JP4950119B2 - Sound processing apparatus and sound processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an audio processing device and an audio processing method that enable reproduction of discrete data with good sound quality according to user preferences. <P>SOLUTION: In an audio processing part 3, discrete data are divided into a low-band range, a middle-band range and a high-band range on a frequency band basis; band-based interpolation parts 6a, 6b, 6c are provided for each of a plurality of band-based adjustment signals generated for each frequency band through amplifiers 5a, 5b, 5c; and the band-based adjustment signals are individually subjected to an interpolation process by the respective band-based interpolation parts 6a, 6b, 6c. Thereby, a sampling function used for the interpolation process can be changed on a frequency band basis, a signal obtained by carrying out the interpolation process can be finely adjusted on a frequency band basis by changing the sampling function on a frequency band basis, and a frequency characteristic of an analog signal thus obtained by synthesizing the signal obtaining by the interpolation process can be changed if needed, whereby high-sound-quality music comprising user-desired sound quality can be reproduced. <P>COPYRIGHT: (C)2010,JPO&amp;INPIT

Description

  The present invention relates to an acoustic processing device and an acoustic processing method, for example, interpolating between discrete data arranged in a time direction sampled at a predetermined sampling frequency, and generating discrete data at a frequency higher than the sampling frequency at the time of input or an analog signal It is suitable for application when generating. In this specification, the generation of signals at high frequency discrete intervals and the generation of analog signals are referred to as “analog signal generation” as the same processing. Further, the case where the value of the function has a finite value other than 0 in the local region and becomes 0 in the other region will be referred to as a “finite platform”.

  Conventionally, when an analog signal is generated from discrete data such as digital data, a Shannon sampling function derived based on the Shannon sampling theorem has been widely used. Here, as shown in FIG. 11, Shannon's sampling function becomes 1 only at the sample position of t = 0, and becomes 0 at all other sample positions, and theoretically, its oscillation from −∞ to + ∞. Indicates a waveform that continues indefinitely. For this reason, when the interpolation processing between discrete data is actually executed by various processors using a Shannon sampling function, the processing is forcibly terminated in a finite interval, and as a result, errors due to the truncation occur. There was a problem that occurred.

  In addition, when such a Shannon sampling function is used, the analog signal to be reproduced is band-limited, so that, for example, discrete data recorded on a CD (Compact Disc) or DVD (Digital Versatile Disc) When the signal is converted into an analog signal and reproduced, there is a problem that an ultrasonic wave of 22.05 kHz or higher cannot be reproduced and a natural sound generated by the difference sound of the ultrasonic wave cannot be reproduced.

Therefore, in order to solve such a problem, a sampling function that converges in a finite range has been devised that has no truncation error and can reproduce even higher-order band components (for example, Patent Documents). 1). In this sampling function, since it converges to 0 at two sample positions before and after the origin, it is confirmed that signal reproduction can be performed with a small amount of calculation and that there is a band up to a high frequency.
International Publication No. 99/38090

  However, in an audio apparatus using such a sampling function, it is possible to vary high-frequency band components in accordance with various users such as the hard of hearing and the elderly, and various conditions such as music reproduction environment, sound source, and tone. Therefore, the frequency characteristics cannot be freely adjusted according to the situation. On the other hand, in recent years, it has been desired to provide a tailor-made audio device in which the user himself can freely adjust the sound quality including high-frequency band components according to the preference of each user, the type of music, and the like.

  The present invention has been made in consideration of the above points, and an object of the present invention is to propose an acoustic processing apparatus and an acoustic processing method capable of reproducing discrete data with good sound quality according to user preferences.

In order to solve this problem, the sound processing apparatus according to claim 1 of the present invention includes a band separation unit that separates a plurality of discrete data arranged in the time direction into a plurality of frequency bands and generates a signal in a time domain for each band. The interpolation processing signal for generating the discrete data signal for each of the time domain signals for each band is individually executed, and the interpolation processing signal is obtained by increasing the sampling frequency of the time domain signal for each frequency band. Interpolation processing means for generating, and band synthesis means for generating a time domain composite signal by synthesizing a plurality of the interpolation processing signals generated for each of the frequency bands.

The acoustic processing apparatus according to claim 2 of the present invention further comprises setting means for setting the interpolation processing method for each of the frequency bands, using a basic sampling function and a control sampling function different from the basic sampling function. It is characterized by providing.

  In the acoustic processing apparatus according to claim 3 of the present invention, the interpolation processing means includes a basic sampling function that can be differentiated a finite number of times and has a value of a finite number of times, For each frequency band, by using a sampling function comprising a control sampling function having a value and a waveform different from the waveform indicated by the basic sampling function and performing a convolution operation on the signal for each band and linear addition Provided with a function processing means for generating the interpolation processing signal, the function processing means having coefficient multiplication means for multiplying the control sampling function by a variable parameter that can be set to an arbitrary numerical value by a user. .

  According to a fourth aspect of the present invention, there is provided the acoustic processing device according to the fourth aspect of the present invention, wherein a sound pressure level is adjusted for each frequency band by multiplying one of the band-specific signal and the interpolation processing signal by a sound pressure parameter. Sound pressure setting means for generating a band-specific adjustment signal, wherein the interpolation processing means individually executes the interpolation process for each band-specific adjustment signal when multiplying the band-specific signal by the sound pressure parameter. Features.

The acoustic processing method according to claim 5 of the present invention includes a band separation step of generating a plurality of discrete data signals at a plurality of separate frequency bands of different respective band time domain aligned in the time direction, each said band Interpolation processing for individually generating the discrete data signal for each different time domain signal and generating an interpolation processing signal in which the sampling frequency of the time domain signal is increased for each frequency band And a band synthesizing step for synthesizing a plurality of the interpolated signals generated for each of the frequency bands to generate a time domain synthesized signal.

The acoustic processing method according to claim 6 of the present invention includes a setting step of setting the interpolation processing method for each of the frequency bands, using a basic sampling function and a control sampling function different from the basic sampling function. And before the band separation step.

  In the acoustic processing method according to a seventh aspect of the present invention, the interpolation processing step includes a parameter setting step in which a variable parameter is set to an arbitrary numerical value by a user, a finite number of differentiable values having a finite stage value. A sampling function comprising: a basic sampling function, and a control sampling function that is multiplied by the variable parameter and is finitely differentiable and has a value of a finite stage and a waveform different from the waveform indicated by the basic sampling function And a function processing step of generating the interpolation processing signal for each of the frequency bands by performing a convolution operation on the band-specific signal and the linear addition.

