JPH0738108B2 - Musical tone control method for electronic musical instruments - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION (a) Field of Industrial Application The present invention relates to a musical tone control method for an electronic musical instrument that electronically generates musical tones.

(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, the operating unit is 4 to 7.5.
Equipped with an octave keyboard (each key corresponds to a pitch for each semitone (C, C #, D, E ♭ ...)), a key-on sensor that detects the on / off state of each key, keystrokes An initial touch sensor for detecting strength (initial touch), an after-touch sensor for detecting 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 controlling the tone generator section to generate sound with this musical tone control parameter, it is possible to generate musical tones with rich facial expressions. In an electronic musical instrument having such a structure, it is sometimes required to enhance the performance effect and give a delicate expression to the musical tone. In such a case, one musical tone control parameter can be controlled by a plurality of musical performance information. It has been done conventionally. For example, vibrato control is performed based on aftertouch, key-on time, etc., pitch control is performed based on initial touch, aftertouch, etc., level control is initial touch, aftertouch, key-on time, foot controller, breath It is performed based on various performance information (operation of the operation unit) such as a controller.

(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, a control amount is individually calculated from each performance information, and these control values are controlled. One tone control parameter is determined by adding or multiplying the amount, and in such a parameter determination method, it is necessary to individually obtain the control amount for each performance information, so that control takes time and the pronunciation is delayed. In addition, even if the sum (or product) of the obtained multiple control amounts becomes extremely large, it cannot be suppressed, and control is performed more than necessary, and there is a risk that it will not be desirable as a musical sound. was there.

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 musical tone control parameters corresponding to a plurality of performance information. To do.

(D) Means for Solving the Problem The present invention is directed to at least two first and second performance information (initial touch, after touch, key-on time,
A tone control parameter (pitch parameter, vibrato parameter, fluctuation parameter, level parameter, etc.) that changes according to the value of the key number, etc. is formed by using fuzzy inference. The first function relating to the first rule indicating the changing manner of the tone control parameter according to the second function, and the second function relating to the second rule indicating the changing manner of the tone control parameter according to the change in the value of the second performance information. Function (for example, in the case of FIG. 2 (A), the parts 101 and 108, the parts 102, 103 and 109, and the part 110), and the input values of the first and second performance information. According to the above, the fuzzy inference processing is performed based on the first and second functions to form the tone control parameters (FIG. 2 (A)).
In the case of, 111,104,112,106,107,113,114,115)) is performed.

(E) Action In the musical tone control method for an electronic musical instrument of the present invention, performance information (initial touch, after touch,
Various tone control parameters are determined by referring to key on time, etc.

Here, the fuzzy inference is performed with respect to "how to set the musical tone control parameter based on various performance information", and a plurality of fuzzy rules for this are defined. Fuzzy rules are generally expressed in the form of if (x = A, y = B, ...) Then (u = R). In the present invention, in order to provide the electronic musical instrument with the required operating characteristic, the preferable operating characteristic represented by the above rule is used. For example, if the initial touch (x) is large (A) and the aftertouch (y) is large (B), the pitch (u) is greatly increased (R). "If the initial touch (x) is small (A) and the aftertouch (y) is small (B), the pitch (u) is lowered slightly (R). "When the initial touch (x) is large (A), the aftertouch (y) is small (B), and the key-on time (z) is long (C), the pitch (u) is not changed (R). [If the aftertouch (x) is large (A) and the key-on time (y) is long (B), a large vibrato (u) is added (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 off-tertouch (y) is small (B), and the key-on time (z) is short (C), the reverb (u) is not added (R). "If the initial touch (x) is large (A) and the after touch (y) is large (B), the level (u) is increased (R). "If the initial touch (x) is small (A) and the after touch (y) is small (B), the level (u) is reduced (R). "If the initial touch (x) is large (A), the aftertouch (y) is large (B), and the key-on time (z) is short (C), the level (u) is made extremely large (R). ] Etc.

Here, a general fuzzy reasoning 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 conditional part is the smallest of the obtained membership values (α _x , β _x ). Conclusion section (“then”
The membership function of the following proposition) is a function for outputting the conclusion of this rule, and is output as a value having a spread in the controlled variable direction (u-axis direction) that is limited (truncated) by the output value of the conditional part. It is something. 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 musical tone control parameter corresponding to the change in 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 (refer to the part of rule 1 in FIG. 7) is prepared, and each output as a conditional part corresponding to the value of each performance information input using each function is Desired. Then, the output corresponding to the value of each performance information based on each function (rule) is used to execute the process corresponding to the above-mentioned conclusion part to correspond to the value of the first and second performance information. A tone control parameter is formed.

