JP3186331B2 - Signal conversion method or apparatus, and recording medium - Google Patents

Abstract

PURPOSE:To obtain a sound of high sound quality that people comfortably hear by converting characteristics of acoustic time signal information by varying a difference in the attitude value of a specific frequency component from other frequency components almost in a critical band. CONSTITUTION:Band-division filters 2-4 and modified DCT(MDCT) circuits 5a-5d as a converting means convert the acoustic time signal information into plural frequency components. Then a frequency component varying circuit 6, a mask circuit 10, a frequency shift peak detecting circuit 12, a dissonant frequency component detecting circuit 11, asking threshold curve detecting 16, and a minimum audible curve generating circuit 17 as an attribute varying means vary the difference in the attribute value of the frequency component, obtained from the acoustic time signal information that frequency components at least two places have different frequency resolution and time resolution among plural frequency components obtained from the converting means, from other frequency components almost in the critical band.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention is applied to, for example, digital audio equipment, and changes the sound quality of an input audio signal, which is a time signal, particularly by using the property of hearing (that is, converts the characteristics of time signal information). The present invention relates to a signal conversion method or apparatus, and a recording medium on which information obtained by converting characteristics of time signal information by the method or apparatus is recorded.

[0002]

2. Description of the Related Art Conventionally, as a method of changing the sound quality of acoustic signal information, for example, a method of changing a frequency characteristic by a filtering process, a method of generating a higher-order harmonic, or a method of changing a dynamic range by a so-called compressor. For example, a method such as performing is used.

[0003]

However, in the case of the method using the above-mentioned filter, the sound quality is changed by changing the way of using the filter, for example, by increasing the midrange to increase the presence. In the case of the method of generating higher-order harmonics, sound is used more effectively than sound that is easy to hear. The method of changing the dynamic range by the above compressor is as follows.
Loud sounds do not hurt your ears and quiet sounds are not masked by the surrounding noise. In these systems, it is difficult to optimally control a sound that is audibly comfortable in response to a change in acoustic signal information that changes instantaneously.

Accordingly, the present invention has been proposed in view of the above-described circumstances, and a signal conversion method and apparatus capable of converting meaningful voice and acoustic signals with respect to sound quality in light of human hearing. It is another object of the present invention to provide a recording medium.

That is, the problem to be solved by the present invention is to provide a method of instantly and instantaneously producing a sound that sounds comfortable and high-quality for humans by using the aural principle of acoustic signal information. . Another object of the present invention is to improve the quality by reducing the auditory influence of quantization noise from audio signal information that has already been digitized and quantization noise has been added. . Another object of the present invention is to reduce the auditory effect of quantization noise from audio signal information that has already been digitized and quantization noise has been added. A technique for reducing the noise level on hearing by changing the spectrum of quantization noise to match so-called equal loudness characteristics and masking characteristics, which is proposed as a technology for improving the sound quality of audio equipment such as a so-called compact disc ( Hereinafter, this technique will be referred to as, for example, a super bit mapping technique.
JP, JP-A-2-185552, JP-A-2-1-1
When recording on a compact disk having a word length of 16 bits using the technique disclosed in Japanese Patent No. 85556 or the like, an object of the present invention is to produce data with improved sound quality by auditory processing. The super bit mapping technique can improve sound quality when a digital signal having a word length exceeding 16 bits is re-quantized for a compact disk having a 16-bit length. Further, one object of the present invention is to provide an audio signal information to which quantization noise has already been added, equivalently reducing the sound quality to 16 perceptually.
Improving the sound quality by improving the sound quality once by maintaining the S / N of the frequency band that is perceptually important at 16 bits or more when re-quantizing to 16 bits again by improving it to 16 bits or more. is there.

[0006]

A signal conversion method according to the present invention has been proposed to achieve the above-mentioned object, and uses a frequency component obtained by converting acoustic time signal information into a frequency. In the signal conversion method for converting an acoustic time signal, for each frequency component in a substantially critical band, at least two indices based on adjacent frequency components are obtained with different frequency widths, and the frequency component in the critical band is determined using the index. Is selected, and the relative magnitude between the frequency component of the selected region and other frequency components within the critical band is changed. Further, a signal conversion device of the present invention has been proposed to achieve the above object, and a signal for converting the acoustic time signal using a frequency component obtained by converting the acoustic time signal information into a frequency. In the conversion device, for each frequency component in the substantially critical band, an index calculating means for obtaining at least two indices based on adjacent frequency components with different frequency widths, and using the indices, a region of the frequency component in the critical band. It has a region selecting means for selecting and a frequency component changing means for changing a relative magnitude of a frequency component of the selected area and another frequency component in the critical band.

Here, when converting the acoustic time signal information into frequency components, the acoustic time signal information is divided into a plurality of bands, and each band signal is orthogonally transformed to obtain a plurality of frequency components. To do. Note that the frequency resolution of the plurality of frequency components is higher as the frequency is lower.