  The acoustic processing method according to claim 8 of the present invention includes a sound pressure adjusting step after any one of the band separating step and the interpolation processing step, and the sound pressure adjusting step is performed after the band separating step. In this case, the signal for each band is multiplied by a sound pressure parameter, and after the interpolation process step, the sound pressure level is multiplied for each frequency band by the sound pressure parameter. A plurality of adjusted band-specific adjustment signals are generated, and when the band-by-band signal is multiplied by the sound pressure parameter, the interpolation processing unit individually executes the interpolation processing for each band-specific adjustment signal. And

  According to the acoustic processing device of claim 1 and the acoustic processing method of claim 5 of the present invention, the interpolation processing method can be changed for each frequency band, and the interpolation processing method can be changed for each frequency band. By changing, the interpolation processing signal can be finely adjusted for each frequency band, and thus the frequency characteristics of the synthesized signal obtained by convolving the interpolation processing signal can be changed as necessary. It is possible to reproduce high-quality music having a desired sound quality.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

(1) Overall Configuration of Audio Device In FIG. 1, reference numeral 1 denotes an audio device having an acoustic processing unit 3 according to the present invention as a whole, and this audio device 1 uses an input unit 2 to record various recordings such as CDs and DVDs. The medium is reproduced, and a plurality of discrete data arranged in the time direction obtained as a result are sequentially sent to the sound processing unit 3. Incidentally, the discrete data is discrete data obtained by, for example, sampling a continuous signal that changes smoothly at regular time intervals and quantizing the sampling data obtained as a result.

  The acoustic processing unit 3 includes, for example, a band separation unit 4 that separates discrete data into three frequency bands, a low sound range, a middle sound range, and a high sound range, and a sound pressure for each of the three frequency bands, the low sound range, the mid sound range, and the high sound range. A sound pressure adjustment unit 5 that adjusts the level, an interpolation processing unit 6 that individually executes interpolation processing for each frequency band using a predetermined sampling function (described later) set for each frequency band, and a user An analog signal as a synthesized signal is generated by synthesizing a setting unit 7 that can arbitrarily set a sound pressure level and a sampling function for each frequency band and an interpolated signal generated for each frequency band. And a band synthesizing unit 8 that performs the same.

  In practice, as shown in FIG. 2, in the sound processing unit 3, the band separation unit 4 includes a digital low-pass filter 4a, a digital band-pass filter 4b, and a digital high-pass filter 4c. The frequency range can be separated into a sound range and a high frequency range. Incidentally, in the case of this embodiment, the case where the digital low-pass filter 4a, the digital band-pass filter 4b, and the digital high-pass filter 4c are constituted by FIR (Finite duration Impulse Response) filters will be described. The present invention is not limited to this, and other various digital filters such as an IIR (Infinite Impulse Response) filter may be used.

  The band separation unit 4 captures a predetermined number of discrete data by the digital low-pass filter 4a and averages the data, thereby generating a band-specific signal having a low frequency band from which a high frequency component is removed. The pressure is sent to the pressure adjusting unit 5 and the digital bandpass filter 4b.

  The digital high-pass filter 4c is composed of a high frequency band obtained by removing the set low frequency component from the discrete data by adding / subtracting the discrete data and the newly input discrete data at a set weighting ratio. A band-specific signal is generated and sent to the sound pressure adjusting unit 5 and the digital bandpass filter 4b.

  The digital band pass filter 4b subtracts the corresponding low-frequency and high-frequency band-specific signal values from the discrete data values, thereby removing the low-frequency component and the high-frequency component from the remaining mid-frequency range. The band-specific signal is generated and sent to the sound pressure adjustment unit 5.

  The sound pressure adjusting unit 5 is provided with three amplifiers 5a, 5b, and 5c corresponding to the low frequency range, the middle frequency range, and the high frequency range, and according to the sound pressure level adjustment command from the setting unit 7, An amplification value for amplifying the sound pressure level of the signal for each band can be set for each amplifier 5a, 5b, 5c.

  As a result, the sound pressure adjusting unit 5 amplifies the amplifier 5a by multiplying only the band-specific signal consisting of the low frequency band by the predetermined amplification value, and the other amplifier 5b for each band consisting of the mid-frequency band. Only the signal can be amplified by multiplying by a predetermined amplification value, and further, the amplifier 5c can multiply and amplify only the signal for each band consisting of the high frequency band by multiplying the predetermined amplification value. As a result, the sound pressure adjusting unit 5 has an amplified value so that, for example, a user who is relatively difficult to hear the low frequency band can amplify only the sound pressure level of the low frequency band-specific signal via the setting unit 7. When set, a band-specific adjustment signal in which the sound pressure level is amplified according to the amplification value is generated.

  Thus, each amplifier 5a, 5b, 5c amplifies each band signal to a predetermined sound pressure level based on an amplification value as a predetermined sound pressure parameter set individually in advance, and is thus generated. Each band-specific adjustment signal is sent to the interpolation processing unit 6. Here, the interpolation processing unit 6 is provided with three band-specific interpolation units 6a, 6b, and 6c corresponding to the frequency bands of the low sound range, the middle sound range, and the high sound range, and the interpolation processing from the setting unit 7 is performed. By the selection command, a predetermined sampling function for interpolating each band-specific adjustment signal can be set for each band-specific interpolation unit 6a, 6b, 6c.

  As a result, the band-by-band interpolation unit 6a performs the interpolation process only on the band-by-band adjustment signal in accordance with the sampling function preset by the setting unit 7, and performs the band-by-band data constituting the band-by-band adjustment signal. The sampling frequency is artificially increased by interpolation, and the interpolation processing signal obtained as a result is sent to the band synthesis unit 8. Further, at this time, the band-by-band interpolation unit 6b executes the interpolation process only on the adjustment signal for each band in the middle sound range according to the sampling function set separately from the other band-by-band interpolation units 6a and 6c by the setting unit 7. Interpolate between the band-specific data constituting the band-specific adjustment signal to increase the sampling frequency in a pseudo manner, and send the interpolation processing signal obtained as a result to the band synthesizing unit 8. Further, at this time, the band-by-band interpolation unit 6c executes interpolation processing only on the adjustment signal for each band in the high sound range according to the sampling function set separately from the other band-by-band interpolation units 6a and 6b by the setting unit 7. Then, the inter-band data constituting the per-band adjustment signal is interpolated to artificially increase the sampling frequency, and the interpolation processing signal obtained as a result is sent to the band synthesizing unit 8.

  The band synthesizing unit 8 synthesizes a plurality of interpolation processing signals generated by the interpolating units 6 a, 6 b, and 6 c for each band to generate one analog signal composed of the entire frequency band, and sends this to the output unit 9. To do. As described above, the acoustic processing unit 3 is configured to execute the interpolation processing individually for each frequency band in the interpolation processing unit 6, so that different sampling functions can be freely set for each frequency band. It becomes like this. Thus, the acoustic processing unit 3 adjusts the interpolation function for interpolating between the band-specific data for each band-specific adjustment signal by appropriately changing the sampling function, and as a result, the interpolation process adjusted for each frequency band. Thus, it is possible to reproduce from the output unit 9 music having a user-desired sound quality in which the frequency characteristics of the analog signal are finely adjusted.

