveform and a prediction filter coefficient of the present invention will be described with reference to the drawings.

In the figure, reference numeral 50 denotes a prediction block;
0 is an encoding unit. The prediction block 50 includes a prediction filter coefficient calculation unit 51 and a prediction filter coefficient memory unit 52, and the encoding unit 60 includes a DPCM encoding unit 61 and a waveform memory 62.

The prediction filter coefficient calculation unit 51 extracts a plurality of samples from an input original waveform such as a natural sound, makes prediction, and calculates and determines an optimum prediction filter coefficient. The determined coefficients are stored in the prediction filter coefficient memory unit 52 and the DPCM encoding unit 6
Sent to 1.

The prediction filter coefficient memory unit 52 is composed of, for example, a ROM and stores the prediction filter coefficients determined by the prediction filter coefficient calculation unit 51. The prediction filter coefficients stored in the prediction filter coefficient memory unit 52 are used as data stored in the prediction filter coefficient memory unit 21 of the electronic musical instrument.

The DPCM encoder 61 quantizes the input original waveform and encodes and compresses the waveform by the DPCM method based on the prediction filter coefficient sent from the prediction filter coefficient calculator 51. The compressed waveform is stored in the waveform memory unit 62.

The waveform stored in the waveform memory section 62 is used as data in the waveform memory 6 of the electronic musical instrument. Note that the prediction filter coefficients stored in the prediction filter coefficient memory unit 52 and the compressed waveform data stored in the waveform memory unit 62 form a pair, and related data for this is also stored in a predetermined area of a ROM (not shown). Is stored.

Next, referring to FIG.
The operation of the encoder in the following case will be described. In encoding, first, prediction filter coefficients are determined.

In determining the prediction filter coefficient, the input sample data of the original waveform is taken out by the prediction filter coefficient calculation section 51, and the prediction filter coefficient calculation section 51 performs, for example, Levinson-D on the basis of the sample data.
The prediction filter coefficient is obtained by a method such as the urbin method or the Burg method.

The calculated prediction filter coefficients are stored in the prediction filter coefficient memory unit 52 and sent to the encoding unit 60.

The encoding unit 60 includes a delay register 61
1, 612, multipliers 613, 614, 615. Adder 6
16 and 617 and a quantization control block 618.

In such a configuration, the prediction filter coefficients sent from the prediction block 50 are set to K0 and K1 as the prediction filter coefficients of the primary and secondary filters.

Next, when a part of the original waveform is fetched into the prediction filter block 60, the values previously input two times before and the values fetched into the delay registers 611 and 612 are called out, and the multipliers 613 and 614 determine the values. After the coefficients are multiplied, they are added by an adder 616.

Further, after the sign is inverted by the multiplier 615, it is added to the original waveform inputted by the adder 617 to obtain a difference value. Thereafter, the quantization width control block 61
8 is quantized. As a result, a waveform subjected to predetermined compression is output, and the waveform is stored in the waveform memory 62.

Since the waveform according to the DPCM method is created in this way, the maker, when manufacturing an electronic musical instrument, prepares the waveform compressed by the above method, the prediction filter coefficient, and the data relating the waveform and the prediction filter coefficient. By incorporating the electronic musical instrument in an electronic musical instrument, an electronic musical instrument with a compressed waveform memory can be provided.

Further, when the loop end is reached as in the prior art, it is not necessary to provide a special device for resetting the waveform to be repeatedly read out to the loop top value, and a low-cost electronic musical instrument can be provided. Become.

Next, an electronic musical instrument equipped with a waveform and a prediction filter created based on the above embodiment will be described with reference to the drawings. FIG. 1 is a schematic block diagram illustrating the overall configuration of an electronic musical instrument according to the present invention.

In the figure, 10 is a CPU, 11 is a ROM, 12 is a RAM, and 13 is a display unit. Also, 1
Is a keyboard, 2 is a keyboard scan circuit, 3 is an operation panel, 4 is a panel scan circuit, 5 is a tone signal generator, and 6 is a waveform memory.

Reference numeral 7 denotes a decoder, 8 denotes a digital control filter (hereinafter referred to as DCF), 9 denotes a digital control amplifier (hereinafter referred to as DCA), 14 denotes a digital / analog converter (hereinafter referred to as a D / A converter), 15
Is an amplifier and 16 is a speaker.