[0008] When changing the characteristics of the acoustic time signal information, at least one local peak of a plurality of frequency components obtained from the acoustic time signal information is interposed between other local frequency components within a substantially critical band. To change the size of the attribute, to increase the size of the attribute between other frequency components having a frequency difference of 10% to 50% of the critical bandwidth, and to increase the frequency component. From the difference between the two moving peak values obtained from the above, the frequency domain in which the difference in the magnitude of the attribute of the frequency component is changed is determined. The value obtained by subtracting the moving peak value of the% width reduces or eliminates the frequency components in the negative frequency region, and adjusts the magnitude of the frequency components so as to preserve the short-time energy of the time signal information. Adjusting the magnitude of the frequency component of at least one local peak so as to conserve the short-time energy of the time signal information, and for the frequency component obtained from the acoustic time signal information, other frequency components within a substantially critical band. Changing the difference in the magnitude of the attribute between the frequency component exceeding the minimum audible level or the masking threshold level, and for the frequency component obtained from the acoustic time signal information, Of the frequency components, changing the difference in the size of the attribute between the minimum audible level and the frequency component exceeding the larger masking threshold level, the frequency component obtained from the acoustic time signal information, Change the difference in attribute size between frequency components within a limited level range, among other frequency components within a substantially critical band If, by changing the difference magnitude of attributes between the frequency components in the level range which is limited by the quantization noise level, and the like performed.

Further, in the signal conversion method or apparatus according to the present invention, requantization processing having a noise shape characteristic is performed on the time signal information recombined on the time axis. At this time, the noise shape characteristic depends on at least one of the minimum audibility, equal loudness, and masking characteristic.

[0010] In the signal conversion method or apparatus according to the present invention, the attribute is a magnitude of a frequency component.

That is, in other words, the signal conversion method or apparatus of the present invention obtains a frequency component by filtering or orthogonally transforming an input acoustic time signal. Next, moving peak values for adjacent components of these frequency components are obtained at two different frequency widths related to the critical band,
By reducing the magnitude of the frequency component in the frequency band where the difference between the two types of moving peak values occurs, the degree of dissonance between the local peak frequency component and other frequency components is reduced. In developing the input acoustic time signal on the frequency axis, a time domain component of a plurality of frequency bands is obtained by a filter or the like, and then a blocking frequency analysis method such as orthogonal transform is used, or a so-called QMF (Quadrature
rror Filter), CQF (Conjugate Quadrature Filte
By connecting the band division filters such as r) in a tree structure, the frequency resolution gradually decreases from the low band to the high band, and conversely the band resolution is improved.

At this time, the low-frequency band may be divided into blocks longer in time than the high-frequency band so as to obtain the peak values of a plurality of samples on the orthogonal transform or the time axis. The frequency bandwidth and the time width of the block should provide a frequency resolution that sufficiently satisfies the critical bandwidth so as to be acoustically optimal. In each block, the spectrum obtained by the analysis is determined based on its magnitude and frequency as to whether or not it is above a masking threshold (masking threshold). If it is below the masking threshold, the intensity is determined. , Phase, and other attributes are not changed. The same is true for the minimum audible limit, and the frequency components below the minimum audible limit are not changed even if the difference between the moving peak values is not zero.

Further, when the level of the already added quantization noise is identifiable or predictable, performing a process different from that of the other components on the frequency component of this level is performed by using the added quantum noise. This is effective in effectively removing the formation noise. For example, it is effective to provide a larger attenuation rate than other components or to completely remove the components.
Further, reducing the bit length by performing the super bit mapping process on the audio signal information processed as described above, when performing recording and reproduction transmission with a limited word length,
This is effective in preventing audible deterioration of sound quality as much as possible.
As described above, the present invention solves the above-described problem by controlling the frequency components of the acoustic signal information in an auditory manner.

Further, a recording medium of the present invention is a medium on which converted data obtained by processing by the above signal conversion method or apparatus is recorded. The recording medium may be a magneto-optical disk, an optical disk, a semiconductor memory,
C memory card and the like.

[0015]

According to the present invention, the sound quality of voice and acoustic signals can be adjusted to be useful to humans by controlling the harmonic relationship between frequency components within a critical band that is acoustically supported. In addition, not changing the masking threshold and the frequency components below the minimum audible limit should not perform unnecessary processing unrelated to sound quality as much as possible, and prevent unnecessary side effects such as connection distortion. It is valid. Furthermore, despite the fact that the digital sample data recorded on the compact disc has only a 16-bit word-length resolution, the combination of the change of the audible frequency component and the super bit mapping process creates 16-bit sound signal information. Recording on a compact disk, digital audio tape, or the like is effective for recording acoustic signal information to which quantization noise has already been added and acoustic signal information containing an acoustically undesirable frequency component.

[0016]

Embodiments of the present invention will be described below with reference to the drawings.