By determining the musical tone control parameter using such fuzzy inference, it is possible to perform delicate musical tone control with a simple structure in consideration of a plurality of performance information. Even in this case, the processing speed does not decrease. Furthermore, by changing various fuzzy rules and membership functions, each musical instrument can be easily given its own character.

(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 various musical tone control parameters can be determined based on the keyboard operation.

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 signal (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 tone control parameter inference circuit 5 and the synthesizer 7, and the key-on time signal (KON) is the tone generator circuit 8.
And the key-on time signal (KONT) are input to the envelope generator 9 and the tone control parameter inference circuit 5. An initial touch intensity signal and an after touch intensity signal are also input to the tone control parameter inference circuit 5, tone generator circuit 8, and envelope generator 9. The tone control parameter inference circuit 5 outputs tone control parameters to the signal generation circuit 6, and the signal generation circuit 6 outputs the pitch and level control values to the synthesizer 7 and the envelope generator 9 every moment. The tone control parameter inference circuit 5 infers what the pitch, vibrato, fluctuation, and level should be based on the input signal, and outputs each control parameter to the signal generation circuit 6. The signal generation circuit generates a frequency displacement signal (CS ₁ ) and a level displacement signal (CS ₂ ) from these parameters every moment 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 this frequency signal into a digital value representing a frequency) and modulating this frequency signal with the frequency displacement signal (CS ₁ ). The frequency signals thus modulated are accumulated at a predetermined timing, and the tone generator circuit 8 stores the phase information as phase information.
Entered in. The tone generator circuit 8 generates a digital (quantized) signal representing a predetermined waveform (timbre) based on this phase information and inputs it to the multiplication circuit 10. An envelope generator 9 is connected to the multiplication circuit 10. The envelope generator 9 generates a basic envelope signal having a level waveform such as rising and decay based on an initial touch signal, an after touch signal, a key-on time, etc.,
The level displacement signal CS ₂ input from the signal generating circuit 6 is superimposed on this basic envelope signal to generate an envelope signal. This envelope signal is input to the multiplication circuit 10. In the multiplication circuit 10, the digital signal is amplitude-modulated by the envelope signal input from the envelope generator 9, and an envelope (level displacement) of a musical tone is applied. The enveloped digital tone signal is
It 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 to 2D are detailed block diagrams of the tone control parameter inference circuit 5. FIG. 2A is a pitch parameter inference circuit, FIG. 2B is a vibrato parameter inference circuit, and FIG. (C) shows a fluctuation parameter inference circuit, and (D) shows a level parameter inference circuit. These circuits are composed of fuzzy inference circuits. Also, the third
Figures (A) to (D) are diagrams showing membership functions of the condition part used in the tone control parameter inference circuit, and Figures 4 (A) to (D) are pitch parameter inference circuits, respectively.
It is a figure which shows the membership function of the conclusion part of a vibrato parameter inference circuit, a fluctuation parameter inference circuit, and a level parameter inference circuit.

In the pitch parameter inference circuit, "if" Aftertouch is not small (AT ₂ ) "then" Pitch is lowered a little (PN) "" (1) "if" Initial touch is not small (IT ₃ ) "and" Immediately after key-on (KO ₁ ) "then" raise pitch a little (P
P) ”” (2) “if“ Aftertouch is not small (IT ₃ ) ”nor“ 'Initial touch is not small (AT ₂ )' and 'Immediately after key-on (KO ₁ )' ”then” Change pitch Not (PZ) ”” ……
Inference (3) is performed.

In the vibrato parameter inference circuit, "if" Aftertouch is not small (AT ₂ ) "then" Vibrato is increased (VL) "... (4)" if "Key on time is long (KO ₃ )" then "Vibrato" (VS) ”………… (5)“ if “The initial touch is very small (IT ₁ ), immediately after the key-on time (KO ₁ ) '” or “the key-on time is not long (K
O ₃ ), aftertouch is small (AT ₂ ), “then“ do not apply vibrato (VZ) ”” ... (6) The inference is made.

In the fluctuation parameter inference circuit, "if"'key number is large (pitch is high: KN)' or 'initial touch is not small (IT ₃ )'"then" fluctuation is increased (YL) "" (7 ) 'If “' Key number is small (pitch is low: KN) 'and
The reason is as follows: 'Initial touch is small (IT ₃ )'"Then" Slight fluctuation (YS) "" (8).