(2) Interpolation Processing in the Interpolation Unit by Band Next, an outline of the interpolation processing executed by the interpolation units by band 6a, 6b, and 6c will be described below. The sampling function s _N (t) used in the band-by-band interpolation units 6a, 6b and 6c is composed of a basic sampling function f (t) and a control sampling function c ₀ (t). Here, the sampling position of the discrete data is assumed to be t, and, for example, a sampling consisting of a basic sampling function f (t) and a control sampling function c ₀ (t) between the sampling positions [−2, 2] of the discrete data. The function s ₂ (t) is given by

When a general control sampling function is expressed as c _k (t) and c _k (t) = c _r (t−k) + c _r (−t−k), the discrete data The sampling function s _N (t) between sample positions [−N, N] is

Represented by Α _k represents a variable parameter described later, and represents an arbitrary numerical value that can be set by the user, and may be the same value that does not vary with k, such as α ₁ = α ₂ = α ₃ . Incidentally, the sampling function s ₂ (t) when N = 2 will be described below simply as the sampling function s _N (t) for convenience of explanation. Since the sampling function s _N (t) can calculate an interpolation value reflecting the value of the variable parameter α, the interpolation processing signal can be adjusted for each frequency band by changing the value of the variable parameter α. Has been made. The basic sampling function f (t) and the control sampling function c ₀ (t) show waveforms as shown in FIG. 3, and the waveform shown by the control sampling function c ₀ (t) according to the value of the variable parameter α. The amplitude of can be increased and decreased.

  The basic sampling function f (t) is a function of a finite stage focusing on differentiability. For example, the basic sampling function f (t) can be differentiated only once in the entire region, and the sample position t along the horizontal axis is −1 to +1 (ie, , [−1, 1]) has a finite value other than 0, and the other intervals are functions that are represented as 0 by identity. Specifically, the basic sampling function f (t) is a quadratic expression in a typical function form, shows a convex waveform that can be differentiated only once in the entire range, and is 1 only at a sample position of t = 0. And converges to 0 toward t = ± 1 and reaches 0 as it is until the sample position of t = ± 2.

  The basic sampling function f (t) may be an nth-order impulse response function of a finite number, and may be an nth-order piecewise polynomial function that is continuous at the point where sample points are divided. Specifically, such a basic sampling function f (t) is, in the case of a quadratic piecewise polynomial function,

Represented by Then, by using the basic sampling function f (t) to perform superposition based on each band-specific data constituting the band-specific adjustment signal, the value between the band-specific data of the band-specific adjustment signal is differentiated only once. Temporary interpolation can be performed using possible functions.

On the other hand, the control sampling function c ₀ (t) is a function of a finite stage focusing on differentiability, and can be differentiated only once in the entire region, for example, and the sample position t along the horizontal axis is from −2. It is a function that has a finite value other than 0 when it is in +2 (that is, the interval [−2, 2]), and is uniformly expressed as 0 in other intervals. The control sampling function c ₀ (t) shows a waveform that can be differentiated only once in the entire range, and has a feature that it becomes 0 at each sample position of t = 0, ± 1, ± 2.

The control sampling function c ₀ (t) may be an n-order impulse response function of a finite number, and may be an n-order piecewise polynomial function that is continuous at a point where sample points are divided. Here, the control sampling function c ₀ (t) is represented by the control sampling function c ₀ (t) = c _r (t) + c _r (−t) as described above, and this _cr (t) is Specifically,

Represented by Then, by using the control sampling function c ₀ (t) to perform superposition based on the band-specific data of the band-specific adjustment signal, the value between the band-specific data of the band-specific adjustment signal can be differentiated only once. Can be interpolated using a simple function.

The sampling function s _N (t) is represented by a linear combination of the basic sampling function f (t) and the control sampling function c ₀ (t), and the actual interpolation operation is the basic sampling function f (t). A convolution operation between a temporary interpolation value (hereinafter referred to as a basic interpolation value) calculated by a convolution operation with discrete data (sample values), a control sampling function c ₀ (t), and discrete data (sample values) By linearly adding the provisional interpolation value calculated in step (hereinafter referred to as the control interpolation value), the value between the band-specific data of the band-specific adjustment signal is interpolated using a function that can be differentiated only once. be able to.

Incidentally, the linear combination of the basic sampling function f (t) and the control sampling function c ₀ (t) is a function that satisfies the following six conditions. First, S ₂ (0) = 1, S ₂ (± 1) = S ₂ (± 2) = 0. Secondly, it should be symmetric with respect to the even function, ie the y-axis. Thirdly, the sample position interval [−∞, −2], [2, ∞] should be zero on the identity. Fourthly, each section [n / 2, (n + 1) / 2] (−4 ≦ n ≦ 3) is at most a quadratic polynomial. Fifth, all sections should be C1 class, that is, differentiable continuously once. Sixth, in the sample position section [−1/2, 1/2],

To be.

In addition to this, the control sampling function c ₀ (t) can be multiplied by a variable parameter α set by an arbitrary numerical value by the user. As a result, the control sampling function c ₀ (t) remains 0 at the sample positions of t = 0, ± 1, ± 2, depending on the value of the variable parameter α between the sample positions −2 and +2. The amplitude of the waveform can be modified. As a result, the control sampling function c ₀ (t) can change the calculation result by the convolution operation with the discrete data (sample value). Thus, the variable parameter α can change the frequency characteristic of the interpolation processing signal calculated by the sampling function s _N (t) by changing the numerical value, and the high frequency component of each frequency band can be changed. The signal level can be adjusted.

Therefore, in the present invention, the interpolation processing signal is adjusted by changing the variable parameter α multiplied by the control sampling function c ₀ (t) for each frequency band, and a plurality of signals generated for each frequency band are generated. By synthesizing these interpolation processing signals, an analog signal is generated, so that an analog signal having a sound quality desired by the user whose high sound range is finely adjusted for each frequency band can be generated.

(3) Circuit configuration of interpolator for each band (3-1) Outline description of interpolation processing in interpolator for each band The three interpolators 6a, 6b, and 6c for each band are sampling functions s _N (t) used for the interpolation process. The variable parameter α is set separately and the adjustment signal for each band to be interpolated is different, but other points have the same configuration. Description will be made by paying attention to the interpolator 6a for each band that interpolates the adjustment signal.

  As shown in FIG. 4, the band-by-band interpolation unit 6 a includes a data extraction unit 15 that sequentially extracts and holds a predetermined number (four in this case) of band-by-band data constituting the band-by-band adjustment signal, and a data extraction unit 15. And a function processing unit 14 for receiving a predetermined number of band-specific data extracted and held at a time and performing interpolation using these band-specific data, and a predetermined interval between the band-specific data sequentially input from the amplifier 5a. The data can be interpolated at the time interval.