As shown in FIG. 1, the signal conversion apparatus of the present embodiment to which the signal conversion method of the present invention is applied includes a band division filter (described later) as conversion means for converting acoustic time signal information into a plurality of frequency components. 2, 3, 4 and MDCT circuit 5
a, 5b, 5c, 5d, and a plurality of frequency components obtained from the conversion means, at least two frequency components of which are obtained from acoustic time signal information having different frequency resolutions and time resolutions, A frequency component changing circuit 6 and a mask circuit 10, a frequency shift peak detecting circuit 12, and a dissonance frequency detecting circuit, which will be described later, serve as attribute changing means for changing the difference in the size of the attribute from other frequency components in the substantially critical band. 11, a masking threshold curve detection circuit 16, and a minimum audible curve generation circuit 17.

First, FIG. 1 is a block circuit diagram showing a schematic configuration of one embodiment of a signal conversion device of the present embodiment for realizing a signal conversion method according to the present invention. Hereinafter, the specific configuration of FIG. 1 will be described in detail.

That is, the signal converter of this embodiment divides an input digital signal such as voice or acoustic signal information (acoustic time signal information) into a plurality of frequency bands, The width is the same, and the higher the frequency band, the wider the bandwidth is selected in the higher frequency band, the orthogonal transform is performed for each frequency band, and the frequency domain shift is performed based on the obtained spectrum data on the frequency axis. Information on the peak curve and the masking curve in the frequency domain is obtained.

From the information on the moving peak curve in the frequency domain, a frequency band in which a desirable change in sound quality can be expected by changing the frequency component based on the harmonic relationship between the frequency components is obtained. In addition, from the information on the masking curve in the frequency domain, in a frequency band in which a preferable change in the sound quality can be expected by changing the frequency component obtained from the information on the moving peak curve in the frequency domain, a substantial change in the sound quality is expected by the masking. A frequency region that cannot be obtained is obtained and excluded from a frequency band in which a frequency component is changed. Frequency components below the minimum audible limit are also excluded from the change. The magnitude of the frequency component in the frequency band in which the frequency component thus obtained is changed is reduced or eliminated.

Next, time signal information is obtained by performing an inverse orthogonal transformation of the frequency component, and the entire band is obtained by synthesizing the entire band with a synthesis filter. Further, when performing quantization, a super bit mapping process for audibly optimizing a quantization noise spectrum within a band of 20 kHz or less is performed.

More specifically, referring to FIG. 1, the input terminal 1 has, for example, a sampling frequency of 44.1 kHz.
At the time of z, an audio PCM signal of 0 to 22 kHz is supplied. This input signal is, for example, the so-called CQ
The band is divided into a band of 0 to 11 kHz and a band of 11 to 22 kHz by a band dividing filter 2 such as F.
The band signal is also converted to a band of 0 to 5.5 kHz and a band of 5.5 to 11 kHz by a band division filter 3 such as a CQF filter.
divided into z bands. Further, the signals in the 0 to 5.5 kHz band are also converted to 0 to 5.5 kHz by a band division filter 4 such as CQF.
It is divided into a 2.75 kHz band and a 2.75 to 5.5 kHz band.

11k to 22k from band division filter 2
The signal in the Hz band is an MDCT which is an example of an orthogonal transformation circuit.
(Modified Discrete Cosine Transform) The signal in the 5.5 kHz to 11 kHz band from the band division filter 3 is sent to the MDCT circuit 5 b, and the signal in the 2.75 kHz to 5.5 kHz band from the band division filter 4 is sent to the circuit 5 a. Is sent to the MDCT circuit 5c, and the signal in the 0 kHz to 2.75 kHz band from the band division filter 4 is transmitted to the MDCT circuit 5c.
d to be subjected to MDCT processing. Of course, these orthogonal transform circuits include the MD
In addition to CT, orthogonal transform such as fast Fourier transform (FFT) and discrete cosine transform (DCT) can be used.

Here, as a method of dividing an input digital signal into a plurality of frequency bands by the above-described band division filter, there is a method of using a filter such as the above-described CQF.
h and Thomas P. Barnwell, "Exact Reconstruction Tec
hniques for Tree-Structured Subband Coders, "IEEE T
rans.ASSP, Vol ASSP-34 No 3, June 1986, pp. 434-4
41. Also, 1976 RECrochiere Dig
ital coding of speech in subbands BellSyst.Tech.
J. Vol. 55, No. 8 1976 describes a method using a filter such as QMF. ICASSP 83, BOSTON Pol
yphase Quadrature filters-A newsubband coding tech
nique Joseph H. Rothweiler describes an equal-bandwidth filter partitioning method.

As the above-described orthogonal transform, for example, an input audio signal is divided into blocks in a predetermined unit time (frame), and for each block, for example, a fast Fourier transform (FFT), a cosine transform (DCT), a modified DCT transform ( For example, there is an orthogonal transformation that transforms a time axis into a frequency axis by performing (MDCT) or the like. MDCT above
About ICASSP 1987 Subband / Transform Coding Usin
g Filter Bank DesignsBased on Time Domain Aliasing
Cancellation JPPrincen ABBradley Univ. Of Surr
ey Royal Melbourne Inst. of Tech.

Here, each of the MDCT circuits 5a, 5b,
FIG. 2 shows a specific example of a standard input signal for a block for each band supplied to 5c and 5d.