The CPU 10 controls each section of the electronic keyboard instrument according to a control program stored in a program memory section (not shown) of the ROM 11, and controls to read out predetermined data in accordance with a key-depressed portion of the keyboard 1 to generate sound. Things.

The ROM 11 stores tone color data and various other fixed data in addition to the above-mentioned program for operating the CPU 10. Note that filter coefficients directly related to the present invention are stored in the prediction filter coefficient memory unit 21 of the ROM 11.

The RAM 12 has a work area for the CPU 10,
Various registers, counters, flags, buffers, and the like for controlling the electronic musical instrument are defined.
1 has a data area in which necessary data is transferred and temporarily stored.

A plurality of registers in which data necessary for sound emission are set in accordance with the setting states of the keys and switches on the operation panel 3 and each tone generation circuit (DCO) of the tone signal generator 5 are not used. The RAM 12 also includes an assigner memory for storing data to be allocated to channels, a storage area for storing musical sound information, and the like.

The keyboard 1 is used for designating a musical tone to be generated, and is composed of a plurality of keys and a key switch which opens and closes in conjunction with a key press / release operation of these keys. The key press / key release operation of the performer is performed by the keyboard scan circuit 2.
, And the detected signal is sent to the tone signal generator 5 under the control of the CPU 10.

The performance information generated by key depression or key release of the keyboard 1 is temporarily stored in a predetermined area of the RAM 12 and read out by the CPU 10 as required.

The keyboard scanning circuit 2 detects a key press / release operation of the player, that is, on / off of a key, and transmits the detected on / off information to the musical tone signal generating section 5 together with the key number. . The CPU 10 stores the key on / off information on the RAM 12.

The operation panel 3 is provided with various switches and indicators, such as a tone color selection switch, a mode designation switch, a melody selection switch, and a rhythm selection switch, in addition to a power switch.

The set / reset state of each switch of the operation panel 3 is detected by a panel scan circuit 4 included therein. Data on the set state of the switch detected by the panel scan circuit 4 is stored in the CPU 10. It is stored in a predetermined area on the RAM 12 under control.

The operation panel 3 is provided with a display 13 for displaying various information in addition to the various switches.

The tone signal generator 5 reads out tone waveform data and envelope data corresponding to the signal output from the CPU 10 from the waveform memory 6, adds an envelope to the read tone waveform data, and outputs the resulting tone signal. is there.

The tone signal generator 5 has a number of digital control oscillators (hereinafter referred to as “DC”) corresponding to the number of simultaneous sounds.
O ”), and a tone signal is generated by a different DCO for each tone and sent to the decoder 7.

The tone signal generator 5 is connected to a waveform memory 6 for storing waveform data and envelope data.

The decoder 7 is for decoding the waveform data sent from the tone signal generator 5, and the prediction filter coefficients of the present invention are used when the decoder 7 decodes the waveform data. You.

The DCF 8 is a digital control filter for adding a tone color change to the tone waveform transmitted from the decoder 7. The DCA 9 is a digital control amplifier for applying amplitude modulation to the tone waveform transmitted from the DCF 8.

The amplifier 15 amplifies the analog tone signal supplied from the D / A converter 14 with a predetermined gain. The output of the amplifier 15 is supplied to a speaker 16.

The speaker 16 converts an analog tone signal as an electric signal sent from the amplifier 15 into an acoustic signal. That is, a tone is emitted according to the generated tone signal.

In this configuration, when the performance starts,
The key press / key release data input from the keyboard 1 connected via the key press detection unit 2 and the sound generation conditions set on the operation panel 3 connected via the panel scan circuit 4 are RA.
It is temporarily stored in M12.

At a predetermined timing, RA
The keyboard data and panel event data stored in M12 are read out by the CPU 10, processed and provided to the tone signal generator 5, and the compressed tone signal is read and provided to the decoder 7 for decoding. And an original waveform is generated.

Next, the decoding flow of the decoder 7 of the electronic musical instrument of the present invention will be described with reference to FIG.

