JP5347405B2 - Waveform generator and waveform generation processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a waveform generation device that generates a waveform by plotting in an attractor space. <P>SOLUTION: After Takens plotting from a source waveform is performed to display an attractor in the attractor space, plotting with a mouse is performed in the attractor space which remains after erasure of the attractor. The plotted figure is handled as an attractor and reverse conversion of the Takens plotting is performed using the same plotting condition to generate a two-dimensional waveform. <P>COPYRIGHT: (C)2010,JPO&amp;INPIT

Description

  The present invention relates to a waveform generator and a waveform generation processing program.

  Traditionally, when a musician creates a song, the first thing to think about is how to impress the listener with the image drawn in the head for each song. This work of creating a song is roughly divided into a work called “composition” for optimizing the melody and chords and a work called “timing determination” for optimizing the tone for playing the composed melody and chords. Of these, the “timbre determination” work generally involves searching for or creating a tone that matches the image that the musician wants to express. It has a particularly important role to impress. These timbres are obtained using a method in which the waveform of an existing musical instrument is stored in memory in advance, a method of synthesizing a waveform like a synthesizer, or a method of generating a waveform by calculating a vibration equation at high speed. It is possible.

  Among them, musicians generally use a synthesizer when creating new sounds. These have been performed by the work of repeatedly synthesizing the waveforms of an oscillator that generates a plurality of electrical vibrations. The method of synthesizing the waveform used musicians' trial and error and many years of experience, and the impression of the sound changed greatly depending on the quality of the synthesis method.

  In order to finally obtain the target tone in this work, the musician extracts "sound impression" which is one of the characteristics of sound, that is, "sound characteristics that remain in the human mind" There is a need to actively use this feature. However, the extraction of this “sound impression” has not been established as a general technique, and relies heavily on experience and sensitivity. Also, since waveform synthesis using a synthesizer takes a lot of time and effort, it is not easy to do this unless you are a highly skilled musician.

  In order to solve these problems, Patent Document 1 discloses a technique in which a timbre is determined from the color of a graphic drawn in two dimensions and new music is generated.

JP-A-6-318074

  However, in the method disclosed in Patent Document 1 in which the shape of the sound waveform is simply changed, sound and music are generated simply by drawing a picture in two dimensions. It only supports, but does not have a function to create sound. In particular, the extraction and holding of “sound impression” is not considered at all, so that a timbre that gives a “sound impression” to the listener cannot be provided, and the user is quickly bored. As described above, even when trying to provide a lot of music that can impress the listener with his / her image using the technique of Patent Document 1, a method of extracting “sound impression” necessary for the song has not been established. Therefore, there was a problem that new tones could not be created one after another.

  However, in recent years, by using a technique called “Turkens Plot” that seems to be similar to the information processing performed in the brain, a certain sound is embedded in an n-dimensional phase space and an attractor is generated. It has been found that this attractor represents an “impression of sound”. The reason can be understood by knowing the mechanism of the human brain.

  First, the human brain takes external stimuli as information, recognizes what it is (extracts features), and stores it. This recognition is not performed only with the input information, but is considered to be recognized with reference to information stored by stimuli received in the past. For example, when a scene seen in a movie overlaps with your past experience, you can remember a great impression. This is because when the brain recognizes a movie scene, it recognizes it with reference to the memory of the experience stored in the past, and if there is an experience with the same characteristics, it is recognized as a strong stimulus, so the impression is large it is conceivable that. Similarly, if you hear a sound you heard somewhere in the past again, you will feel familiar with it.

  In this brain recognition method, it is considered that not only those that are recognized by referring to a distant past memory, but also the past in a shorter time has a great influence. And it is thought that the sound, which is information related to hearing, is recognized against the sound immediately before for a shorter time.

For this reason, the task of selecting the current waveform based on the specified plot scale width in the Turkens plot is the same as the past information that is being used as a reference when recognizing the current information. It can be said that it is very similar to the work of For this reason, the work of drawing an attractor using a turn plot with a predetermined plot scale width and sampling frequency from the original waveform representing the sound is necessary for the brain to recognize the waveform. This is nothing but the work of extracting “impressions”. In other words, it can be said that the attractor displayed using the Turkens plot visually expresses the characteristic part of the sound “sound impression”. Hereinafter, a space in which the phase space used when the attractor is displayed and a predetermined plot condition used when the attractor is drawn is referred to as an attractor space. In addition, the attractor shows a pattern with a trajectory like a unique bundle that attracts subsequent data to the miracle, and each piece of data that creates this miracle is called attractor data. This attractor has a reversible correspondence that returns to the original waveform when the reverse conversion of the Turkens plot is performed using the same conditions as the plot conditions used for drawing. The plot conditions are valuable condition data for extracting the “sound impression” of the original waveform.
Here, when the user wants to create a new sound, the attractor obtained from the original waveform is used as it is, and after changing a part of this, the inverse conversion of the Turkens plot is performed. However, in this method, most of the attractor components obtained from the original waveform remain, and even if the inverse conversion of the Turkens plot is performed, the timbre of the original waveform can be generated. It is thought that the tone is very similar to Therefore, the inventor did not leave as much of the attractor component obtained from the original waveform as possible, but by reflecting the plot conditions, the timbre was innovative, and the impression of the sound was devised to give the same impression as the original waveform. Went.
That is, the attractor drawn from the original waveform by the Turkens plot is completely erased, and then the user draws the attractor data by the operator with respect to the attractor space where the plot condition is left.