In the level parameter inference circuit, "if"'small initial touch (IT ₂ )' and 'small aftertouch (AT ₁ )'"then" reduce level (LS) "" ... (9) "if""Initial touch is normal (IT ₄ )" and "After touch is normal (AT ₃ )""then" Level is not changed (L
N) ”” (10) “if“ 'Initial touch is large (IT ₅ )' and 'Key-on time is not extremely long (KO ₂ )' ”and“ Aftertouch is large (AT ₄ ) “then” Increase level (L
L) ”” ... (11) is inferred.

Pitch parameters, vibrato parameters, fluctuation parameters, and level parameters are determined based on these inference results.

3 (A) to 3 (D), the initial touch is “very weak (IT ₁ )” and “weak (IT ₂ )” in FIG. 3 (A).
"Not weak (IT ₃ )""Normal (IT ₄ )""Strong (IT ₅ )"
The membership function of after-touch is shown in Fig. 2B as "weak (AT ₁ )", "not weak (AT ₂ )", "normal (AT ₃ )", and "strong (AT ₄ )". In the same figure (C), the membership functions of the key-on time “very short (immediately after key-on: KO ₁ )”, “not extremely long (KO ₂ )”, and “not short (KO ₃ )” are shown. FIG. 6D shows a membership function of “large key number (KN)”. In addition, in FIG. 4 (A) to (D)
PN, PZ, PP are membership functions corresponding to the conclusions of "pitch slightly lower", "pitch not changed", and "pitch slightly increased". VL, VS, VZ are "vibrato" and "vibrato". Is a membership function that corresponds to "apply small" and "do not apply vibrato".
YL, YS are the membership functions corresponding to "large fluctuation" and "small fluctuation". LS, LN, LL
Is a membership function corresponding to "decrease the level", "do not change the level", and "increase the level".

Since the fuzzy rule is executed by using the membership function as described above, the circuits shown in FIGS. 2A to 2D are configured.

The configuration of the pitch parameter inference circuit will be described with reference to FIG. Membership function generator (MFC: Memb
ership Function Cercuit) 101-103 is AT ₂ , I in the conditional part
A circuit that generates the membership function of T ₃ , KO ₁ ,
The aftertouch strength signal, the initial touch strength signal, and the key-on time signal are respectively received and the corresponding membership value is obtained. Membership function generator
108 to 110 are circuits that generate membership functions of PN, PP and PZ in the conclusion part. Further, the minimum circuits 111 to 113 are circuits for inferring the conclusions of the fuzzy rules of (1) to (3), respectively. The minimum circuit 111 accepts the membership values and membership functions of the membership function generation circuits 101 (conditional part) and 108 (conclusion part) and infers the conclusion of the fuzzy rule (1). Membership values for membership functions 102 and 103 are minimum circuits 10
It is input to 4 and the logical product (minimum value) is calculated, and this is the value of the conditional part of the fuzzy rule (2) and the minimum circuit 11
Entered in 2. The membership function (PP) of the membership function generating circuit 109 is input to the minimum circuit 112, and the conclusion of the fuzzy rule (2) is inferred. Also,
Membership function generator 101 and minimum circuit 104
The output of is logically ORed in the maximum circuit 106 (the maximum value is obtained), and subtracted from "1" in the subtractor 109 (the complementary set is obtained). This value is input to the minimum circuit 113 as the value of the condition part of the fuzzy rule (3). The membership function (PZ) of the membership function generating circuit 110 is input to the minimum circuit 113, and the conclusion of the fuzzy rule (3) is inferred. The three conclusions inferred by the minimum circuits 111 to 113 are ORed together by the maximum circuit 114 and the area is obtained. The obtained logical sum figure and area are input to the centroid calculation circuit 115, and the centroid calculation circuit 115 obtains the centroid. The numerical value of this center of gravity position becomes the pitch parameter.

