JPH0789278B2 - Musical tone control method for electronic musical instruments - Google Patents

Description

The present invention relates to a musical tone control method for an electric musical instrument that electronically produces musical tones, and more particularly to a method for controlling effects such as vibrato.

(B) Conventional Techniques Various electronic musical instruments that electronically generate musical tones are currently in practical use, and a conventional keyboard (keyboard) has been used.
In addition to molds, wind instruments and strings (guitars) are also in practical use. These electronic musical instruments have various operating parts (key switches and the like), and when these operating parts are operated (played), musical information generated by controlling performance information is controlled. For example, in the case of a keyboard type electronic musical instrument, 5 to 7.5
Equipped with an octave keyboard (each key corresponds to a pitch (C, C, D, E ...) for each semitone), each key has a key-on sensor that detects whether the key is on or off, keystroke strength ( An initial touch sensor for detecting an initial touch, an after touch sensor for detecting a key pressing strength (after touch) during key-on, and the like are provided. In addition to this keyboard, it also has a pedal and a wheel type operation unit. On the other hand, in the case of a wind instrument type electronic musical instrument, a key system and a mouthpiece similar to a woodwind instrument are provided as an operation unit, and a sensor for detecting the operation state of each key, a breath sensor for detecting the strength of breath to be blown, and a lead are provided. It has a lip sensor and the like for detecting the applied pressure. Based on the performance information obtained from such an operation unit, pitch, pitch (small frequency within the same pitch), level (volume),
By determining various musical tone control parameters such as waveforms and additional effects (vibrato, etc.) and causing the sound source section to generate sound with these musical tone control parameters, musical tones with rich facial expressions can be generated. In an electronic musical instrument having such a structure, it is sometimes required to enhance the performance effect and give a delicate expression to a musical sound. In such a case, it has been a conventional practice to control one musical sound control parameter with a plurality of musical performance information. Is done more.

(C) Problem to be Solved by the Invention However, in the conventional electronic musical instrument, when one musical tone control parameter is determined based on a plurality of performance information, the control amount is individually set based on each performance information. The tone control parameters have been determined by adding them or multiplying them. For example, additional effects of musical tones such as vibrato (periodic change of musical tone pitch (frequency)), tremolo (periodic change of musical tone level), reverb (reverberation after key-off) further enhance the expressiveness of musical tone. Therefore, the effect parameters that determine the extent of these effects are often used during performance, but are determined based on performance information such as aftertouch, breath, pitch bend wheel, and key-on time. Conventionally, this effect parameter is determined by individually determining the control amount from each of the performance information (the above-mentioned aftertouch, the operation amount of the pitch bend wheel, the key-on time, etc.) obtained from the operation section set to control the effect. It was done by adding or multiplying.

However, when trying to control the effect in a complicated manner by using a lot of performance information, the parameter determination method as described above requires the control amount to be individually calculated for each performance information, and thus the control takes time and the sound is delayed. In addition to its drawbacks, even if the sum (or product) of the required multiple control amounts becomes extremely large, it cannot be suppressed, and effects such as vibrato are applied more than necessary, which is preferable as a musical sound. There was a risk of disappearing.

Further, when an electronic musical instrument is used to express a nuance close to that of a natural musical instrument, it is necessary to compositely calculate various performance information to control a musical tone. When attempting to perform program processing using a general algorithm, there is a drawback that the calculation takes time and is not practical. In addition, if the speed of the arithmetic unit is increased to compensate for this, there is a drawback that the size and cost are increased.

The present invention has been made in view of the above-mentioned conventional drawbacks, and an object thereof is to provide a musical tone control method for an electronic musical instrument capable of easily and rapidly forming effect control parameters corresponding to a plurality of performance information. To do.

(D) Means for Solving the Problems The present invention forms an effect control parameter that changes according to the values of at least two first and second performance information,
A tone control method for an electronic musical instrument, which controls an effect imparted to a tone by this effect control parameter, comprising: a first mode showing a change mode of the effect control parameter according to a change in a value of the first performance information. The first function related to the rule and the second function related to the second rule indicating the change mode of the effect control parameter according to the change in the value of the second performance information are prepared, and the first and second input The effect control parameter is formed by performing fuzzy inference processing based on the first and second functions according to the value of the performance information of No. 2.