  Then, it is possible to create audio data by returning the attractor data drawn in this attractor space to a two-dimensional waveform in the reverse order of the turnens plot using the same conditions as the plot conditions obtained earlier. This sound is completely different from the original waveform while providing the “sound impression” necessary for the brain to recognize the waveform.

  The present invention has been made in view of such circumstances, and the features of the source waveform are extracted as attractors on the nth-order phase space, and the attractor space expressed using the plot conditions obtained in the process, An object of the present invention is to provide a waveform generation apparatus and a waveform generation processing program capable of creating a new tone color waveform having a “sound impression” based on the plot conditions by drawing a new attractor.

In order to achieve the above object, the present invention provides a plurality of different plot conditions by combining a plurality of plot scales t and a resampling time Δt, respectively, and an input time axis based on each of the plurality of plot conditions. And by executing the Turkens plot process for embedding the original waveform data in the two-dimensional phase space having the peak value axis into the n (n> 2) dimensional phase space according to the Turkens embedding theorem, The n-dimensional phase space using coordinates as a coordinate and a plurality of attractor data generated by the turn plot processing means, a turn at plot processing means for sequentially generating attractor data, a basic attractor data storage means for storing basic attractor data Waveform represented above and basic attractor data storage means Correlation value extraction means for extracting a correlation value with the waveform represented on the n-dimensional phase space using the stored basic attractor data as coordinates, and the correlation value extracted by the correlation value extraction means is maximized; Extraction means for extracting a plot condition composed of a plot scale value t and a resampling time Δt, and attractor data for generating coordinates on the n-dimensional phase space of the waveform drawn on the n-dimensional phase space as new attractor data By performing the inverse transformation process of the Turkens plot process on the new attractor data generated by the generating means and the attractor data generating means using the plot conditions extracted by the plot condition extracting means, 2 Waveform generation processing means for generating waveform data in a dimensional phase space.

In the invention according to claim 2, the Turkens plot processing designates n sampling positions each having an interval of the plot scale value t on the time axis of the input original waveform data in the two-dimensional phase space. A step of determining an initial coordinate position by associating a peak value of each of the n sampling positions with a position on each axis in the n-dimensional phase space; and thereafter, simultaneously resetting the n sampling positions. and executes a step of generating attractors data by sequentially determining the coordinate position on the n-dimensional phase space by going only sequentially shifted on the time axis sampling time Delta] t.

According to a third aspect of the present invention, the waveform generation processing means sequentially reads the coordinate positions in the n-dimensional phase space constituting the new attractor data generated by the attractor data generation means from the end, and performs the read Each of the positions on the n axes representing the last coordinate position is the peak value of each of the n sampling positions designated at intervals of the plot scale value t on the time axis of the two-dimensional phase space. Then, every time the coordinate position is read, the n sampling positions are simultaneously shifted on the time axis by the resampling time Δt, and the read values are obtained as the peak values of the n sampling positions thus shifted. The operation of assigning each position on n axes representing the coordinate position is repeated.

In the invention described in claim 4 , a plurality of different plot conditions are prepared by combining a plurality of plot scales t and resampling times Δt in a computer having basic attractor data storage means for storing basic attractor data , Based on each of the plurality of plot conditions, the original waveform data in the two-dimensional phase space having the input time axis and peak value axis is embedded in the n (n> 2) dimensional phase space by the Turkens embedding theorem. The n-dimension using a turnens plot processing step for sequentially generating a plurality of types of attractor data by executing a turnens plot processing to be executed, and a plurality of types of attractor data generated by the turnens plot processing step as coordinates. The waveform represented on the phase space and the basic A correlation value extracting step for extracting a correlation value with the waveform represented on the n-dimensional phase space using the basic attractor data stored in the tractor data storage means as coordinates, and a correlation value extracted by the correlation value extraction step An extraction step for extracting a plot condition composed of a plot scale value t and a resampling time Δt that maximizes the value, and coordinates on the n-dimensional phase space of the waveform drawn on the n-dimensional phase space as new attractor data An attractor data generation step generated as follows, and the generated new attractor data is subjected to an inverse transformation process of the Turkens plot process using the extracted plot condition, thereby generating a two-dimensional phase space. And a waveform generation processing step for generating waveform data.

  According to the present invention, an attractor space in which sound features can be extracted as attractor features is created, a new attractor is drawn in the space by an arbitrary operation of the user, and the inverse of the turnens plot is performed based on the drawn waveform. By performing this conversion, a new two-dimensional waveform can be created.

Embodiments of the present invention will be described below with reference to the drawings.
A. Constitution
FIG. 1 is a block diagram showing a configuration of a waveform generator 100 according to an embodiment of the present invention. The waveform generating apparatus 100 shown in this figure includes an input unit 10, an operation unit 20, a display unit 30, a keyboard 40, a CPU 50, a ROM 60, a RAM 70, and a sound system 80. The input unit 10 includes an input terminal connected to a microphone and an external sound source, and an A / D converter, and outputs original waveform data obtained by sampling a waveform input from the outside under the control of the CPU 50. The original waveform data output from the input unit 10 is stored in the original waveform data area of the RAM 70.

  The operation unit 20 includes various switches arranged on the operation panel, and generates a switch event corresponding to a user's switch operation. The switch event output from the operation unit 20 is captured by the CPU 50 described later. The main switches arranged in the operation unit 20 include a power switch for turning on / off the apparatus power, a mode switch for selecting an operation mode, a tone color selection switch for selecting a tone color of a generated musical tone, an original waveform, and a regeneration described later. There are switches for selecting the waveform and phase space conditions. The operation unit 20 includes a mouse that performs known click operations and drag operations as a pointing device.