The configuration of the vibrato parameter inference circuit will be described with reference to FIG. Membership function generators 121-124
Is a circuit that generates a membership function of AT ₂ , KO ₃ , KO ₁ , and IT _{1 in} the conditional part.
The key-on time signal and the initial touch strength signal are accepted and the corresponding membership value is obtained. The membership function generating circuits 130 to 132 are circuits that generate the membership functions of VL, VS, VZ in the conclusion part. The minimum circuits 133 to 135 are circuits for inferring the conclusions of the fuzzy rules of (4) to (6), respectively. Minimum circuit 13
3 is a membership function generating circuit 121 (conditional part) and 13
Accept the membership value and membership function of 0 (conclusion part) to infer the conclusion of fuzzy rule (4). The minimum circuit 134 is the membership function generating circuit 122.
(Condition part) and 131 (conclusion part) are accepted and the conclusion of the fuzzy rule (5) is inferred. Further, the membership values of the membership function generating circuits 121 and 122 are input to the maximum circuit 125 and the maximum value is obtained. This maximum value is subtracted from "1" in the adder 126 and then input to the maximum circuit 129. Further, the membership values of the membership function generating circuits 123 and 124 are input to the minimum circuit 128 to obtain the minimum value. This minimum value is input to the maximum circuit 129. The output of the maximum circuit 129 becomes the output of the condition part of the fuzzy rule (6). The output of the condition part and the membership function generated by the membership function generation circuit 132 are input to the minimum circuit 135, and the conclusion of the fuzzy rule (6) is inferred. Minimum circuit 133
The three conclusions inferred in .about.135 are ORed in the maximum circuit 136 and the area is obtained. The obtained logical sum figure and area are input to the centroid calculation circuit 137, 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 141 and 142 are circuits that generate the membership functions of KN and IT _{3 in} the conditional part, and each accepts a key number (which can be obtained from the key code) and an initial touch strength signal, and a corresponding membership value. Ask for. The membership function generating circuits 146 and 147 are circuits that generate the membership functions of YL and YS in the conclusion part. Also, the minimum circuit 148,149
Are circuits for inferring the conclusions of the fuzzy rules (7) and (8), respectively. The membership values of the membership functions 141 and 142 are input to the maximum circuit 143 and the maximum value thereof is obtained. This maximum value becomes the condition part output of the fuzzy rule (7) and is input to the minimum circuit 148. The membership function of the membership function generation circuit 146 is also input to the minimum circuit 148 to infer the conclusion of the fuzzy rule (7). The output of the maximum circuit 143 is subtracted from the "1" generated by the "1" signal generation circuit 144 in the adder 145. This value is input to the minimum circuit 149. The membership function of the membership function generating circuit 147 is also input to the minimum circuit 149 to infer the conclusion of the fuzzy rule (8). The two conclusions inferred by the minimum circuits 148, 149 are ORed together by the maximum circuit 150 and the area is obtained. The obtained logical sum figure and area are input to the centroid calculation circuit 151, and the centroid is obtained. This center of gravity becomes the fluctuation parameter.

The configuration of the level parameter inference circuit will be described with reference to FIG. Membership function generator circuit 161 to 167 is a circuit for generating the _{IT 2, AT 1, IT 4} , AT 3, IT 5, AT 4, KO membership functions of the condition part, after touch intensity signals, respectively, initial touch It accepts the strength signal and the key-on time signal and outputs the corresponding membership value.
Membership function generators 171-173 are LS, LN,
This is the circuit that generates the LL membership function. Also,
The minimum circuits 168 and 169 and the arithmetic circuit 170 are circuits for inferring the conclusions of the fuzzy rules (9) to (11). The minimum circuit 168 receives the membership values and membership functions of the membership function generating circuits 161, 162 (conditional part) and 171 (conclusion part) and infers the conclusion of the fuzzy rule (9). Minimum circuit 16
9 receives the membership values and membership functions of the membership function generating circuits 163, 164 (conditional part) and 172 (conclusion part) to infer the conclusion of the fuzzy rule (10). Further, the arithmetic circuit 170 receives the membership values of the membership function generating circuits 165 (IT ₅ ), 166 (AT ₄ ), 167 (KO) and the membership function (LL) of the membership function generating circuit 173, and outputs the IT ₅ And KO ₂ are multiplied, and the minimum value of this multiplication value and AT ₄ is used as the output of the conditional part to cut off LL and infer the conclusion of the fuzzy rule (11). The three conclusions inferred by the minimum circuits 168, 169 and the arithmetic circuit 170 are logically ORed by the maximum circuit 174 and the area is obtained. The obtained logical sum figure and area are input to the centroid calculation circuit 175, and the centroid is obtained. This center of gravity becomes the level parameter.

The parameters obtained by the above circuits are input to the signal generating circuit 6 and are calculated by the signal generating circuit 6 as the frequency displacement amount and the volume displacement amount. 5 (A) to 5 (F) show examples of tone control by key operation. In the same figure (A), initial touch,
The intensity of after-touch is shown, and the control amounts by the parameters output by this key touch are shown in FIGS. (B) shows the pitch control amount by the pitch parameter, (C) shows the fluctuation (frequency) control amount by the fluctuation parameter, and (D) shows the frequency (volume) control amount by the vibrato parameter. FIG. 6F shows the volume control amount by the level parameter. FIG. 6E is a graph showing the total frequency control amount obtained by combining the control amounts by the pitch parameter, the uragi parameter, and the vibrato parameter.