The function processing unit 14 includes a basic term calculation unit 16 that processes a convolution operation with a term of the basic sampling function f (t) in the sampling function s _N (t) based on the band-specific data, and the band-specific data. Based on the control function arithmetic unit 17 for processing the convolution operation with the term of the control sampling function c ₀ (t) in the sampling function s _N (t), and the variable parameter α in the calculation result of the control term arithmetic unit 17 Are multiplied by a coefficient multiplication unit 18 and an addition calculation unit 19 that linearly adds the calculation result of the basic term calculation unit 16 and the calculation result of the coefficient multiplication unit 18.

  In the case of this embodiment, the data extraction unit 15 extracts the previous four band-specific data from the band-specific data that are sequentially input, and these four bands are then input until new band-specific data is next input. Separate data is held, and these four band-specific data are sent to the basic term calculation unit 16 and the control term calculation unit 17, respectively.

  The basic term calculation unit 16 stores a basic sampling function f (t) in a predetermined storage means (not shown), and when an interpolation position between band-specific data is designated, this interpolation position and band-specific calculation are performed. Based on the distance to the data, the value of the basic sampling function f (t) is calculated. The basic term calculation unit 16 can calculate the value of the basic sampling function f (t) for each of the four band-specific data transmitted from the data extraction unit 15. Further, the basic term calculation unit 16 multiplies the values of the band-specific data corresponding to the values of the four basic sampling functions f (t) obtained for the band-specific data, and then the four band-specific data. The convolution operation corresponding to is performed, and the calculation result of the convolution operation is sent to the addition operation unit 19.

At the same time, the control term calculation unit 17 stores the control sampling function c ₀ (t) in a predetermined storage means (not shown), and when an interpolation position is designated, this interpolation position and band-specific data The value of the control sampling function c ₀ (t) is calculated based on the distance between. The control term calculation unit 17 can calculate the value of the control sampling function c ₀ (t) for each of the four band-specific data transmitted from the data extraction unit 15. Further, the control term calculation unit 17 multiplies the values of the corresponding band-specific data for each value of the four control sampling functions c ₀ (t) obtained for the band-specific data, and then adds these. Thus, the convolution operation corresponding to the four band-specific data is performed, and the calculation result of the convolution operation is sent to the coefficient multiplier 18.

The coefficient multiplication unit 18 multiplies the calculation result of the convolution calculation of the control sampling function c ₀ (t) received from the control term calculation unit 17 by the variable parameter α, and adds the variable parameter multiplication result obtained as a result to the addition calculation unit Send to 19. The addition calculation unit 19 linearly adds the calculation result of the convolution calculation of the basic sampling function f (t) received from the basic term calculation unit 16 and the variable parameter multiplication result received from the coefficient multiplication unit 18 to obtain 4 An operation result corresponding to one band-specific data is obtained. A value obtained by this linear addition is an interpolation value at an interpolation position between two predetermined band-specific data. Incidentally, the value of this interpolation position is updated every predetermined period of time, specifically, every 1 / N period (= T / N) of the period T corresponding to the input interval of the band-specific data. The

(3-2) Specific example of obtaining an interpolation value based on four band-specific data Next, an interpolation value between two predetermined band-specific data is calculated based on four band-specific data arranged in time series. The interpolation processing to be performed will be described below with reference to FIG. 5 showing the positional relationship between the continuous four band-specific data and the point of interest that is the interpolation position. In FIG. 5, the values of the band-specific data d1, d2, d3, d4 sequentially input corresponding to the respective sample positions t1, t2, t3, t4 are represented by Y (t1), Y (t2), Y ( Assume that t3) and Y (t4) are set, and an interpolation value y corresponding to a predetermined position between the sample positions t2 and t3 (that is, the interpolation position (distance b from t2)) t0 is obtained.

Since the sampling function s _N (t) used in the present embodiment converges to 0 at the sample position of t = ± 2, the band-specific data d1, d2, d3, d4 up to t = ± 2 is taken into consideration. That's fine. Therefore, when obtaining the interpolation value y shown in FIG. 5, only the four band-specific data d1, d2, d3, and d4 corresponding to t = t1, t2, t3, and t4 need to be considered. The amount can be greatly reduced. In addition, data for each band (not shown) of t = ± 3 or more should be considered originally, but is not ignored in consideration of the amount of calculation and accuracy, but is considered theoretically. There is no need for censoring errors.

  As shown in FIG. 6, the data extraction unit 15 includes three shift circuits 20a, 20b, and 20c. When continuous band-specific data is input, the corresponding band is obtained for each shift circuit 20a, 20b, and 20c. The different data is shifted, for example, at a CD sampling period (44.1 kHz), and each of the shift circuits 20a, 20b, and 20c can extract and hold the previous band-specific data d1, d2, d3, and d4, respectively. That is, when four consecutive band-specific data d1, d2, d3, d4 are input, the data extraction unit 15 uses the latest band-specific data d4 as it is and the basic term calculation circuit 21a and the control term of the basic term calculation unit 16. Each is sent to the control term calculation circuit 22a of the calculation unit 17.

  Further, the data extraction unit 15 sends a band-specific data string composed of four consecutive band-specific data d1, d2, d3, d4 to the shift circuit 20a, and the shift circuit 20b shifts the band-specific data string to the latest. The previous band-specific data d3 is extracted from the band-specific data d4 and sent to the basic term calculation circuit 21b of the basic term calculation unit 16 and the control term calculation circuit 22b of the control term calculation unit 17, respectively.

  Further, the data extraction unit 15 sequentially transmits the band-specific data string to the remaining shift circuits 20b and 20c, and further shifts the band-specific data string by the shift circuit 20b, so that two data from the latest band-specific data d4 are obtained. The previous band-specific data d2 is sent to the basic term calculation circuit 21c and the control term calculation circuit 22c, respectively, and the band-specific data string is further shifted by the shift circuit 20c, so that the previous band-specific data d4 is changed by the previous three bands. The data d1 is sent to the basic term calculation circuit 21d and the control term calculation circuit 22d.

  Here, FIGS. 7 and 8 are diagrams showing an outline of the interpolation processing for the predetermined interpolation position t0 in the basic term calculation unit 16 and the control term calculation unit 17 of the present embodiment. As the contents of the interpolation processing, as described above, first, the calculation processing for calculating the basic interpolation value in the basic term calculation unit 16 (hereinafter simply referred to as basic interpolation value calculation processing), the control term calculation unit 17 Then, a calculation process for calculating a control interpolation value in the coefficient multiplication unit 18 (hereinafter simply referred to as a control interpolation value calculation process) is executed. Hereinafter, the basic interpolation value calculation process and the control interpolation value calculation process will be described with reference to FIGS. 7 and 8.

(3-2-1) Basic Interpolation Value Calculation Processing As shown in FIGS. 7A to 7D, the basic interpolation value calculation processing includes basic information for each sample position t1, t2, t3, and t4. The peak heights at t = 0 (center position) of the sampling function f (t) are matched, and the value of each basic sampling function f (t) at the interpolation position t0 at this time is obtained.