  The display unit 30 includes an LCD panel and a drive driver, and displays a setting state and an operation state of each unit of the device according to a display control signal supplied from a CPU 50 described later, and also displays a trajectory of attractor data described later. . The keyboard 40 generates performance information including key-on / key-off events, note numbers, velocities, and the like in response to key pressing / release operations.

  The CPU 50 controls each part of the apparatus according to the switch event supplied from the operation unit 20. Specifically, the processing operation according to the operation mode selected by operating the mode switch provided in the operation unit 20 is executed. The CPU 50 that has transitioned to the setting mode designates an operation mode of each part of the apparatus under each operation mode in accordance with a setting parameter input according to a user operation. The CPU 50 that has transitioned to the input mode instructs the input unit 10 to start waveform sampling, and stores the original waveform data captured from the input unit 10 in accordance with this instruction in the original waveform data area of the RAM 70.

  In addition, the CPU 50 that has transitioned to the waveform generation mode executes waveform generation processing (described later), and extracts attractor data and attractor space from the original waveform data stored in the original waveform data area (FIG. 2A) of the RAM 70. The number of points of the plot scale t and sampling time t and the number of points of data to be taken and other coordinate information are stored in the reproduction data area (FIG. 2B) of the RAM 70 together with the attractor space condition identification number. Then, leaving the condition and coordinate space for extracting the attractor, deleting the locus of this attractor, letting the user draw a new attractor waveform in that space, and new attractor data corresponding to each coordinate corresponding to this waveform Is generated. The attractor data generated here is written in the attractor data area shown in FIG. Further, the reverse conversion of the Taken-Slot is performed under the same conditions as the plot conditions for extracting the attractor using the newly generated attractor data, and the two-dimensional waveform is restored. Furthermore, the CPU 50 that has transitioned to the performance mode executes performance processing for generating musical tone data corresponding to the performance information supplied from the keyboard 40.

Various control programs are stored in the ROM 60. The various programs referred to here include a main routine and waveform generation processing described later. The waveform generation process includes a sequence / plot display process, an attractor drawing process, and a waveform regeneration process, which will be described later. The basic attractor data area, which stores attractor data that has already been discovered and is closely related to the natural world and that has the characteristics of famous attractors such as limit cycle, strange, torus, and Lorenz, Is stored more than once.
Further, attractor space data obtained from previously obtained experimental data and known to be effective for creating a new waveform is also stored in the same format as in FIG. 2B.

  The RAM 70 has a work area for temporarily storing various register / flag data, an original waveform data area (FIG. 2A) for storing original waveform data output from the input unit 10, and a sequence / plot display process (to be described later). ), The attractor data area (FIG. 3) for storing the attractor data obtained by subject plotting the original waveform data and the new attractor data generated by drawing, and the new attractor data drawn are regenerated. A regenerated waveform data area (FIG. 2B) for storing regenerated waveform data.

FIG. 2A is a diagram showing an original waveform in an original waveform data area in the RAM 70, and each peak value W (n) (n = 0 to N) is stored. FIG. 2B includes a regeneration waveform data portion for storing the generated waveform in the regeneration waveform data area in the RAM 70, and a regeneration condition data portion for storing the conditions at the time of reproduction.
The regenerated waveform data area portion has a structure similar to that of the original waveform data area, and each peak value NW (n) (n = 0 to N) is stored.
A plurality of original waveform data areas and reproduction waveform data areas are prepared, and a user can select a waveform required by operating a switch (not shown) as appropriate. For example, the user can select an original waveform having a “sound impression” as desired. Even if the original waveform is not selected, it is possible to directly select the attractor space identification number from the regenerated waveform data area and to draw the attractor space under this condition suddenly. In this case, it is possible to quickly create a new timbre without the need for a process / plot display process described later.
FIG. 3 is a diagram showing the contents of attractor data (described later) in the attractor data area of the RAM 70, and coordinates on the screen of the display unit 30 from n = 0 to N are written. Each coordinate consists of an x component, a y component, and a z component.

  Further, the sound system 80 in FIG. 1 performs amplification such as removing unnecessary noise from a musical sound signal obtained by D / A converting the musical sound data generated by the CPU 50 in the performance mode, and then amplifies and emits the sound from the speaker. .

B. Action
Next, the operation of the waveform generator 100 configured as described above will be described. Hereinafter, the operation of the “main routine” executed by the CPU 50 of the waveform generation device 100 will be described with reference to FIG. 4, and then the “waveform generation processing” called from the main routine with reference to FIGS. 5 to 17. The operation will be described.

(1) Operation of Main Routine FIG. 4 is a flowchart showing the operation of the main routine executed by the CPU 50. When the apparatus power is turned on, the CPU 50 advances the processing to step SA1 of the main routine shown in FIG. 4 and executes initialization for initializing each data area provided in the RAM 70. Subsequently, in step SA2, the operation mode is set according to the user's mode switch operation. In steps SA3 to SA6, the operation mode (setting mode, input mode, waveform generation mode, and performance mode) set in step SA2 is determined. The operation when the setting mode, input mode, waveform generation mode and performance mode are set will be described below.

<When set to setting mode>
When the setting mode is set, the determination result in step SA3 is “YES”, the process proceeds to step SA7, and the setting process is executed. In the setting process, an operation mode of each part of the apparatus under each operation mode is designated according to a setting parameter input in response to a user operation. For example, a waveform sampling period length and a sampling frequency in an input mode, which will be described later, are set, a tone color waveform selection in a performance mode, a type of effect to be applied, and the like are set.