(E) Action In the musical tone control method for an electronic musical instrument of the present invention, performance information (key-on time, aftertouch intensity,
The effect control parameter is controlled by referring to the wheel operation amount and the like).

Here, fuzzy inference is performed regarding "how much effect should be applied based on various performance information". Therefore, multiple fuzzy rules are defined. Fuzzy rules are generally expressed in the form of if (x = A, y = B, ...) Then (u = R). In the present invention, for example, if the aftertouch (x) is large (A) and the key-on time (y) is long (B), the vibrato (u) is increased (R). "If the initial touch (x) is small (A) and the key-on time (y) is long (B), the reverb (u) is lengthened (R). "If the initial touch (x) is large (A), the aftertouch (y) is small (B), and the key-on time (z) is short (C), the reverb (u) is not added (R). ] And other rules are constructed.

Here, a general fuzzy inference method will be described with reference to FIG. This method is called mini / max rule. In this example, two fuzzy rules “if (x = A ₁ )
then (u = R ₁ ), if (x = A ₂ , y = B ₂ ) then (u = R ₂ ) ”
Explain the reasoning based on. Each proposition (x = A ₁ , x =
A ₂ , y ＝ B ₂ , u ＝ R ₁ , u ＝ R ₂ ) is expressed by the membership function. The membership function of the conditional part (proposition below "if") shows how much the input variable value (x ₀ , y ₀ ) belongs to the given fuzzy set (A ₁ , A ₂ , B ₂ ). This is a function for obtaining the function values (membership values: α _x , β _x , β _y ), and the output of the condition part is the smallest one of the obtained membership values (α _x , β _x ). The membership function of the conclusion part (proposition below "then") is a function for outputting the conclusion of this rule, and spreads in the control amount direction (u-axis direction) limited (cut off) by the output value of the condition part. Is output as a value with. The final controlled variable (u ₀ ) is the value of the center of gravity obtained by logically adding the conclusions of a plurality of fuzzy rules.

In the present invention, as a function of the above-mentioned condition part, the first rule relating to the first rule indicating the change mode of the effect control parameter corresponding to the change of the value of the performance information corresponding to the first and second performance information, respectively. A second function relating to the function and the second rule is prepared, and each output is obtained as a conditional part corresponding to the value of each performance information input using each function. Then, the output corresponding to the value of each performance information based on each function is used to execute the process corresponding to the above-mentioned conclusion part, so that the effect control parameter corresponding to the value of the first and second performance information. Is formed.

By using such fuzzy inference for effect control, it is possible to easily perform inference processing that considers a plurality of performance information in a complex manner, and thus it is possible to perform delicate effect control with a simple circuit configuration. Even in this case, the processing speed does not decrease. Furthermore, by changing various fuzzy rules and membership functions, it is possible to easily impart unique effect characteristics to each musical instrument.

(F) Embodiment FIG. 1 is a block diagram of an electronic musical instrument in which a musical tone control method according to an embodiment of the present invention is used. This electronic musical instrument is a keyboard type, and can perform vibrato control and pitch fluctuation control during sound generation based on keyboard operation. Here, the vibrato is a periodic upper and lower sides of the tone frequency (pitch) as shown in FIG. 7 (A), and is an effect of giving the tone a softness. Further, the fluctuation means an unstable state of the pitch immediately after the pronunciation as shown in FIG. 7B, which is an effect of simulating the characteristic of the natural musical instrument.