  Focusing on the band-specific data d1 at the sample position t1 shown in FIG. 7A, the distance between the interpolation position t0 and the sample position t1 is 1 + b. Therefore, the value of the basic sampling function at the interpolation position t0 when the center position of the basic sampling function f (t) is aligned with the sample position t1 is f (1 + b). Actually, in order to match the peak height of the center position of the basic sampling function f (t) so as to match the value Y (t1) of the band-specific data d1, the above-described f (1 + b) is multiplied by Y (t1). The obtained value f (1 + b) · Y (t1) is a desired value. Calculation of f (1 + b) is performed by the basic term calculation circuit 21a of the basic term calculation unit 16, and calculation for multiplying f (1 + b) by Y (t1) is performed by the basic term multiplication circuit 23a of the basic term calculation unit 16. (FIG. 6).

  Similarly, focusing on the value Y (t2) of the band-specific data d2 at the sample position t2 shown in FIG. 7B, the distance between the interpolation position t0 and the sample position t2 is b. Therefore, the value of the basic sampling function at the interpolation position t0 when the center position of the basic sampling function f (t) is aligned with the sampling position t2 is f (b). Actually, in order to match the peak height of the center position of the basic sampling function f (t) so as to match the value Y (t2) of the band-specific data d2, the above-described f (b) is multiplied by Y (t2) times. The obtained value f (b) · Y (t2) is a desired value. The calculation of f (b) is performed by the basic term calculation circuit 21b of the basic term calculation unit 16, and the calculation of multiplying f (b) by Y (t2) is performed by the basic term multiplication circuit 23b of the basic term calculation unit 16. (FIG. 6).

  Focusing on the value Y (t3) of the band-specific data d3 at the sample position t3 shown in FIG. 7C, the distance between the interpolation position t0 and the sample position t3 is 1-b. Therefore, the value of the basic sampling function at the interpolation position t0 when the center position of the basic sampling function f (t) is aligned with the sampling position t3 is f (1-b). Actually, in order to match the peak height of the center position of the basic sampling function f (t) so as to coincide with the value Y (t3) of the band-specific data, the above-described f (1-b) is changed to Y (t3). The multiplied value f (1-b) · Y (t3) is the value to be obtained. The calculation of f (1-b) is performed by the basic term calculation circuit 21c of the basic term calculation unit 16, and the calculation of multiplying f (1-b) by Y (t3) is the basic term multiplication circuit of the basic term calculation unit 16. 23c (FIG. 6).

  Focusing on the value Y (t4) of the band-specific data d4 at the sample position t4 shown in FIG. 7D, the distance between the interpolation position t0 and the sample position t4 is 2-b. Therefore, the value of the basic sampling function at the interpolation position t0 when the center position of the basic sampling function f (t) is aligned with the sampling position t4 is f (2-b). Actually, in order to match the peak height of the center position of the basic sampling function f (2-b) so as to match the value Y (t4) of the band-specific data d4, the above-described f (2-b) is set to Y The value f (2-b) · Y (t4) multiplied by (t4) is the desired value. The calculation of f (2-b) is performed by the basic term calculation circuit 21d of the basic term calculation unit 16, and the calculation of multiplying f (2-b) by Y (t4) is the basic term multiplication circuit of the basic term calculation unit 16. 23d (FIG. 6).

  The basic term calculation unit 16 then obtains four values f (1 + b) · Y (t1), f (b) · Y (t2), and f (1−b) obtained corresponding to the point of interest at the interpolation position t0. ) · Y (t3) and f (2-b) · Y (t4) are convolutionally calculated in the basic term convolution circuit 24, and the basic interpolation value ya is calculated in the low frequency band. Incidentally, in the case of this embodiment, the values f (1 + b) · Y (t1) and f (2-b) · Y (t4) obtained corresponding to the point of interest at the interpolation position t0 are shown in FIG. ) And 0 as shown in (D), the basic interpolation value ya is {f (b) · Y (t2)} + {f (1−b) · Y (t3)}.

(3-2-2) Control Interpolation Value Calculation Processing On the other hand, the contents of the control interpolation value calculation processing are as shown in FIGS. 8A to 8D for each sample position t1, t2, t3, t4. , to match the t = 0 (center position) of the control sampling function c ₀ (t), the band-by-band data d1 corresponding to each control sampling function _{c 0 (t), d2,} d3, d4 of the value Y ( t1), Y (t2), Y (t3), and Y (t4) are multiplied, and the value of each control sampling function c ₀ (t) at the interpolation position t0 at this time is obtained.

Focusing on the value Y (t1) of the band-specific data d1 at the sample position t1 shown in FIG. 8A, the distance between the interpolation position t0 and the sample position t1 is 1 + b. Therefore, the value of the control sampling function at the interpolation position t0 when the center position of the control sampling function c ₀ (t) is aligned with the sample position t1 is c ₀ (1 + b). Actually, in order to match the waveform height of the control sampling function c ₀ (t) in correspondence with the value Y (t 1) of the band-specific data d 1, a value obtained by multiplying the above c ₀ (1 + b) by Y (t 1). c ₀ (1 + b) · Y (t1) is a desired value. The calculation of c ₀ (1 + b) is performed by the control term calculation circuit 22a of the control term calculation unit 17, and the calculation of multiplying c ₀ (1 + b) by Y (t1) is performed by the control term multiplication circuit 25a of the control term calculation unit 17. Performed (FIG. 6).

Similarly, paying attention to the value Y (t2) of the band-specific data d2 at the sample position t2 shown in FIG. 8B, the distance between the interpolation position t0 and the sample position t2 is b. Therefore, the value of the control sampling function at the interpolation position t0 when the center position of the control sampling function c ₀ (t) is aligned with the sample position t2 is c ₀ (b). Actually, in order to match the waveform height of the control sampling function c ₀ (t) in correspondence with the value Y (t 2) of the band-specific data d 2, a value obtained by multiplying the above c ₀ (b) by Y (t 2). c ₀ (b) · Y (t2) is a desired value. The calculation of c ₀ (b) is performed by the control term calculation circuit 22b of the control term calculation unit 17, and the calculation of multiplying c ₀ (b) by Y (t2) is performed by the control term multiplication circuit 25b of the control term calculation unit 17. Performed (FIG. 6).

Focusing on the value Y (t3) of the band-specific data d3 at the sample position t3 shown in FIG. 8C, the distance between the interpolation position t0 and the sample position t3 is 1-b. Therefore, the value of the control sampling function at the interpolation position t0 when the center position of the control sampling function c ₀ (t) is aligned with the sampling position t3 is c ₀ (1-b). Actually, in order to match the waveform height of the control sampling function c ₀ (t) in correspondence with the value Y (t 3) of the band-specific data d ₃ , the above c ₀ (1-b) is multiplied by Y (t 3). The value c ₀ (1-b) · Y (t3) is the value to be obtained. The calculation of c ₀ (1-b) is performed by the control term calculation circuit 22c of the control term calculation unit 17, and the calculation of multiplying c ₀ (1-b) by Y (t3) is the control term of the control term calculation unit 17. This is performed by the multiplication circuit 25c (FIG. 6).