  In step SA8, it is determined whether or not there is an operation event for instructing the end of the setting mode. If there is no operation event for instructing termination, the determination result is “NO”, and the setting process in step SA7 is continued. However, when an operation event for instructing termination is generated, the determination result is “YES”. Return to the operation mode setting state.

<When set to input mode>
When the input mode is set, the determination result in step SA4 is “YES”, and the flow advances to step SA9 to execute the waveform input process. In the waveform input process, after performing the initialization process necessary for this process, the input unit 10 is instructed to start waveform sampling, and the original waveform data fetched from the input unit 10 in response to this instruction is stored in the setting mode described above. In accordance with the set waveform input mode, each peak value W (n) (n = 0 to N) of the acquired original waveform data is sequentially stored in the original waveform data area of the RAM 70. In this embodiment, the source waveform is fetched from the input unit. However, if the source waveform can be fetched from the ROM or another storage medium, the user can arbitrarily specify the waveform at that portion and perform sampling. It is also possible.

  In step SA10, it is determined whether or not there is an operation event for instructing the end of the input mode. If there is no operation event for instructing termination, the determination result is “NO”, and the waveform input process in step SA9 is continued. However, when an operation event for instructing termination is generated, the determination result is “YES”, and step SA2 described above is performed. Return to the operation mode setting state.

<When quick waveform generation mode is set>
When the quick waveform generation mode is set, the determination result in step SA15 is “YES”, and the process proceeds to step SA16, where the attractor space condition identification number selection process of the regenerated waveform data area shown in FIG. Do. In other words, the conditions for generating the waveform are selected using the attractor space stored in advance without performing the turn plot as will be described later. Thereafter, the waveform generation process of step SA17 is executed. In the waveform generation process, as will be described later, the attractor is drawn in the read attractor space, and using this data, the regenerated waveform data is regenerated and stored in the regenerated waveform data area of the RAM 70. .
FIG. 12 shows a flow showing the quick waveform generation process.
<When set to waveform generation mode>
When the waveform generation mode is set, the determination result in step SA5 is “YES”, and the process proceeds to step SA11 to execute the waveform generation process. In the waveform generation processing, as will be described later, regenerated waveform data having the features of the attractor space extracted from the original waveform data stored in the original waveform data area of the RAM 70 is regenerated and stored in the regenerated waveform data area of the RAM 70. save.

  In step SA12, it is determined whether or not there is an operation event for instructing the end of the waveform generation mode. If there is no operation event for instructing termination, the determination result is “NO”, and the waveform input process in step SA11 is continued. However, when an operation event for instructing termination is generated, the determination result is “YES”, and step SA2 described above is performed. Return to the operation mode setting state.

<When set to performance mode>
When the performance mode is set, the determination result in step SA6 is “YES”, and the process proceeds to step SA13 to perform performance processing. In the performance processing, performance processing for generating musical tone data corresponding to performance information supplied from the keyboard 40 is executed. That is, the regenerated waveform data selected in timbre in the setting mode described above from among the regenerated waveform data of various tones having the features of the attractor space stored in the regenerated waveform data area of the RAM 70 is recorded on the keyboard 40. The sound of the key released by the keyboard 40 among the musical sound data that is played (reproduced) at the readout speed corresponding to the pitch of the key pressed and is simultaneously sounded (reproduced) with multiple sounds. The sound data corresponding to high is muted.

  In step SA14, it is determined whether or not there is an operation event for instructing the end of the performance mode. If there is no operation event for instructing termination, the determination result is “NO”, and the performance processing in step SA13 is continued. However, when an operation event for instructing termination is generated, the determination result is “YES”, and in step SA2 described above. Return to the operation mode setting state.

(2) Operation of Waveform Generation Processing Next, the operation of the waveform generation processing will be described with reference to FIGS. FIG. 5 is a flowchart showing the waveform generation process performed by the CPU 50. The waveform generation process executed through step SA11 (see FIG. 4) of the main routine described above is from the sequence / plot display process (step SB1), the attractor drawing process (step SB2), and the waveform regeneration process (step SB3). Composed. Hereinafter, the operation of each of these processes will be described.

a. Operation of Turns Plot Display Processing When this processing is executed via step SB1 (see FIG. 5) of waveform generation processing, the CPU 50 proceeds to step SC1 of turn plot display processing shown in FIG. Set up. In the initial setting, in addition to the initialization process necessary for this process, plot conditions (waveform section length Stime, plot scale width t, and resampling period Δt) necessary for the turn plot process executed in step SC2, which will be described later, are user-operated. Set accordingly.

  In step SC2, based on the plot conditions (waveform section length Stime, plot scale width t, and resampling period Δt) initialized in step SC1, the original waveform data stored in the original waveform data area of the RAM 70 is subjected to a turn plot. Apply processing. In the turn plot process, an attractor is generated from original waveform data, and the operation will be described with reference to FIG.

  FIG. 7 is a diagram for explaining the outline of the Turkens plot process. In the Turkens plot, a plot scale for resampling the original waveform data stored in the original waveform data area of the RAM 70 is used. An example illustrated in FIG. 7 illustrates a plot scale in the case of generating a three-dimensional attractor from two-dimensional original waveform data. The plot scale specifies the waveform value T (x, y, z) of the original waveform data at three points (x component, y component, and z component) separated by the plot scale width t.

  The plot scale for specifying the waveform value T (x, y, z) of the original waveform data moves in time series order for each resampling period Δt. The resampling period Δt has a time width equal to or greater than the sampling period of the original waveform data. Waveform values T1 (x, y, z) to waveform values Tn (x, y, z) are obtained by a plot scale that moves in time series order at each resampling period Δt. The number of waveform values T1 (x, y, z) to waveform values Tn (x, y, z) is determined by the waveform section length Stime set in step SC1.