The keyboard 1 has keys corresponding to a plurality of pitches. Each key is provided with a key-on sensor for detecting ON / OFF of the key, an initial touch sensor for detecting initial touch strength (speed), and an after-touch sensor for detecting after-touch strength. The initial touch sensor turns on continuously with the key-on operation 2
It is composed of individual photosensors, and the photosensor which is turned on later also serves as a key-on sensor. The states of these sensors are detected by the key-on detection circuit 2, the initial touch detection circuit 3, and the after-touch detection circuit 4. Key-on detection circuit 2 is always keyboard 1 (photo sensor)
The key is scanned to monitor the on / off state of each key. When there is a key on, the key code (code representing pitch: KC), key on signal (KON) and key on time (KONT) are output. When the key is turned on, the initial touch detection circuit 3 detects and outputs the strength of keystroke of the key. The aftertouch detection circuit 4 also detects and outputs the pressing strength of the key that is turned on. The key code (KC) is input to the synthesizer 7, the key-on signal (KON) is input to the tone generator circuit 8 and the envelope generator 9, and the key-on time signal (KONT) is input to the effect parameter inference circuit 5. The initial touch intensity signal and the after touch intensity signal are also input to the effect parameter inference circuit 5, the tone generator circuit 8, and the envelope generator 9. The effect parameter inference circuit 5 is connected to the synthesizer 7 and the envelope generator 9 via the signal generating circuit 6. The effect parameter inference circuit 5 infers the effect (vibrato, fluctuation) control amount based on the input signal and outputs it to the signal generation circuit 6. The signal generation circuit generates displacement waveform signals (CS ₁ , CS ₂ ) from this effect control amount and synthesizes them respectively.
7, output to envelope generator 9. The synthesizer 7 converts the input key code (KC) into a frequency signal (F number:
It is a circuit for converting the frequency signal into a digital value representing a frequency and modulating the frequency signal with the displacement waveform signal (CS). The frequency signals of the musical tones thus determined are accumulated at a predetermined timing and input to the tone generator circuit 8. The tone generator circuit 8 generates a digital signal representing a predetermined waveform (timbre) with this accumulated value and inputs it to the multiplication circuit 10. Multiplier circuit 10
Is connected to an envelope generator 9, and the digital signal is amplitude-modulated by the envelope signal generated by the envelope generator 9. The envelope generator 9 rises based on the initial touch signal, the after touch signal, the key-on time, etc.
A basic envelope signal having a level waveform such as attenuation is generated, and the level displacement waveform signal CS ₂ input from the signal generating circuit 6 is superimposed on the basic envelope signal to multiply the multiplier circuit 1
Generate an envelope signal to output to 0. The enveloped digital tone signal is input to the D / A conversion circuit 11. The D / A conversion circuit 11 samples / holds a digital musical tone signal and converts it into an analog musical tone signal. The analog tone signal is input to the amplifier 12.

2A and 2B are detailed block diagrams of the effect parameter inference circuit 5. The figure (A) is a vibrato parameter inference circuit, and the figure (B) is a fluctuation parameter inference circuit. These circuits are composed of fuzzy inference circuits. The fuzzy inference performed in these circuits is "if" Large aftertouch "" then "uses a large amount of vibrato""...(1)" if "long key-on time" then "uses a small amount of vibrato""... ( 2) “If“ 'Initial touch is small'and' Immediately after key-on '”or“ Key-on time is not long ”“ and After-touch is not small ”then“ No vibrato ”” ……
(3) And "if"'key number is large (pitch is high)' or 'initial touch is large'"then" fluctuation is greatly applied "" (4) "if"'key number is small (pitch is Is low) 'and' Initial touch is not large '"then" small fluctuation "" (5). The pitch fluctuation amount is determined by combining these inference results. FIGS. 3 (A) to (G) show the membership function of each proposition making up this rule. Where AT, IT ₁ , K
O ₁ , KO ₂ and KN, IT ₂ are “large aftertouch”, “small initial touch”, “immediately after key-on”
It is a membership function that represents a fuzzy set (conditional part) of "long key-on time", "large key number", and "large initial touch". Also, VL, VS, VZ and Y
L and YS are membership functions corresponding to the conclusions of "a large amount of vibrato", "a small amount of vibrato", "no vibrato", "a large amount of fluctuation", and "a small amount of fluctuation".

By executing the above fuzzy rule using such a membership function, pitch control as shown in FIGS. 4 (A) to 4 (D) can be performed. FIG. 6A shows the strength of initial touch and after touch. That is, the key with a certain key number was played so that the initial touch was strong and the aftertouch was gradually strong. By performing such a key touch, the fluctuation is greatly affected (FIG. (B)) and the vibrato is gradually increased (FIG. (C)). The change in the control amount synthesized by these effects is represented by the graph shown in FIG. By changing the fuzzy rules and membership functions variously, it is possible to obtain arbitrary vibrato and fluctuation characteristics other than the above example.