In the specific example shown in FIG. 2, the four filter output signals described above have different orthogonal transform block sizes for each band, and are subjected to frequency analysis that sufficiently satisfies the critical bandwidth at each frequency. Do. Thus, the higher the frequency, the lower the frequency resolution, but instead, the higher the time resolution. In the present embodiment, the frequency decomposition is selected so that the critical band is divided into approximately ten parts. Thus, the control of the magnitude of the frequency component in the critical band can be performed with the frequency in the critical band being restricted quite freely.

That is, in the present embodiment, from 0 Hz to 2.
For the band up to 75 kHz, the time block size of the orthogonal transform is set to 46.4 msec so that a frequency resolution of approximately 10 Hz, which is one tenth of the narrowest critical bandwidth of 100 Hz, is obtained. Similarly, 2.7
The 5 kHz to 5.5 kHz band has a frequency resolution of 40 Hz using the orthogonal block time block size of 11.6 msec, and the 5.5 kHz to 11 kHz band has 5.8 m.
80H using the time block size of the orthogonal transform in sec
As for the frequency resolution of z, the frequency resolution of 160 Hz is obtained using the time block size of the orthogonal transform of 2.9 msec in the 11 kHz to 22 kHz band. In addition, 11k
Since the critical bandwidth in Hz is approximately 3 kHz, it is effective to further reduce the orthogonal transform block size to a frequency resolution of 320 Hz to further increase the time resolution. Table 1 shows the center frequency and the bandwidth of the critical band.

[0029]

[Table 1]

Referring back to FIG. 1, each MDCT circuit 5a,
The frequency component or MDCT coefficient data obtained by performing the MDCT processing in 5b, 5c, and 5d includes a frequency shift peak detecting circuit 12 that determines a frequency region in which a frequency component having a dissonance relation with the local peak frequency component exists; The signal is supplied to a dissonance frequency detection circuit 11 and a masking threshold curve detection circuit 16 for obtaining a masking threshold curve.

Here, the frequency shift peak detecting circuit 1
Operation 2 will be described below. FIG. 3 illustrates how to obtain moving peak values for three adjacent frequency components for easy understanding.

First, the moving peak value centered on the component s1 is calculated as the component s1 including the component s1 and its neighboring components.
The moving peak value is defined by the magnitude of the component having the largest magnitude among 0, s1, and s2. Next, the moving peak value around the component s2 is determined by the magnitude of the component having the largest magnitude among the components s1, s2, and s3 including the component s2 and its neighboring components. Defined. The moving peak curve is obtained by successively obtaining the peak values in this manner.

In FIG. 3, for the sake of clarity, all the frequency components have the same bandwidth, and the frequency width for obtaining the moving peak is also shown as being equal. In the present embodiment, however, as shown in FIG. In addition, as the frequency becomes higher, the bandwidth of the frequency component expands and becomes 10% of the critical bandwidth at that frequency.
Alternatively, a moving peak value in a frequency width of 50% width is obtained. In FIG. 4, reference numeral BE1~BE4 shows the band, respectively, the movement peak curve of 10% the width of the curve P ₁₀ is critical bandwidth in the figure, the curve P ₅₀ 50% of the critical bandwidth
A moving peak curve of the width is shown, a curve SD shows a frequency component distribution, and CB shows a critical bandwidth at each frequency. Here, in a frequency band in which the peak values are defined in an overlapping manner, the higher peak value is selected.

Note that the critical bandwidth is a physical quantity that enables human hearing characteristics such as consonance, noise sensation, and masking characteristics to be well understood. For the present invention, FIG. Will be explained. FIG. 5 shows that when the frequency difference between the two frequency components is only the frequency indicated on the horizontal axis (the axis indicating the frequency normalized by the critical bandwidth), the degree of coordination or imbalance between the two frequency components The vertical axis indicates whether or not concordance is exhibited. According to this result, 2
When the frequency difference between the two frequency components is between 10% and 50% of the critical bandwidth (dissonance band NHB), a sense of dissonance occurs (dissonance level NHL), between 0% and 10% and between 50% and 100%. In the frequency difference (consonant band HB), a sense of consonance occurs (consonant level HL). As shown in Table 1, the higher the critical bandwidth, the wider the critical bandwidth.

Next, specific means for detecting a dissonance band will be described with reference to FIG. Each MDCT circuit 5 in FIG.
The frequency components or MDCT coefficient data obtained by performing the MDCT processing at a, 5b, 5c, and 5d are subjected to an absolute value, and then are processed by the dissonance frequency detection circuit 11 shown in FIG. It is provided to an input terminal 41. Here, the low-frequency characteristic having a longer time width is commonly used for each high-frequency time.

From the frequency components applied to the input terminal 41, moving peak characteristics having two different frequency widths can be obtained. That is, the moving peak detecting circuit 42 having a width of 10% of the critical bandwidth giving a moving peak value having a width of 10% of the critical bandwidth and the moving peak detecting circuit 42 having a width of 50% of the critical bandwidth giving a moving peak value having a width of 50% of the critical bandwidth. The moving peak detection circuit 43 provides moving peak characteristics having two different frequency widths.