A part directly related to the decoding of the present invention is a waveform memory 6 for storing a compressed waveform, and a prediction filter for storing a prediction filter coefficient of a filter which is read when decoding the compressed waveform. A coefficient memory unit 21;
A DPCM decoding unit 22 that performs DPCM decoding includes an association data storage unit (not shown) that stores data that associates waveform data read from the waveform memory 6 with prediction filter coefficients.

In this configuration, for example, when it is detected that the keyboard 1 is pressed, under the control of the CPU 10, the tone signal generator 5 reads out the corresponding waveform data from the waveform memory 6 and generates a tone signal. Send to decoder 7.

On the other hand, the CPU 10 reads the association data for determining the prediction filter coefficient corresponding to the waveform read out by the musical tone signal generation section 5 and, based on the data, stores the predetermined prediction filter coefficient from the prediction filter coefficient memory section 21. The data is read and sent to the DPCM decoding unit 22.

The DPCM decoding section 22 performs decoding based on this to generate a musical tone waveform. The decoding operation will be described in detail with reference to FIG.

FIG. 5 is a diagram for explaining the structure of the decoder 7. As shown, the decoder 7 includes a quantization width control block 2
01, delay registers 202 and 203, multiplier 204,
205 and adders 206 and 207.

In this configuration, the tone signal generator 5 reads the compressed waveform read from the waveform memory 6 by the decoder 7.
To the decoder 7, the quantization width control block 20
1 controls the quantization width and sends it out.

At this time, at the same time, the CPU 10 reads out from the prediction filter coefficient memory section 21 the prediction filter coefficient value associated with the musical tone waveform read out by the musical tone signal generation section 5, and sets K0, K0, K1
Set to.

Thus, the delay registers 202 and 203
Is read out, the multiplier 204,
After a predetermined operation is performed in 205, the result is sent to an adder 206 and added to obtain a desired predicted value.

The predicted value is sent to the adder 207 and added to the input data to generate the original tone waveform, which is sent to the DCF 8.

These operations are performed by the tone signal generator 5.
The waveform data is repeated every time the waveform data is transmitted. A part of the waveform added and transmitted by the adder 207 is sequentially taken into the delay registers 202 and 203, and is used as the data of the waveform of the immediately preceding and last time. , 20
3 is stored.

In such an operation, if the filter coefficients of the present invention with fast convergence and high stability are used, the contents of the delay registers 202 and 203 always match at the loop top.
A device for resetting at the loop top becomes unnecessary.

Note that the encoder and decoder of the present invention
The following case is described as an example, but the present invention is not limited to this. The prediction filter coefficient memory is RO
Although provided at M, the memory may be provided at other locations.

Next, a description will be given of a case where the filter coefficient of the present invention, which has fast convergence and high stability, is applied to a waveform compressed by the ADPCM method.

The ADPCM system is a differential PCM system using adaptive quantization. Since the quantization width is adaptively controlled according to the amplitude value, a system capable of performing higher-performance encoding than the DPCM system. Also known as

However, when the present invention is applied to the ADPCM system, the structure and operation of the actual device are the DPCM
And the difference is only in the coding and decoding of the signal. Therefore, the description of the parts performing the same operation will be omitted, and only the differences will be described.

FIG. 6 is a view for explaining a waveform compression procedure when the present invention is applied to the ADPCM system. As shown in the drawing, the difference from the DPCM method when determining the filter coefficient is that the DPCM encoding unit 61 of the prediction filter block 60 uses
Only the PCM encoding unit 63 has been changed.
The method of encoding by the method is a known technique.

Accordingly, as in the case of the DPCM system, the operation of arbitrarily setting the filter coefficient, encoding the waveform based on the ADPCM encoding system, reproducing and checking the waveform is repeated, and a suitable prediction filter coefficient is obtained. Just choose.

Also, when the waveform according to the present invention is mounted on an electronic musical instrument, as shown in FIG.
2 is changed to the ADPCM encoding unit 23, and A
The encoding method using the DPCM method is a known technique,
The operation procedure is the same as in the case of DPCM.

According to the present invention, it is not necessary to reset even the waveform compressed and encoded by the ADPCM method when shifting from the loop end to the loop top, and the quality is further improved as compared with the DPCM encoding. A high waveform can be obtained.