The configuration of the vibrato parameter inference circuit will be described with reference to FIG. Membership function generator (MFC:
Membership Function Cercuit) 101-104 is the AT of the conditional section,
This is a circuit that generates a membership function of KO ₁ , KO ₂ , IT ₁ and receives an aftertouch intensity signal, a key-on time signal, and an initial touch intensity signal, respectively, to obtain a corresponding membership value. The membership function generating circuits 110 to 112 are circuits that generate the membership functions of VL, VS, VZ in the conclusion part. Further, the minimum circuits 113 to 115 are circuits for inferring the conclusions of the fuzzy rules of (1) to (3), respectively. The minimum circuit 113 accepts the membership values and membership functions of the membership function generation circuits 101 (conditional part) and 110 (conclusion part) to infer the conclusion of the fuzzy rule (1). The minimum circuit 114 accepts the membership values and membership functions of the membership function generating circuits 102 (conditional part) and 111 (conclusion part) and infers the conclusion of the fuzzy rule (2). Also, membership function generation circuits 101 and 1
The membership value of 02 is input to the maximum circuit 104 to obtain the maximum value. This maximum value is subtracted from “1” in the adder 106 and then input to the maximum circuit 109. Further, the membership values of the membership function generating circuits 103 and 104 are input to the minimum circuit 108 to obtain the minimum value. This minimum value is input to the maximum circuit 109. The output of the maximum circuit 109 becomes the output of the condition part of the fuzzy rule (3). The output of the condition part and the membership function generated by the membership function generating circuit 112 are input to the minimum circuit 115 to infer the conclusion of the fuzzy rule (3). The three conclusions inferred by the minimum circuits 113 to 115 are maximum. The logical sum is obtained by the circuit 116 and the area is obtained. The obtained logical sum figure and area are input to the centroid calculation circuit 117, and the centroid is obtained. This center of gravity becomes the vibrato parameter.

The configuration of the fluctuation parameter inference circuit will be described with reference to FIG. Membership function generation circuits 121 and 122 are circuits that generate a membership function of KN and IT ₂ of the conditional part, and each accepts a key number (which can be obtained from a key code) and an initial touch strength signal to receive a corresponding membership value. Ask for. The membership function generation circuits 126 and 127 are circuits that generate the membership functions of YL and YS in the conclusion part. Also, the minimum circuit 128,129
Are circuits for inferring the conclusions of the fuzzy rules (4) and (5), respectively. The membership values of the membership functions 121 and 122 are input to the maximum circuit 123 and the maximum value thereof is obtained. This maximum value becomes the condition part output of the fuzzy rule (4) and is input to the minimum circuit 128. The membership function of the membership function generation circuit 126 is also input to the minimum circuit 128 to infer the conclusion of the fuzzy rule (4). Further, the output of the maximum circuit 123 is subtracted from "1" generated by the 1-signal generating circuit 124 in the adder 125. This value is input to the minimum circuit 129. The membership function of the membership function generating circuit 127 is also input to the minimum circuit 129 to infer the conclusion of the fuzzy rule (5). The two conclusions inferred by the minimum circuits 128 and 129 are logically ORed by the maximum circuit 130 and the area is obtained. The obtained logical sum figure and area are input to the centroid calculation circuit 131, and the centroid is obtained. This center of gravity becomes the fluctuation parameter.

The vibrato parameter and the fluctuation parameter are combined and output as the output of the effect parameter inference circuit 5.

The minimum circuit, the maximum circuit, the center of gravity calculating circuit, and the like can be composed of discrete circuits or a microcomputer. 5 (A) to 5 (E), the minimum circuit, the maximum circuit,
The flow chart when a gravity center calculation circuit is constituted by a microcomputer is shown.

9A and 9B are flow charts for executing the operations of the maximum circuits 105, 109, 123 and the minimum circuit 108. In FIG. (A), 2 pieces of scalar first (scl _1, scl ₂₎ compares reads (n1), writes the scl ₁ in the memory scl ₀ if scl ₁ is large (n2), scl ₂ If is larger, write scl ₂ to memory scl ₀ (n3). In the figure (B), first, two scalar quantities (scl ₁ , scl ₂ )
Read and compare (n4), and if scl ₁ is small, scl ₁
Write to memory scl ₀ (n5), if scl ₂ is small
Write scl ₂ to memory scl ₀ (n6).

FIG. 6C is a flow chart for executing the operation of the minimum circuits 113 to 115, 128, 129. First, i representing the value on the horizontal axis of the membership function is set to 0 at n7. When the value of i becomes equal to or larger than the size (size) of the membership function on the horizontal axis, the operation is ended by the judgment of n8. At n9, the value (mem (i)) at i of the membership function is read, and it is determined whether this value is less than or equal to the membership value scl of the condition part (n10). If mem (i) is less than or equal to scl, write the value of mem (i) to the buffer (buf) (n1
2) If mem (i) exceeds scl, write the value of scl to the buffer (buf) (n11). After writing the value of this buffer to the conclusion memory memo (i) corresponding to i (n1
3), add 1 to i and return to (n14) n8.