A moving peak detecting circuit 42 having a width of 10% of the critical bandwidth giving a moving peak value of 10% of the critical bandwidth, and a 50% of a critical bandwidth giving a moving peak value of 50% of the critical bandwidth. The difference of the moving peak curve obtained by the moving peak detecting circuit 43 of the width is obtained by the difference detecting circuit 44, and is taken out from the output terminal 45.

A frequency region in which the difference between the moving peak values thus obtained exceeds a certain threshold is defined as a dissonant frequency region.

However, when considering other auditory effects, ie, masking effect, equal loudness, and minimum audibility, it is necessary to operate all the frequency components included in the dissonance frequency region obtained as described above. Absent. That is, when considering the masking effect, equal loudness, and minimum audibility, frequency components determined to be inaudible are hardly affected even when removed from the operation target, and the equal loudness is considered. At times, it is useful to reduce the amount of calculation by operating only the effective band.

As described above, the mask circuit 10 having the mask function, the masking threshold curve detection circuit 16 having the masking curve calculation function, and the minimum audible curve generating circuit 17 for storing the minimum audible information are shown in FIG. Considering the masking effect and minimum audibility,
It is used to exclude a frequency component determined not to be audible from the operation target.

Hereinafter, the mask function in the mask circuit 10, the masking curve calculation function in the masking threshold curve detection circuit 16, and the minimum audible limit storage function in the minimum audible curve generation circuit 17 will be described in more detail. .

FIG. 7 is a block circuit diagram showing a schematic configuration of a specific example of a masking curve calculation function in the masking threshold curve detection circuit 16. In FIG. 7, an input terminal 71 is supplied with frequency component data from each of the MDCT circuits 5a, 5b, 5c and 5d in FIG.

The input data on the frequency axis is sent to the energy calculation circuit 72 for each critical band, where the energy of each critical band calculates the sum of the amplitude values of the frequency components in each critical band. It is required by Instead of the energy for each critical area, a peak value or an average value of the amplitude value may be used. This energy calculation circuit 72
For example, the spectrum of the sum value of each band is shown as SB in FIG. However, in FIG. 8, the number of divided bands is represented by 12 bands (B1 to B12) to simplify the illustration.

Here, in order to consider the influence on the so-called masking of the spectrum SB, a convolution (convolution) process is performed in which the spectrum SB is multiplied by a predetermined weighting function and added. Therefore, the output of the energy calculation circuit 72 for each band, that is, each value of the spectrum SB, is sent to the convolution filter circuit 73. The convolution filter circuit 73 includes, for example, a plurality of delay elements for sequentially delaying input data and a plurality of multipliers (for example, 25 corresponding to each band) for multiplying an output from these delay elements by a filter coefficient (weighting function). Multipliers) and a sum adder for summing the outputs of the multipliers. By this convolution process, for example, the sum of the portions indicated by the dotted lines in FIG. 8 is obtained for the spectrum SB of the band indicated by B6 in FIG. The above-mentioned masking is a phenomenon in which a certain signal masks another signal and becomes inaudible due to human auditory characteristics. The masking effect includes successive masking by an audio signal on a time axis. There is an effect and a simultaneous masking effect by a signal on the frequency axis. Due to these masking effects, even if there is signal information or noise in the masked portion, they will not be heard. Therefore, in the actual audio signal, the signal information and the noise within the masked range need not be operated.

A specific example of the multiplication coefficient (filter coefficient) of each multiplier of the convolution filter circuit 73 is shown below.
Assuming that the coefficient of the multiplier M corresponding to an arbitrary band is 1, the multiplier M-1 has a coefficient of 0.15, the multiplier M-2 has a coefficient of 0.0019, and the multiplier M-3 has a coefficient of 0. 00000
86, the multiplier M + 1 multiplies the coefficient 0.4, the multiplier M + 2 multiplies the coefficient 0.06, and the multiplier M + 3 multiplies the coefficient 0.007 by the output of each delay element.
B convolution processing is performed. Here, M is an arbitrary integer of 1 to 25.

Next, the output of the convolution filter circuit 73 is sent to a subtractor 74. The subtractor 74 is for obtaining a level α corresponding to signal information or a noise level which can be excluded from an operation target described later in the convolved area. The level α corresponding to signal information or noise level that can be excluded from the operation target is
As will be described later, by performing the inverse convolution process, the level is such that the signal information or the noise level can be excluded from the operation target for each band of the critical band (critical bandwidth). Here, an allowance function (a function expressing a masking level) for obtaining the level α is supplied to the subtractor 74. The level α is controlled by increasing or decreasing the allowable function. The permissible function is (n−
ai) It is supplied from the function generating circuit 75.