In this embodiment, the case where the prediction filter coefficient is determined for each waveform is described as an example. However, the present invention is only required to be able to absorb an error within the cycle of a repeatedly read waveform. The prediction filter coefficient may be changed for each group.

[0090]

As described in detail above, according to the present invention, D
In an electronic musical instrument equipped with a waveform compressed by the PCM encoding method or the ADPCM encoding method, there is no need to reset when shifting from a loop end to a loop top of a waveform to be repeatedly read, and a high compression rate and structure can be achieved. However, an electronic musical instrument that is simple and inexpensive can be provided.

[Brief description of the drawings]

FIG. 1 is an overall configuration diagram of an electronic musical instrument equipped with waveform data of the present invention.

FIG. 2 is a diagram illustrating an operation of calculating a filter coefficient using a general-purpose computer or the like in waveform compression of the DPCM method.

FIG. 3 is a diagram illustrating an encoding operation in a general-purpose computer.

FIG. 4 is a diagram illustrating the operation of a decoder of an electronic musical instrument equipped with a waveform according to the DPCM method.

FIG. 5 is a block diagram illustrating a configuration of a decoder of an electronic musical instrument equipped with a waveform according to the DPCM method.

FIG. 6 is a diagram illustrating an operation of calculating a filter coefficient using a general-purpose computer or the like in waveform compression in the ADPCM system.

FIG. 7 is a diagram illustrating an operation of a decoder of an electronic musical instrument equipped with a waveform according to the ADPCM method.

FIG. 8 is a diagram illustrating a relationship between a filter coefficient and an impulse response.

FIG. 9 is a diagram (continued) illustrating the relationship between the filter coefficient and the impulse response.

[Explanation of symbols]

Electronic musical instrument 1 Keyboard 2 Keyboard scan circuit 3 Operation panel 4 Panel scan circuit 5 Music signal generator 6 Waveform memory 7 Decoder 8 DCF 9 DCA 10 CPU 11 ROM 12 RAM 13 Display unit 14 D / A converter 15 Amplifier 16 Speaker 21 Prediction Filter coefficient memory 22 DPCM decoding unit 23 ADPCM decoding unit 201 Quantization width control block 202, 203 Delay register 204, 205 Multiplier 206, 207 Adder General-purpose computer 50 Prediction block 51 Prediction filter coefficient calculation unit (Prediction filter coefficient calculation Means) 52 prediction filter coefficient memory (prediction filter coefficient storage means) 60 prediction filter block (encoder) 61 DPCM encoder (encoding means) 62 waveform memory (waveform storage means) 63 ADPCM encoder (encoding means) ) 611, 612 Delay register 613, 614, 615 Multiplier 618 Quantization block

Continuation of the front page (56) References JP-A-2-140021 (JP, A) JP-A-2-146599 (JP, A) JP-A-63-289594 (JP, A) JP-A-62-242996 (JP, A) JP-A-62-242995 (JP, A) JP-A-62-22993 (JP, A) JP-A-5-257478 (JP, A) (58) Fields investigated (Int. Cl. ⁷ , DB Name) G10H 7/02

Claims (1)

(57) [Claims] 1. A second-order differential PCM method or an adaptive differential P
In an electronic musical instrument that repeatedly reads and decodes a waveform encoded by the CM method, a prediction filter means for sampling an original waveform and compression-encoding the sampled original waveform data, and calculating a filter coefficient of the prediction filter. A prediction filter coefficient calculating means, wherein the prediction filter coefficient is set such that an impulse response of the prediction filter is shorter than a repetitive read interval of a waveform to be repeatedly read. Coding means for generating compression-coded data according to the coefficient; prediction filter coefficient storage means for storing the prediction filter coefficient; and compression-coded data storage for storing the generated compression-coded data Means for predicting a prediction filter coefficient from the prediction filter coefficient storage means. Filter data reading means for reading compressed waveform data from the compressed coded data storage means, and filter means having a decoding register, and storing the compressed coded data based on the prediction filter coefficients. A decoding means for decompressing and decoding the compression-encoded data read from the means, wherein the contents of the decoding register match each time at the beginning of repeated reading.