FIG. 6D is a flowchart for executing the logical sum and area calculation operation of the maximum circuit 116. First n1
At 5, the horizontal axis value i and the area integration memory acc are set to 0. The value of i is the size of the horizontal axis of the membership function (siz
When e) is exceeded, the operation ends with the judgment of n16. In n17, the conclusion function values (mem1 (i), mem2 (i), mem3 (i)) of the fuzzy rules (1), (2), and (3) in i are read, and the largest one is determined in n18. . mem1
If (i) is maximum, write mem1 (i) to the buffer (buf) (n19); if mem2 (i) is maximum, mem2
Write (i) to buffer (buf) (n20), mem3
If (i) is the maximum, mem3 (i) is written in the buffer (buf) (n21). At n22, the buffer value is written to mem0 (i) (n22), and the buffer value is added to the area integration memory acc (n23). After this, add 1 to i (n
24) Return to n16. Although the maximum circuit 130 has two conclusion function values (4) and (5) to be input, the same operation is performed by performing the operations of n17 and n18 with respect to these two function values. You can

FIG. 11E is a flowchart for executing the gravity center calculation operation of the gravity center calculation circuits 117 and 131. First, half the value of the area (acc) found in FIG.
It is stored in f) (n25). Next, 0 is set to j and the area integration area hac corresponding to the horizontal axis of the logical summed conclusion function (n26). Mem0 (j) is read to the buffer (buf) (n27), and this value is integrated in the area integration area hac (n2)
8). Compare the accumulated hac value with (half) (n29),
If (hac) is (half) or more, the value of j at that time is regarded as the center of gravity, and the operation is terminated.
When it is less than f), 1 is added to j and the process returns to (n30) and n27.

Although the effect control of vibrato and fluctuation has been described in the above embodiments, the same can be applied to other additional effects (reverb, tremolo, etc.). The same control is possible not only for an electronic musical instrument that is played in real time, but also for a device that stores performance information in advance and automatically performs.

(G) Effects of the Invention As described above, according to the musical tone control method for an electronic musical instrument of the present invention, by using fuzzy inference for effect control, an effect in which a plurality of performance information is considered in a complex manner with a simple circuit configuration Inference of the controlled variable becomes possible. As a result, delicate effect control can be easily executed at high speed, and delicate nuances can be added to the performance. Furthermore, the characteristics of the musical instrument can be easily changed by variously changing the fuzzy rule and the membership function, and the effect can be easily characterized for each musical instrument.

[Brief description of drawings]

FIG. 1 is a block diagram of an electronic musical instrument in which a musical sound effect control method according to an embodiment of the present invention is used, and FIGS. 2 (A) and 2 (B).
Is a block diagram of the effect parameter inference circuit of the electronic musical instrument,
3 (A) to (G) are diagrams showing membership functions used in the same effect parameter inference circuit, and FIG. 4 (A) to (G).
FIG. 5D is a diagram showing an example of frequency displacement associated with the keyboard operation of the electronic musical instrument, and FIGS. 5A to 5E show the operation when each operation unit of the effect parameter inference circuit is configured by a microcomputer. It is a flowchart shown. FIG. 6 is a diagram for explaining a general fuzzy inference method, and FIGS. 7A and 7B are diagrams showing pitch displacement due to a general vibrato effect and a fluctuation effect. 1 ... Keyboard, 2 ... Key-on detection circuit, 3 ... Initial touch detection circuit, 4 ... Aftertouch detection circuit, 5 ... Effect parameter inference circuit.

Claims (1)

[Claims] 1. An effect control parameter that changes depending on the values of at least two first and second performance information,
A tone control method for an electronic musical instrument, which controls an effect imparted to a tone by this effect control parameter, comprising: a first mode showing a change mode of the effect control parameter according to a change in a value of the first performance information. The first function related to the rule and the second function related to the second rule indicating the change mode of the effect control parameter according to the change in the value of the second performance information are prepared, and the first and second input 2. A musical tone control method for an electronic musical instrument, characterized in that the effect control parameter is formed by performing fuzzy inference processing based on the first and second functions according to the value of the performance information.