That is, the level α corresponding to the signal information or noise level that can be excluded from the operation target is
Assuming that the number given in order from the lower band of the critical band is i, it can be obtained by the following equation (1). α = S− (n−ai) (1) In the equation (1), n and a are constants, a> 0, S is the intensity of the convolution-processed bark spectrum, and (1)
In the equation, (n-ai) is an allowable function. In this embodiment, n = 38,
a = 1.

Thus, the level α is obtained, and this data is transmitted to the divider 76. In the divider 76, the level α in the convolved region is inversely convoluted. Therefore, by performing this inverse convolution processing,
A masking spectrum can be obtained from the level α. That is, this masking spectrum becomes signal information or a noise spectrum that can be excluded from the operation target.

The above inverse convolution processing is
Although complicated operations are required, in this embodiment, inverse convolution is performed using a simplified divider 76.

Next, the masking spectrum is transmitted to a subtractor 78 via a synthesis circuit 77. Here, the output from the energy detection circuit 72 for each critical band, that is, the aforementioned spectrum SB is
It is supplied via a delay circuit 79. Therefore, the subtraction operation of the masking spectrum and the spectrum SB is performed by the subtracter 78, as shown in FIG.
The level below the level indicated by the level S is masked.

The output from the subtracter 78 is taken out via an output terminal 81 via signal information or a noise level correction circuit (not shown) which can be excluded from the operation object, and is output from the mask circuit. The frequency range that can be excluded from the operation target is excluded from the discordant frequency range.

The delay circuit 79 is provided with an energy detection circuit 72 in consideration of the amount of delay in each circuit before the synthesis circuit 77.
Is provided to delay the spectrum SB from.

By the way, at the time of synthesizing by the synthesizing circuit 77 described above, data indicating a so-called minimum audible curve RC which is a human auditory characteristic as shown in FIG. , And the masking spectrum MS. At this minimum audible curve, if the absolute signal or noise level is below this minimum audible curve, the signal and noise will not be heard. This minimum audible curve differs depending on, for example, the difference in the playback volume at the time of playback, but in a realistic digital system, for example, there is not much difference in how to enter music into the 16-bit dynamic range.
For example, if quantization noise in the most audible frequency band around 4 kHz is not heard, it is considered that quantization noise below the level of the minimum audible curve is not heard in other frequency bands. Therefore, for example, assuming that the system is used so that noise around 4 kHz of the word length of the system cannot be heard, it is possible to remove the minimum audible curve RC and the masking spectrum MS from the operation target by combining them together. If the appropriate signal information or noise level is obtained, the signal information or noise level that can be excluded from the operation target in this case can be up to the shaded portion in FIG.

In this embodiment, the 4 kHz level of the minimum audible curve is adjusted to the lowest level corresponding to, for example, 20 bits. FIG. 10 also shows the signal spectrum SS.

As another method of limiting the frequency component to be operated, there is a case where the frequency component is limited by the level of the quantization noise included in the input digital signal information. When the spectrum is almost white, the quantization noise level is almost determined by the word length. Therefore, by restricting the frequency components in this level range to the operation target, the component of the quantization noise that causes dissonance is effectively generated. Can be reduced or eliminated. In FIG. 1, by storing the quantization noise level in the quantization noise level storage function,
The frequency components to be operated are limited to this level range. Of course, this quantization level may be adjusted to be optimal.

In the signal information or noise level correction circuit which can be excluded from the operation target, the subtracter 78 is provided based on, for example, information on an equal loudness curve sent from a correction information output circuit not shown. The signal information or the noise level that can be excluded from the operation target in the output from is corrected. Here, the equal loudness curve is a characteristic curve relating to human auditory characteristics. For example, the loudness curve is obtained by calculating the sound pressure of sound at each frequency that sounds as loud as a pure tone of 1 kHz, and is connected by a curve. Also called a sensitivity curve. Further, this equal loudness curve draws substantially the same curve as the minimum audible curve RC shown in FIG. In this equal loudness curve, for example, at around 4 kHz, even if the sound pressure falls by 8 to 10 dB from the place of 1 kHz, it sounds as large as 1 kHz. It doesn't sound the same size. For this reason, it can be seen that the magnitude of a signal or noise exceeding the level of the minimum audible curve should be evaluated by a frequency characteristic given by a curve corresponding to the equal loudness curve. For this reason, in consideration of the above equal loudness curve, selecting signal information or noise that can be excluded from the operation target in order to reduce the amount of calculation is:
It can be seen that it is compatible with human hearing characteristics.

Returning to FIG. 1, the mask circuit 10 uses the above-described auditory effect to prevent the frequency components from being changed in unnecessary frequency bands. The mask circuit 10 outputs, as an output, component information of the frequency components having a dissonant relationship with the local peak component that can be effectively operated to improve the auditory sound quality. The frequency component changing circuit 6 in FIG. 1 changes the size of the target frequency component based on this information.