Focusing on the value Y (t4) of the band-specific data d4 at the sample position t4 shown in FIG. 8D, the distance between the interpolation position t0 and the sample position t4 is 2-b. Therefore, the value of the control sampling function at the interpolation position t0 when the center position of the control sampling function c ₀ (t) is aligned with the sampling position t4 is c ₀ (2-b). Actually, in order to match the waveform height of the control sampling function c ₀ (2-b) in correspondence with the value Y (t4) of the band-specific data d4, the above-described c ₀ (2-b) is changed to Y (t4). ) The multiplied value c ₀ (2-b) · Y (t4) is the desired value. The calculation of c ₀ (2-b) is performed by the control term calculation circuit 22d of the control term calculation unit 17, and the calculation of multiplying c ₀ (2-b) by Y (t4) is the control term of the control term calculation unit 17. This is performed by the multiplication circuit 25d (FIG. 6).

Then, four values c ₀ (1 + b) · Y (t1), c ₀ (b) · Y (t2), c ₀ (1−b) · Y () obtained corresponding to the point of interest at the interpolation position t0. t3), c ₀ (2-b) · Y (t4) are subjected to a convolution operation by the control term convolution circuit 26 of the control term operation unit 17, and then multiplied by the variable parameter α in the coefficient multiplication unit 18, thereby reducing A control interpolation value yb in the frequency band of the sound range is calculated.

(3-2-3) Interpolation Value Calculation Processing The addition calculation unit 19 is calculated by the basic interpolation value ya corresponding to the target point calculated by the basic term calculation unit 16, the control term calculation unit 17, and the coefficient multiplication unit 18. By linearly adding the control interpolation value yb corresponding to the target point, the interpolation value y at the interpolation position t0 in the low frequency band can be output. In this manner, interpolation values are similarly calculated for all other interpolation positions between the band-specific data d2 and d3, and the band-based interpolation units 6b and 6c are also provided for each frequency band of the middle sound range and the high sound range. A similar interpolation processing technique can be executed using the set sampling function.

(3-3) Interpolation Processing Result when Variable Parameter Values are Changed In addition to the above configuration, the acoustic processing unit 3 causes the setting unit 7 to change the variable parameter α value of the coefficient multiplication unit 18 into each band-based interpolation unit 6a. , 6b, and 6c, the value of the sampling function s _N (t) is changed for each of the interpolators 6a, 6b, and 6c for each band, and the interpolation value y is adjusted for each frequency band. obtain. As a result, the analog signal generated in the band synthesizing unit 8 can be adjusted in frequency characteristics by changing the numerical value of the variable parameter α for each frequency band. Here, with respect to how the sampling function s _N (t) changes when the variable parameter α is changed, the waveform shown by the basic sampling function f (t) shown in FIG. The following description will be focused on a waveform obtained by combining the waveform indicated by the function c ₀ (t).

As shown in FIG. 9, the waveform of the sampling function s _N (t) obtained by synthesizing the waveform indicated by the basic sampling function f (t) and the waveform indicated by the control sampling function c ₀ (t) is a variable parameter. It varies greatly depending on the numerical value of α. In this embodiment, when the variable parameter α is sequentially changed to −1.5, −0.25, and 1.5, the region of −2 ≦ t ≦ −1 and the region of 1 ≦ t ≦ 2 Then, it was confirmed that the amplitude of the wavelength of the sampling function s _N (t) gradually increased and the waveform polarity was inverted. On the other hand, in the region of −1 ≦ t ≦ 0 and the region of 0 ≦ t ≦ 1, it was confirmed that the wavelength amplitude of the sampling function s _N (t) gradually decreased and the polarity of the waveform was inverted.

By the way, the discrete data obtained by playing the violin song “Zigeunerweisen” recorded on CD as a test song for 23 seconds is not separated into the low, mid and high frequency bands. The interpolation processing was performed as is. At this time, the variable parameter α is set to −0.25, −1.5, and 1.5, respectively, and the frequency characteristics of the analog signals interpolated with each sampling function s _N (t) are compared. The results as shown in Fig. 1 were obtained.

As shown in FIG. 10, in the interpolation process using each sampling function s _N (t) in which the numerical value of the variable parameter α is changed, even if the numerical value of the variable parameter α is changed, all of them are in a high frequency range of 20 kHz or more. The signal level increased, and it was confirmed that the high frequency range component could be reproduced compared to the case where the conventional Shannon sampling function was used. Since the waveform having such characteristics is formed in the same manner even when interpolating the band-specific data generated by separating discrete data into the frequency bands of the low range, the mid range and the high range, As compared with the case where the Shannon sampling function is used, it is possible to reproduce a high-frequency component in each frequency range of the low-frequency range, the mid-range and the high-frequency range.

  Further, when the variable parameter α is set to 1.5, −1.5, or −0.25, the waveforms of the respective signal levels are different from each other. And since a waveform having such characteristics is formed in the same way even when interband processing is performed on band-specific data generated by separating discrete data into low-frequency, middle-frequency and high-frequency ranges. , By changing the value of the variable parameter α as appropriate for each frequency range of the low, mid and high frequencies, the signal level can be adjusted individually within the low, mid and high frequency ranges. can do.

Thus, the acoustic processing unit 3 can adjust the fine signal level for each frequency band by changing the variable parameter α of the sampling function s _N (t) for each frequency band. It is possible to make the user easily perform finer adjustment of characteristics. Thus, in the present invention, each interpolation processing signal is individually adjusted by changing the variable parameter α for each frequency band, and an analog signal is generated by synthesizing the plurality of adjusted interpolation processing signals. An analog signal in which the high frequency range is finely adjusted for each frequency band can be generated.

(4) Operation and Effect In the above configuration, the acoustic processing unit 3 separates discrete data for each frequency band of the low frequency range, the middle frequency range, and the high frequency range, and generates a plurality of band-specific adjustment signals generated for each frequency range. The band-specific interpolation units 6a, 6b, and 6c are provided for each band, and the band-specific adjustment signals are individually interpolated by the band-specific interpolation units 6a, 6b, and 6c. As a result, the acoustic processing unit 3 can change the sampling function used for the interpolation process for each frequency band, and the interpolation process obtained by performing the interpolation process by changing the sampling function for each frequency band. The signal can be finely adjusted for each frequency band, and by synthesizing a plurality of interpolation processing signals obtained by the interpolation processing, the frequency characteristics of the analog signal can be finely changed as necessary, and the sound quality desired by the user High-quality music consisting of can be played.