FIG. 8 is a flowchart showing the Turkens plot process. First, the variable n is reset to 0 (step SF1), and then in step SF2, the three points separated by the plot scale width t are set to have a positional relationship on the time axis of the original waveform for plotting. That is, when t ₀ which is the first point is determined to be 0, a point t ₁ separated by time by the width of t, and t ₂ further separated by time by the width of t are set.

Next, the CPU 50 stores the peak value W (t ₀ ) at the position at time t ₀ in x ₀ in the attractor data area of the RAM 70 (step SF3). Then, the peak value W (t ₁ ) at time t ₁ is stored in y ₀ (step SF4). Further, the peak value W (t ₂ ) at time t ₂ is stored in z ₀ (step SF5). By this process, the first three-dimensional coordinates T ₁ (see FIG. 7) of the attractor displayed on the screen of the display unit 30 are determined. Thereafter, n is incremented (step SF6), and the plot scale positions t ₀ , t ₁ and t ₂ on the time axis are shifted by Δt (step SF7).

Subsequently, it is determined whether the time _{t 2} exceeds Stime (step SF8) is again x component returns to the processing in step SF3 does not exceed, y components sequentially reads the value of the z component of the RAM70 Write to the attractor data area. This operation is repeated until the time t ₂ exceeds Stime. Thereby, the waveform value T1 (x, y, z) to the waveform value Tn (x, y, z) are all stored, and the operation of the turn plot process is completed.

  Next, in step SC3 illustrated in FIG. 6, the attractor for the obtained waveform value T1 (x, y, z) to waveform value Tn (x, y, z) can express the feature most. Correlation extraction processing is performed. FIG. 9 is a flowchart of the correlation extraction process. Here, a plurality of basic attractors (hereinafter referred to as basic attractors) such as “limit cycle, strange, torus”, which are the characteristics of attractors that have been discovered and become famous, are stored in the basic attractor data area of the ROM 60 in advance. The optimum plot condition is recorded (not shown), and the correlation between the basic attractor and the attractor obtained by the above-mentioned Turkens plot process in the three-dimensional phase space is examined to obtain the highest correlation. The process for detecting is performed.

  First, one basic attractor data is retrieved from the ROM 60 from a plurality of recorded basic attractors (step SH1). Next, attractor data obtained by the Turkens plot process of FIG. 8 is called (step SH2). Then, the shapes of these two attracted attractors are compared (step SH3).

  The comparison of the figures is preferably a multi-faceted comparison by adjusting the position, scale, angle, etc. of the two figures so as to perform fingerprint authentication, but is not limited to this, and is not limited to this. A method of comparing figures in the phase space may be used.

  Next, a correlation value is determined in order to quantitatively show the correlation by comparing the two figures (step SH4). For example, this method includes a method such as pixel matching performed in image processing. Then, the calculated correlation value is compared with the value of the correlation value register in the work area of the RAM, and if it is larger, the calculated correlation value and the corresponding plot condition are stored (step SH5). Subsequently, it is determined whether or not all the stored basic attractors have been referred to (step SH6). If the reference has not been completed, other basic attractors are sequentially designated, and the processing of steps SH2 to SH6 is repeated.

When the reference to all the basic attractors is completed, the process proceeds to step SH8. That is, the correlation value register records the correlation value having the highest correlation with one of the most basic attractors at this time and the plot condition used at that time. Then, in order to perform the preparation for the next Takensu plot In step SH8, erasing data of the data _T 1 through T _n of attractor data area in the RAM 70.

  Here, the basic attractor data area for storing the basic attractor data recorded in the ROM 60 has the same structure as the attractor data area shown in FIG. In this basic attractor data area, attractor data having a famous shape among the attractors is stored. For example, in the case of showing a strange attractor, it is known that there is a high possibility of being a chaotic state, and this chaotic state is very famous as a state included in the natural world including humans. The shape of this attractor is still being discovered, and it has been found that these attractors are deeply related to human senses and natural fluctuations. This attractor may be recorded as a basic attractor whenever a new one is discovered.

  Furthermore, if the actual relationship between the characteristics of the attractor and the sound is known in advance, it can be recorded in the ROM 60 in advance as a necessary basic attractor. This makes it possible to display necessary attractors efficiently. If it is found that an unnamed attractor found by himself has a special effect, it may be possible to increase the number of basic attractors by using the attractor as a basic attractor. Furthermore, the drawn waveform may be used as a basic attractor by adding a function that allows the user to freely draw a waveform on the phase space where the attractor is displayed.

  Next, in FIG. 6, in step SC4, it is determined whether or not the processing of all plot conditions has been executed. If the turn plot and correlation extraction processing have not been performed for all plot conditions, the determination result is “NO”, the process proceeds to step SC5, the plot condition is updated, and the above steps SC2 to SC3 are repeated again. .

  The plot condition update is performed so that a combination created by a plurality of plot scale widths t and a plurality of resampling periods Δt becomes a new plot condition in the range of the waveform section length Stime. This process makes it possible to automatically and efficiently perform a Turkens plot using a large number of plot conditions.

  Note that the combination of plot conditions increases or decreases depending on how fine t and Δt are used to make the combination, but the step amount may be freely set by the user depending on the processing capacity of the CPU. It is also possible to set an appropriate value obtained from an experimental value from the beginning.

  Furthermore, in the present embodiment, the waveform section length Stime is fixed, but the plot condition may be increased by making this variable. Also, by changing the interval for each component of the plot scale t (t from x component to y and t from y to z) separately, the plot conditions are increased to increase the number of comparison processes, and the correlation value is calculated. It is also possible to improve accuracy.