FIG. 11 shows how the frequency component changing circuit 6 changes the magnitude of the frequency component. In FIG. 11, Band1 to Band4 in the figure are frequency regions in which the magnitude of the frequency component specified by the mask circuit 10 is changed, and the degree of the change is larger in the center of each band. This utilizes the fact that the degree of dissonance shown in FIG. 5 differs depending on the frequency difference. In the drawing, Sp1 to Sp4 represent gains at the positions of the respective local peak spectra. In order to compensate for a decrease in the total energy due to a decrease in the frequency component of the dissonant frequency band, the frequencies are used. This indicates that the magnitude of the spectrum at the position is increased.

The output of the frequency component changing circuit 6 in which the magnitude of the frequency component is changed in this way is shifted from the frequency axis to the time axis by the IMDCT circuits 9a, 9b, 9c and 9d which perform the inverse transform of the MDCT. Is converted to IMDC from these IMDCT circuits 9a, 9b, 9c, 9d
The T output signal is frequency-combined (ICQ
F) The signals are frequency-synthesized by the band synthesizing filters 13, 14, and 15 having a function to be a full band time signal.

These band synthesis filters 13, 14, 15
In some cases, the dynamic range of the full-band signal due to the change of the frequency component is larger than that of the original input signal information. Therefore, when recording on a compact disc, requantization to 16 bits is required. May be required. The applicant of the present application first re-quantizes the input digital audio signal by noise shaping in the audio band to give a noise frequency characteristic close to the equal loudness characteristic, and performs 16-bit compact disc recording.
Techniques for recording a bit requantized signal are described in, for example, the above-mentioned JP-A-2-20812 and JP-A-2-1855.
No. 52, JP-A-2-185556.

According to the present invention, in such a case, the signal processed according to the present invention is further subjected to the noise shaping to obtain a compact disk recording signal having a characteristic exceeding 16 bits.

Hereinafter, the operation of the noise shaper for performing the noise shaping will be described with reference to FIG. The signal supplied from the band synthesis filter 15 to the addition circuit 18 is
The difference from the output signal of the feedback filter 21 is obtained. The output of the addition circuit 18 is a requantizer 19 and a second addition circuit 20.
Supplied to The requantizer 19 attempts to transmit and record a signal with a small amount of information by being output with a word length smaller than the word length of the input signal. This requantizer 1
9 is connected to the output terminal 22 of the noise shaper and the second terminal.
Is supplied to the adder circuit 20 of FIG. The second adding circuit 20 obtains the difference between the input and output signals of the requantizer 19, and extracts a quantization error as an output. The output of the second adding circuit 20 is supplied to a feedback filter 21.

Here, the feedback filter 21 will be described in detail with reference to FIG. In FIG. 12, terminal 5
The signal supplied to the feedback filter 21 via 0 is sequentially shifted to a series circuit of the delay elements 52, 53, 54, and 55. The output of each delay element 52, 53, 54, 55 is
The multipliers 56, 57, 58, 59 are connected to each other, and the products of the multipliers 56, 57, 58, 59 are multiplied by the filter coefficients supplied from the corresponding coefficient input terminals 62, 63, 64, 65. Can be These multiplying elements 5
The outputs of 6, 57, 58, and 59 are added by an adding element 60 and guided to an output terminal 61 of a feedback filter.

The digital audio signal to which the noise frequency characteristic close to the equal loudness characteristic is given by the noise shaper constituted by the adder circuit 18, the requantizer 19, the second adder circuit 20, and the feedback filter 21 is output. Output from terminal 22. This output signal is subjected to a predetermined error correction process or the like, and is output to a recording medium (a magneto-optical disk, an optical disk, a semiconductor memory, an IC memory card,
Optical disc).

The converted data formed by the embodiment of the present invention can be transmitted via a transmission path in addition to being recorded on a recording medium.

Further, the present invention is not limited to the above embodiment, but can be applied to image signal information and the like.

[0067]

According to the present invention, from the above, it is possible to instantly and instantaneously produce a sound that sounds comfortable and high quality to humans by using the auditory principle of acoustic time signal information. it can. In addition, quality can be improved by reducing the auditory influence of quantization noise from the acoustic time signal information that has already been digitized and has quantization noise added, thereby improving the quality. After reducing the audible effects of quantization noise from the audio signal information obtained, as a technique for improving the sound quality of audio equipment such as compact discs, for example, the spectrum of quantization noise is adjusted to match the equal loudness characteristics and masking characteristics. When data is recorded on a compact disk having a word length of 16 bits by using a technique of reducing the noise level on the audibility by changing the data, data with improved sound quality can be produced by audible processing. Thus, when re-quantizing a digital signal having a word length exceeding 16 bits for a compact disk having a 16-bit length, sound quality can be improved. Furthermore, according to the present invention, when audio signal information to which quantization noise has already been added is perceptually improved in sound quality equivalently once to 16 bits or more and re-quantized to 16 bits again, By setting the S / N of the important frequency band to 16 bits while maintaining it at 16 bits or more, it is possible to improve sound quality.

[Brief description of the drawings]

FIG. 1 is a block circuit diagram illustrating a schematic configuration example of a signal conversion device according to an embodiment of the present invention that implements a method for converting characteristics of time signal information (signal conversion method) according to the present invention.

FIG. 2 is a diagram showing a time block for each band according to the present invention.