  As described above, the acoustic processing unit 3 generates the interpolation processing signal in which the interpolation value is finely adjusted for each frequency band, and generates the analog signal by combining the plurality of interpolation processing signals. High-quality music composed of the desired sound quality with the frequency characteristics of the analog signal adjusted by the user changing the sampling function for each frequency band as appropriate according to various conditions such as music playback environment, sound source, tune, etc. Can be played.

In particular, in the present invention, the variable parameter α of the sampling function s _N (t) is individually changed for each frequency band so that the interpolation process can be performed, so that the interpolation value can be finely adjusted for each frequency band. As a result, the frequency characteristics of analog signals can be further finely adjusted accordingly. That is, the discrete data composed of all frequency bands without being separated into the low, middle and high frequency bands is simply interpolated by changing the variable parameter α of the sampling function s _N (t) as it is. Compared with the case of adjusting the frequency characteristics, in the present invention, the frequency characteristics of the analog signal can be finely adjusted by the fine adjustment of the interpolation value for each frequency band, and thus the high sound quality of the user desired sound quality can be obtained. Music can be played.

  In the case of this embodiment, the basic sampling function f (t) is stored in the basic term calculation unit 16, and each band-specific data d1, d2, d3, d4 extracted by the data extraction unit 15 is stored. The value of the basic sampling function f (t) is calculated with the distance to the interpolation position t0 as t, and the value of the basic sampling function f (t) corresponding to each of the band-specific data d1, d2, d3, d4. The basic interpolation value ya at the interpolation position t0 is calculated by performing a convolution operation.

Separately from this, in the acoustic processing unit 3, the control sampling function c ₀ (t) is stored in the control term calculation unit 17, and the band-specific data d 1, d 2, d 3 extracted by the data extraction unit 15. , The value of the control sampling function c ₀ (t) is calculated by setting the distance at the interpolation position t ₀ for each d 4, and the control sampling function c ₀ corresponding to each of the band-specific data d 1, d 2, d 3, d 4. After the convolution operation of the value of (t), the variable parameter α set to an arbitrary numerical value by the user is multiplied by the convolution operation result of the control sampling function c ₀ (t), thereby controlling at the interpolation position t0. The interpolation value yb was calculated.

The acoustic processing unit 3 calculates the interpolation value y between the discrete data by linearly adding the basic interpolation value ya calculated in this way and the control interpolation value yb. An interpolation value y reflecting the numerical value of the variable parameter α multiplied by the value of the function c ₀ (t) can be calculated.

Therefore, the acoustic processing unit 3 can easily adjust the interpolation value y obtained by performing the interpolation process with the sampling function s _N (t) by simply changing the numerical value of the variable parameter α. There is no need to provide a plurality of circuit boards corresponding to each of _N (t), and the configuration can be simplified correspondingly and the cost can be reduced.

In addition, the acoustic processing unit 3 uses a finite base basic sampling function f (t) and a control sampling function c ₀ (t) that can be differentiated only once over the entire area as the sampling function s _N (t). Since the control sampling function c ₀ (t) is multiplied by the variable parameter α, the amount of computation required for the interpolation processing between discrete data is greatly reduced as compared with the conventional Shannon sampling function. In addition, the truncation error that occurs when the Shannon sampling function is used does not occur, and the occurrence of aliasing distortion can be prevented.

In the case of this embodiment, in particular, the value of the waveform of the sampling function s _N (t) is converged to 0 in a range that is the same as or narrower than two sample positions before and after the interpolation position t0. Therefore, when data interpolation or the like is performed using the sampling function s _N (t), it is only necessary to use a total of four discrete data pieces before and after the position of interest. Compared with the case of using, the processing burden can be remarkably reduced.

In the case of this embodiment, in the sampling function s _N (t), the basic sampling function f (t) and the control sampling function c ₀ (t) that varies depending on the numerical value of the variable parameter α are separately provided. Each of them is stored, and a convolution operation is separately performed on discrete data. A convolution operation result of the control sampling function c ₀ (t) and the discrete data is multiplied by a variable parameter α, and this is multiplied by a basic sampling function. Since the output signal is obtained by linearly adding the convolution calculation results of s _N (t) and discrete data, it is sufficient to have one control sampling function c ₀ (t), and the formula is simplified as much as possible. And variable control of the control sampling function c ₀ (t) can be easily performed.

  Furthermore, in the acoustic processing unit 3, the amplifiers 5a, 5b, and 5c are provided for each frequency band, and the sound pressure level is individually amplified by the amplifiers 5a, 5b, and 5c. It is possible to amplify only the sound pressure level in a frequency band that is difficult to hear, and thus it is possible to reproduce high-quality music composed of the sound quality desired by the user.

(5) Other Embodiments The present invention is not limited to the present embodiment, and various modifications can be made within the scope of the gist of the present invention. For example, in the above-described embodiment, the case where the interpolation process using the sampling function s _N (t) is applied as the interpolation process is described. However, the present invention is not limited to this, and the sampling function is used. In addition to the interpolation processing using, various other interpolation processing may be applied.

Also, here, a sampling function s _N (t) composed of a basic sampling function f (t) and a control sampling function c ₀ (t) is used, and the control sampling function c ₀ (t) is multiplied. Although the case where the interpolation processing signal is adjusted by changing the numerical value of the variable parameter α has been described, the present invention is not limited to this, and in addition to the sampling function s _N (t), Shannon sampling is performed. The interpolation processing signal may be adjusted by selecting a function or simply selecting various preset sampling functions.

For example, although the sampling function s _N (t) is a function of a finite stage that can be differentiated only once in the entire region, the number of differentiable times may be set to 2 or more. Furthermore, in the above-described embodiment, the case where an analog signal is generated as a synthesized signal by performing an interpolation process using the sampling function s _N (t) is described, but the present invention is not limited to this. Alternatively, an oversampled composite signal may be generated by performing an interpolation process using the sampling function s _N (t), and then an analog signal may be generated by an analog-to-digital converter.

Further, in the above-described embodiment, the case where the sampling function s _N (t) converges to 0 at t = ± 2 has been described, but the present invention is not limited to this, and t = ± 3 or more. May converge to 0. For example, when t = ± 3 and converge to 0, the data extraction unit 15 extracts the previous six discrete data, and the function processing unit 14 performs sampling function s on these six discrete data. The value of _N (t) can be calculated.

Furthermore, in the above-described embodiment, the basic sampling function f (t) is stored in the basic term calculation unit 16, and separately, the control sampling function c ₀ (t) is stored in the control term calculation unit 17. The basic interpolation value ya and the control interpolation value yb are calculated by performing a convolution operation on the band-specific data d1, d2, d3, and d4 for each of the basic sampling function f (t) and the control sampling function c ₀ (t). In the above description, the interpolation value y is calculated by linearly adding the basic interpolation value ya and the control interpolation value yb. However, the present invention is not limited to this, and the basic sampling function f (t ) And the control sampling function c ₀ (t) are previously linearly added and stored as one sampling function s _N (t), and the sampling function s _N (t) with the variable parameter α changed is used. Interpolated values by performing convolution operations on band-specific data d1, d2, d3, d4 The may be calculated directly.