  In the present embodiment, optimum plot conditions and attractors can be extracted by automatically changing various plot conditions in the Turkens plot process. For this reason, it is possible to easily display the optimum attractor without requiring the labor of the operator. Of course, instead of automatically extracting the optimal attractor as in the present embodiment, the user may extract an attractor that seems to be optimal while setting an arbitrary value.

  Further, in the present embodiment, the features of the attractor are extracted by looking at the correlation value obtained by comparing the basic attractor and the original waveform attractor. However, the present invention is not limited to this method. Various methods are currently proposed to find chaos, but if the Lyapunov exponent becomes positive by adding a separate function to calculate the Lyapunov exponent, the color of the waveform is changed to represent the trend of chaos. Alternatively, a function for executing the Fourier transform surrogate method may be added to display that the currently handled waveform is chaotic on a display unit provided separately. As a result, the characteristics of the waveform can be shown to the user in more detail, and a more efficient and convenient waveform generator can be provided.

Returning to FIG. 6 again, when the turnens plot and its correlation extraction are completed under all plot conditions, the determination result in step SC4 is “YES”. Then, the process proceeds to step SC6, where the plot condition stored in the register in step SH5 of FIG. 9 is determined to be the optimum plot condition for obtaining the maximum correlation value, the phase space condition identification number, and the dimension required for the Turkens plot. number,
The plot scale t, sampling time Δt, and other coordinate information are stored in the regenerated waveform data area. The other coordinate information includes, for example, the coordinate axis scale, color, and scale value. A plurality of phase space condition identification numbers can be stored in the regenerated waveform data area, and the user can reuse this phase space by calling it arbitrarily.

  Next, in step SC7, an attractor is obtained by executing a turn plot process on the original waveform again under the determined optimum plot condition. The obtained attractor is displayed on the display unit, and is stored in a new attractor data area in the next step SC8.

  As a result, the waveform values T1 (x, y, z) to waveform values Tn (x, y, z), which are the respective coordinate values of the attractor obtained under the optimum plot conditions, are stored in the three-dimensional phase space on the display unit 30. Plots will result in displaying attractors with plot conditions that are most correlated with the basic attractor. In this case, information such as the plot condition and the name of the basic waveform having a high correlation value may be displayed on the display unit 30 at the same time so as to inform the user of the tendency of the attractor. . By doing so, the user-friendliness is improved and the user can perform editing with planning.

  FIG. 10 is a diagram showing an example of an attractor. The CPU 50 creates an attractor space by scaling the coordinate axes in the x, y, and z directions so that the entire attractor can be accommodated. The attractor of the original waveform data is displayed on the display unit 30 like a trajectory in the attractor space. When this attractor is displayed, the plotted point and the next point may be displayed as a light-colored line in an easy-to-understand manner by performing spline processing or the like in order to show the locus clearly.

b. Next, the operation of the attractor drawing process will be described with reference to FIGS. When the three-dimensional attractor is generated from the two-dimensional original waveform data by the above-described Turkens plot display processing and drawing of the attractor of the original waveform data is completed as shown in the example shown in FIG. 10, the CPU 50 is shown in FIG. The process proceeds to step SDc of the attractor drawing process to clear the attractor data area and erase the attractor trajectory displayed in the attractor space.
Thereafter, in step SD1, as shown in FIG. 13, when the left mouse button is clicked with the mouse cursor pointing in the attractor space, data is generated in the attractor space.
The trajectory drawn in this attractor space means that the data projected on the x, y, and z coordinates is generated at the moment when a certain point is generated. The data at the time according to the correction was corrected. This means that at the same time that the point of the attractor is changed, not only that point but also the data going back by the plot scale t and 2t need to be changed in association with each other. For this reason, in the present invention, when the attractor draws the related data that goes back to the past, the related data is corrected simultaneously so that the consistency with the plot scale is maintained. When this correction process is performed, the past data already drawn is automatically changed while drawing the attractor, so the trajectory written so far automatically changes.

  Next, in step SD2, a mouse operation amount (x-axis component displacement amount, y-axis component displacement amount and z-axis component displacement amount) that changes the attractor's trajectory starting from the point designated in step SD1 is detected. That is, as shown in FIG. 14, when the mouse is dragged back and forth from the state in which a plurality of data change points are specified by clicking the left button of the mouse, the amount of movement by the drag operation is the mouse movement amount. It is detected as the y-axis component displacement amount of the cursor. Further, when the mouse is dragged left and right, the amount of movement by the drag operation is detected as the x-axis component displacement amount of the mouse cursor. Furthermore, the mouse wheel rotation operation amount is detected as the z-axis component displacement amount of the mouse cursor. By dragging the mouse in this way, data can be generated like a trajectory in an empty attractor space. This data is created for each time pitch of Δt from the starting point, and drawing is continued until the length of Stime is reached.

Subsequently, in step SD3, attractor generation / drawing processing is executed. In the attractor generation drawing process, the data start point specified in step SD1 is set to 3 according to the mouse operation amount (x-axis component displacement amount, y-axis component displacement amount and z-axis component displacement amount) detected in step SD2. In addition to the movement on the dimensional orthogonal coordinates, drawing attractor data is generated one after another for every sampling time t (see FIG. 13) for the moved section. The apparent interval on the drawing indicated by the sampling time t may be generated using the same interval as that of the deleted attractor. Further, in order to correct past attractor data related to the generated data, the data in the attractor data area corresponding to the past attractor data is corrected, and the position of the data in the already drawn space is also corrected. The generated attractor data is smoothly connected by performing known image processing so that the locus can be understood.
As described above, at the same time as the attractor data is generated, the coordinate positions of the plurality of generated data are corrected so as to be consistent with the Turkey plot condition each time, and the drawing attractor of the RAM 70 is corrected. (Waveform value T1 (x, y, z) to Waveform value Tn (x, y, z)) are stored in the data area (see FIG. 13). Interpolation calculation is performed to connect multiple points and display a smooth trajectory.