FIG. 3 is a diagram showing a frequency shift peak according to the present invention.

FIG. 4 is a diagram showing an example of a frequency shift peak frequency characteristic according to the present invention.

FIG. 5 is a diagram showing a relationship between a degree of consonance and a critical band.

FIG. 6 is a block circuit diagram showing a configuration example of a dissonance band detection circuit of the device according to the embodiment of the present invention.

FIG. 7 is a block circuit diagram illustrating a configuration example of a masking threshold curve detection circuit of the device of the present embodiment.

FIG. 8 is a diagram showing the sum of signal components in each critical band.

FIG. 9 is a diagram illustrating a sum value of signal components in each critical band and a masking threshold.

FIG. 10 is a diagram showing the sum of signal components in each critical band, a masking threshold, and a minimum audible limit.

FIG. 11 is a diagram illustrating an example in which the magnitude of a frequency component is changed.

FIG. 12 is a diagram illustrating a configuration example of a feedback filter for noise shaping.

[Explanation of symbols]

1, 41, 71 ... input terminal 2, 3, 4 ... band division filter (CQF) 5a, 5b, 5c, 5d ... MDCT circuit 6 ... frequency Component change circuit 10 Mask circuit 11 Dissonance frequency detection circuit 12 Frequency shift peak detection circuit 13, 14, 15 Band Synthetic filter 16 Masking threshold curve detection circuit 16 17 Minimum audible curve generation circuit 18, 20 Addition circuit 19 .. requantizer 21... Feedback filter 22, 45, 61, 81... Output terminal 42... 10% width of the critical band moving peak detection circuit 43. ........... Moving peak detection circuit having 50% width of critical band ·········· Difference detection circuits 52, 53, 54 and 55 ··· Delay elements 56, 57, 58 and 59 ··· Multiplication elements 60 ········ Addition elements 72 ···· Critical band energy calculation circuit 73 ······· Convolution filter circuit 75 ····· Function generation circuit 74 ················· ··········································· Subtraction circuit

──────────────────────────────────────────────────続 き Continued on the front page (58) Field surveyed (Int.Cl. ⁷ , DB name) H03M 7/30 G10L 13/00 G11B 20/10 301

Claims (11)

(57) [Claims] An audio time signal information is obtained by converting it into a frequency.
Transforms the sound time signal using the frequency component
In the signal conversion method, for each frequency component substantially in the critical band,
Find at least two component-based indices with different frequency widths
Because the area of the frequency components within the critical band with the index
Select and select the frequency components of the selected region and other
A signal conversion method characterized by changing a relative magnitude with respect to a frequency component . 2. The method according to claim 1, wherein the acoustic time signal information is converted into a frequency.
Transforms the sound time signal using the frequency component
In the signal conversion device, for each frequency component within the substantially critical band,
Find at least two component-based indices with different frequency widths
Index calculating means, and using the above-mentioned index to calculate the frequency component region in the critical band.
Region selecting means to select, frequency components of the selected region and other within the critical band
Frequency component change that changes the relative size with the frequency component
Additional signal conversion apparatus characterized by having means. 3. The method according to claim 2 , wherein the region selecting means includes a region within the critical band.
Select the region corresponding to at least one local peak
Signal converting apparatus according to claim 2, characterized in that. 4. The method according to claim 1, wherein the index calculating means comprises two different
The frequency width is 10% and 50% of the critical bandwidth.
3. The signal converter according to claim 2 , wherein a wave number width is used . 5. The method according to claim 1, wherein the index calculating means transfers the index.
Using the moving peak value, the region selecting means increases the difference according to the difference between the moving peak values.
The region of the frequency component is selected.
2. The signal conversion device according to 2 . Wherein said area selection means selects a frequency region where the value is negative minus the moving peak value of 10% the width of the critical bandwidth from the mobile peak value of 50% the width of the critical bandwidth
And the frequency component changing means is provided by the area selecting means.
Set the magnitude of the frequency component in the selected area within the above critical band.
6. The signal conversion device according to claim 5 , wherein the signal conversion device is relatively reduced or eliminated as compared with other frequency components . 7. The frequency component changing means, wherein, characterized in that to change the relative size of the <br/> frequency components within the critical band to store the short energy time signal information Item 3. The signal conversion device according to Item 2 . 8. The apparatus according to claim 7, wherein said frequency component changing means is selected.
Relative magnitude between the frequency component, a frequency component exceeding the minimum audible level or a masking threshold level of the other frequency components within the critical band of the serial area
Signal converter according to claim 2, wherein changing the. 9. The apparatus according to claim 6, wherein said frequency component changing means is selected.
The relative magnitude between the frequency components in the region and the frequency components within the level range defined by the quantization noise level
Signal converter according to claim 2, wherein changing the. 10. The signal conversion according to claim 2 , further comprising requantization processing means for performing a requantization process having a noise shape characteristic on the time signal information recombined on the time axis. apparatus. 11. A recording medium on which is recorded conversion data converted based on the signal conversion method according to claim 1.