  Furthermore, in the above-described embodiment, the case where the interpolation processing is executed for each adjustment signal for each band in which the sound pressure level is amplified has been described. However, the present invention is not limited to this, and for each frequency band. Without amplifying the sound pressure level, the interpolation processing unit directly receives the band-specific signal separated into the predetermined frequency band by the band separation unit, and executes the predetermined interpolation process for each band-specific signal. Good.

  Furthermore, in the above-described embodiment, the case where the interpolation process is executed after the sound pressure level is amplified has been described. However, the present invention is not limited to this, and the sound pressure level is changed after the interpolation process is executed. In this case, the interpolation process may be individually executed for each band-specific adjustment signal, and the interpolation process signal obtained as a result may be individually multiplied by the sound pressure parameter.

  Furthermore, in the above-described embodiment, the case where the amplification value as the sound pressure parameter is multiplied to amplify the sound pressure level in the frequency band that is difficult for the user to hear is described. However, the present invention is not limited to this. Alternatively, the sound pressure level in a frequency band that is easy for the user to listen to may be attenuated by multiplying the attenuation value as the sound pressure parameter. Even in this case, the sound pressure level is not attenuated. Since the frequency band can be emphasized, it is easy for the user to listen to a frequency band that is difficult for the user to listen to, and thus high-quality music can be reproduced for the user.

  Furthermore, in the above-described embodiment, the case where discrete data is separated into three frequency bands, a low sound range, a middle sound range, and a high sound range has been described. However, the present invention is not limited to this, and the low sound range and the high frequency range are also described. The discrete data may be separated into two of the sound ranges, or the discrete data may be further separated into four or five frequency bands such as a low-mid range and a low-mid range between the mid-range. In this case, an amplifier and a band-specific interpolation unit may be provided according to the number of frequency bands to be separated.

It is a block diagram which shows the circuit structure of an audio apparatus. It is a block diagram which shows the circuit structure of an acoustic process part. It is the schematic which shows the relationship between the waveform of the basic sampling function used in the interpolation part according to band of this invention, and the waveform of a control sampling function. It is a block diagram which shows the circuit structure of the interpolation part according to zone | band. It is the schematic which shows the positional relationship of the data according to four bands, and the attention point. It is a block diagram which shows the detailed structure of the interpolation part according to zone | band. It is the schematic which shows the interpolation process using the basic sampling function by the interpolation part according to band by this invention. It is the schematic which shows the interpolation process using the control sampling function by the interpolation part according to band by this invention. It is the schematic which shows the waveform of the sampling function when a variable parameter is changed. It is the schematic which shows the frequency characteristic when a variable parameter is changed. It is the schematic which shows the waveform of the sampling function of Shannon in the past.

Explanation of symbols

3 Acoustic processing unit (acoustic processing device)
4 Band separation part (band separation means)
5 Sound pressure adjustment unit (Sound pressure adjustment means)
6 Interpolation processing unit (interpolation processing means)
7 Setting part (setting means)
8 Band combiner (band combiner)
14 Function processing section (Function processing means)
18 Coefficient multiplier (coefficient multiplier)

Claims (8)

Band separation means for separating a plurality of discrete data arranged in the time direction into a plurality of frequency bands and generating a signal in a time domain for each band;
Interpolation processing for generating a signal between the discrete data for each of the time domain signals for each band is performed individually, and an interpolation processing signal obtained by increasing the sampling frequency of the time domain signal for each frequency band Interpolation processing means to generate,
Band processing means for generating a time domain composite signal by combining a plurality of the interpolation processing signals generated for each of the frequency bands. The acoustic processing apparatus according to claim 1, further comprising setting means for setting the interpolation processing method for each frequency band using a basic sampling function and a control sampling function different from the basic sampling function. . The interpolation processing means includes
A basic sampling function that is finitely differentiable and has a value of a finite stage, and a control sampling that is finitely differentiable and has a value of a finite stage and shows a waveform different from the waveform indicated by the basic sampling function A function processing means for generating the interpolation processing signal for each of the frequency bands by performing a convolution operation on the signal for each band and linear addition using a sampling function comprising a function;
The acoustic processing apparatus according to claim 1, wherein the function processing means includes coefficient multiplying means for multiplying the control sampling function by a variable parameter that can be set to an arbitrary numerical value by a user. A sound pressure adjusting means for multiplying one of the band-specific signal and the interpolation processing signal by a sound pressure parameter to generate a band-specific adjustment signal in which the sound pressure level is adjusted for each frequency band,
The said interpolation process means performs the said interpolation process separately for every said adjustment signal classified by band, when multiplying the said sound pressure parameter by the said signal classified by band. The any one of Claims 1-3 characterized by the above-mentioned. The sound processing apparatus according to the description. A band separation step for separating a plurality of discrete data arranged in the time direction into a plurality of frequency bands and generating a signal in a time domain for each band;
Interpolation processing for generating a signal between the discrete data for each of the time domain signals for each band is performed individually, and an interpolation processing signal obtained by increasing the sampling frequency of the time domain signal for each frequency band Interpolating steps to generate;
A band synthesizing method comprising: synthesizing a plurality of the interpolated signals generated for each of the frequency bands to generate a time domain synthesized signal. A setting step for setting the interpolation processing method for each frequency band using a basic sampling function and a control sampling function different from the basic sampling function is provided before the band separation step. The acoustic processing method according to claim 5. The interpolation processing step includes
A parameter setting step in which a variable parameter is set to an arbitrary numerical value by the user;
A basic sampling function that is finitely differentiable and has a value of a finite stage and a waveform that is multiplied by the variable parameter and is finitely differentiable and has a value of finite stage and that is different from the waveform indicated by the basic sampling function A function processing step of generating the interpolated signal for each frequency band by using a sampling function composed of a control sampling function indicating a waveform and performing a convolution operation on the band-specific signal and the linear addition. The sound processing method according to claim 5, further comprising: A sound pressure adjustment step is provided after any one of the band separation step and the interpolation processing step,
The sound pressure adjustment step includes
After the band separation step, the band-specific signal is multiplied by a sound pressure parameter,
After the interpolation processing step, the interpolation processing signal is multiplied by a sound pressure parameter,
Generate a band-specific adjustment signal in which the sound pressure level is adjusted for each frequency band according to the sound pressure parameter,
The interpolation processing means includes
The acoustic processing method according to any one of claims 5 to 7, wherein when the signal for each band is multiplied by the sound pressure parameter, the interpolation processing is individually executed for each adjustment signal for each band.

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