In this example, the keys are slightly strongly pressed (initial touch), and then gradually strongly pressed (aftertouch). By performing such a key touch, the pitch control is performed so as to keep the target frequency from a little higher than the beginning, the fluctuation control is performed so as to slightly fluctuate at the start of the musical sound, and the vibrato control is gradually performed from the middle. It is done so that it takes a lot of time. In addition, the level control is performed such that the level is first largely decreased and then gradually increased again. As a result, frequency control is performed as shown in FIG. Further, the volume control may be performed by directly using the level control amount shown in FIG. 6F as the control amount, or by adding the vibrato control amount to this.

Other than this example, various characteristics can be obtained by variously changing the fuzzy rules and membership functions, and it is easy to change the so-called personality of the musical instrument to a favorite one.

It may be configured by a discrete circuit of each processing unit of the tone control parameter inference circuit 5 or a circuit using a microcomputer. Fig. 6 (A)
(E) shows a flow chart when the minimum circuit, the maximum circuit, and the center of gravity calculation circuit are configured by a microcomputer.

FIGS. 9A and 9B are flow charts for executing the operations of the maximum circuit (106 etc.) and the minimum circuit (104 etc.). 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), sc
If l ₂ is large, write scl ₂ to memory scl ₀ (n
3). In the same figure (B), two scalar quantities (s
cl _1, scl ₂₎ compares reads (n4), writes the scl ₁ in the memory scl ₀ if scl ₁ is small (n5), if scl ₂ is small writes scl ₂ in memory scl ₀ ( n6).

FIG. 7C is a flow chart for executing the operation of the niimum circuit (111 to 113 etc.). First, i representing the value on the horizontal axis of the membership function is set to 0 at n7. This i
When the value of becomes equal to or larger than the size (size) of the horizontal axis of the membership function, the operation is terminated 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 (114 etc.).
First, at n15, the horizontal axis value i and the area integration memory acc are set to 0. When the value of i exceeds the size (size) of the membership function on the horizontal axis, the operation is terminated by the judgment of n16. n17
Then, the conclusion function values (mem1 (i), mem2 (i), mem3 (i)) of the three (or two) fuzzy rules in i are read out, and the maximum one is judged by n18.

If mem1 (i) is the maximum, mem1 (i) is buffered (bu
Write to f) (n19), mem2 if mem2 (i) is maximum
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.

FIG. 6E is a flowchart for executing the center-of-gravity calculation operation of the center-of-gravity calculation circuit (115, etc.). First, the same figure (D)
Half the value of the area (acc) found in
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 ends. When (hac) is less than (half), 1 is added to j (n30). Return to n27.

In the above embodiments, the electronic musical instrument played in real time was jealous, but the same control can be performed by an apparatus 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, fuzzy inference is used to determine the musical tone control parameters, so that a plurality of performance information can be combined in a simple circuit configuration. It is possible to determine the musical tone control parameter in consideration. As a result, delicate musical tone 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 changing various fuzzy rules and membership functions, and it becomes easy to give different characteristics to each musical instrument.

[Brief description of drawings]

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, and FIGS. 2A to 2D are block diagrams of a musical tone control parameter inference circuit of the electronic musical instrument.
3 (A) to (D) are diagrams showing membership functions used in the condition part of the same tone control parameter inference circuit, and FIGS. 4 (A) to (D) are conclusion parts of the same tone control parameter inference circuit. Diagram showing membership functions used in
FIGS. 6A to 6F are diagrams showing examples of frequency control amount and volume control amount associated with keyboard operation of the electronic musical instrument, and FIGS.
(E) is a flow chart showing the operation when each arithmetic unit of the musical tone control parameter inference circuit is constituted by a microcomputer. FIG. 7 is a diagram for explaining a general fuzzy reasoning method. 1 ... keyboard, 2 ... key-on detection circuit, 3 ... initial touch detection circuit, 4 ... after-touch detection circuit, 5
...... Music control parameter inference circuit.

Claims (1)

[Claims] 1. Forming a musical tone control parameter that changes according to the values of at least two first and second performance information,
A musical tone control method for an electronic musical instrument for performing musical tone control by means of this musical tone control parameter, comprising: a first function relating to a first rule indicating a change mode of the musical tone control parameter according to a change in the value of the first performance information. And a second function relating to a second rule indicating a change mode of the musical tone control parameter according to a change in the value of the second performance information, and input values of the first and second performance information. A musical tone control method for an electronic musical instrument, characterized in that fuzzy inference processing is performed based on the first and second functions to form the musical tone control parameters.