  Further, in step SD33, it is detected whether or not the data is designated as the last point, that is, whether or not the dragging is finished and the generation of the data is finished, and then the process proceeds to step SD4. If it has not been designated as the last point, the process returns to step SD2 to continue the drawing operation.

  Here, the necessity for attractor correction processing will be described in detail. All the trajectories of attractor data created by the above-mentioned Turkens plot are affected by the relationship defined by the plot scale. For example, in the case of plotting a two-dimensional waveform, a numerical value that has been treated as a z component until now is treated as y again at a different time, and data treated as y is treated as x again. . This relationship based on the plot scale is related from the first data to the last data. In other words, if data is generated in the attractor space created by a turbence plot from a two-dimensional waveform, the data of the attractor must be corrected while maintaining the relationship with the two-dimensional waveform. A mismatch occurs between the changed data and the original waveform when returning to the waveform. For example, if one piece of data is generated in this space, x, y, and z components at different times are generated from this data. At that time, the z component can be the data value of the current time, but the x and y components have generated data that is traced back by the plot scale. (This means that the past data has been rewritten.) However, even before this point is generated, this point has already been generated with a different value. At this time, it is necessary to follow the rules of Turkens plot. That is, the x and y components related to the final point of the drawing attractor that has been determined need to be retroactively corrected to the current data. In this operation, the amount of data to be modified depends on how the plot scale is created. When the relevant point reaches the first point, it is necessary to make corrections retroactively. In addition, if the user needs to do so, the data written last is overwritten with the highest priority when generating the original data of the two-dimensional waveform in the waveform generation processing to be described later without correcting this data. You may take a method. However, in this case, since the relationship between the two-dimensional waveform and the attractor is lowered, the impression given to the brain is lowered. You may enable it to set how much relevance is ensured for a user.

  As described above, the attractor trajectory illustrated in FIG. 10 is once erased, and then drawn by the user in the attractor space in the display unit 30 as a new attractor trajectory as illustrated in FIG. Then, in step SD4, the drawing attractor data representing the generated attractor trajectory, that is, each waveform value on the three-dimensional orthogonal coordinates is stored in the drawing attractor data area of the RAM 70, and this processing is finished.

c. Operation of Waveform Regeneration Process Next, the operation of the waveform regeneration process will be described with reference to FIG. This waveform regeneration process is to create a two-dimensional waveform from a drawing attractor drawn in the three-dimensional phase space by performing a process opposite to the Turkens plot performed so far.

First, when the drawing attractor data has been generated by the above-described attractor drawing process, the CPU 50 executes a waveform regeneration process via step SB3 shown in FIG. When the waveform regeneration process is executed, the CPU 50 advances the process to step SI1 in FIG. 16, and stores N, which is the last value obtained by the last sequence plot for the variable n.
In the present invention, since the drawing is permitted for the same length of time as the attractor data erased in step SDc in the attractor drawing process of FIG. 11, N is used as the last value.
In some cases, the drawing may be written longer than the attracted eraser, but in this case, the last value of the drawing attractor may be used as N.

Furthermore, steps a position on the time axis of the end of the SI2 the waveform to be reproduced and t _2, only the back time t ₁ the plot scale width t upper shaft from which time, time further back on only the time axis t it is determined that t _0. That is, here, preparation work for moving the plot scale in the reverse direction on the time axis is performed.

In step SI3, zn, yn, and xn, which are the nth coordinates of the drawing attractor data, are read out. Each of the read zn, yn, and xn is converted into peak values NW (t ₂ ), NW (t ₁ ), NW (t ₀ ) at positions t ₂ , t ₁ , t ₀ on the time axis of the two-dimensional waveform. ) Is written in the regenerated waveform data area secured in the RAM 70 (step SI4 to step SI6). This reproduced waveform area has basically the same structure as the original waveform area shown in FIG. Next, _t 2, _{t 1, t 0} moves to back in a time period Δt is decremented to n at step SI7. In the subsequent step SI8, it is determined whether n is smaller than 0. If not smaller, the process returns to step SI3, and the processes from step SI3 to SI7 are repeated. When n is smaller than 0, the determination in step SI8 is YES and the waveform reproduction process is terminated. By this waveform generation process, the changed attractor data is converted into two-dimensional regenerated waveform data and stored in the regenerated waveform data area.

  FIG. 17 shows the two-dimensional rearrangement processing of the waveform advanced by this processing. The plot scale thus completes the two-dimensional waveform while going back in time sequentially by Δt.

  In this way, in the waveform regeneration process, the attractor transformed by the above-described attractor drawing process is subjected to a processing operation opposite to the above-described turn plot process in step SC2 (see FIG. 6) to perform three-dimensional drawing. Two-dimensional regenerated waveform data is generated from the attractor data. Thereby, a sound that can be heard as a sound can be generated.

  As described above, in the present embodiment, the turn plot process is performed on the original waveform data obtained by sampling the waveform inputted from the outside, the attractor of the original waveform data is displayed, and this displayed A new trajectory is generated in the space of the attractor in response to a user operation to create a drawing attractor, and regenerated waveform data is generated by performing a reverse process of the turnens plot. Therefore, it is possible to inherit the characteristics of the attractor of the original waveform data and generate completely new waveforms of various timbres.

In the above-described embodiment, the waveform original waveform data input from the outside is used. However, a waveform obtained from a discrete sequence obtained from a logistic function or the like may be generated and used.
In addition, in this embodiment, in order to create an attractor space, it is obtained by intentionally plotting from the source waveform, but in advance, a plurality of attractor spaces that seem to be useful are stored in advance and a timbre is created. The environment can be arbitrarily selected by the user and can be rendered and reproducible.

Furthermore, in the present embodiment, an example of creating a three-dimensional attractor from two-dimensional original waveform data has been described. However, the gist of the present invention is not limited thereto, and four or more dimensions can be obtained from two-dimensional original waveform data. Needless to say, the present invention can be applied to a mode in which an attractor is generated.

It is a block diagram which shows the structure of embodiment by this invention. (A) is a figure which shows the structure of an original waveform data area. (B) is a figure which shows the structure of the regenerated waveform data area. It is a figure which shows the structure of an attractor data area. It is a flowchart which shows operation | movement of a main routine. It is a flowchart which shows the operation | movement of a waveform generation process. It is a flowchart which shows operation | movement of a turnens plot display process. It is a figure for demonstrating operation | movement of the turn plot process of step SC2 shown in FIG. It is a flowchart which shows a Turkens plot process. It is a flowchart which shows a correlation extraction process. It is a figure which shows an example of the drawn attractor track. It is a flowchart which shows operation | movement of an attractor drawing process. The flow which shows a quick waveform generation process is shown. It is a figure which shows designation | designated of the data change point in an attractor orbit. It is a figure for demonstrating the mouse operation amount detection of step SD2. It is a figure which shows an example of the changed attractor track | orbit. It is a flowchart which shows a waveform regeneration process. It is a figure which shows the operation | movement of a waveform regeneration process.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Input part 20 Operation part 30 Display part 40 Keyboard 50 CPU
60 ROM
70 RAM
80 sound system

Claims (4)

A two-dimensional phase space having a plurality of different plot conditions prepared by combining a plurality of plot scales t and a resampling time Δt, and having an input time axis and peak value axis based on each of the plurality of plot conditions. Turkens plot processing for sequentially generating multiple types of attractor data by executing Turkens plot processing for embedding in the n (n> 2) dimensional phase space by the Turkens embedding theorem on the above original waveform data Means,
Basic attractor data storage means for storing basic attractor data;
A plurality of types of attractor data generated by the Turkens plot processing means are used as coordinates to represent the waveform represented on the n-dimensional phase space and the basic attractor data stored in the basic attractor data storage means as the coordinates. A correlation value extracting means for extracting a correlation value with the waveform represented on the dimensional phase space;
Extraction means for extracting a plot condition consisting of a plot scale value t and a resampling time Δt that maximizes the correlation value extracted by the correlation value extraction means;
Attractor data generating means for generating, as new attractor data, coordinates on the n-dimensional phase space of the waveform drawn on the n-dimensional phase space;
On the two-dimensional phase space, the new attractor data generated by the attractor data generation means is subjected to the inverse conversion process of the turnense plot process using the plot conditions extracted by the plot condition extraction means. Waveform generation processing means for generating the waveform data of
The waveform generator characterized by comprising. The turnens plot processing includes a step of designating n sampling positions at intervals of plot scale values t on the time axis of the input original waveform data in the two-dimensional phase space, and the n sampling positions. A first coordinate position is determined by associating each of the crest values of each with a position on each axis in the n-dimensional phase space, and thereafter, the n sampling positions are sequentially set on the time axis for the resampling time Δt at the same time. shift to a waveform generator of claim 1, wherein performing the steps of generating an attractor data by sequentially determining the coordinate position on the n-dimensional phase space by going.   The waveform generation processing means sequentially reads the coordinate position on the n-dimensional phase space constituting the new attractor data generated by the attractor data generation means from the end, and represents the last read coordinate position n Each of the positions on the axes is set to the peak value of each of the n sampling positions designated at intervals of the plot scale value t on the time axis of the two-dimensional phase space, and each time the coordinate position is read out thereafter. The n sampling positions are simultaneously shifted on the time axis by the resampling time Δt at the same time, and the peak values of the shifted n sampling positions are used as n peak values representing the read coordinate positions. 2. The waveform generator according to claim 1, wherein the operation of assigning each position is repeated. In a computer having basic attractor data storage means for storing basic attractor data,
A two-dimensional phase space having a plurality of different plot conditions prepared by combining a plurality of plot scales t and a resampling time Δt, and having an input time axis and peak value axis based on each of the plurality of plot conditions. Turkens plot processing for sequentially generating multiple types of attractor data by executing Turkens plot processing for embedding in the n (n> 2) dimensional phase space by the Turkens embedding theorem on the above original waveform data Steps,
A plurality of types of attractor data generated by the Turkens plot processing step are used as coordinates to represent the waveform represented on the n-dimensional phase space and the basic attractor data stored in the basic attractor data storage means as the coordinates. A correlation value extracting step for extracting a correlation value with the waveform represented on the dimensional phase space;
An extraction step for extracting a plot condition composed of a plot scale value t and a resampling time Δt that maximizes the correlation value extracted by the correlation value extraction step;
An attractor data generation step of generating coordinates on the n-dimensional phase space of the waveform drawn on the n-dimensional phase space as new attractor data;
A waveform generation processing step for generating waveform data in a two-dimensional phase space by performing inverse conversion processing of the turnense plot processing using the extracted plot conditions for the generated new attractor data When,
Waveform generation processing program that executes

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