JP4287840B2 - Encoder - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an encoding device capable of encoding even a signal which principally consists of a speech and on which music and an environmental sound are superposed at a low bit rate with high quality. <P>SOLUTION: A down samplers 101 decreases the sampling rate of an input signal from a sampling rate FH to a sampling rate FL. A basic layer encoder 102 encodes a sound signal with the sampling rate FL. A local decoder 103 decodes the encoded code outputted from the basic laser encoder 102. An up sampler 104 increases the sampling rate of the decoded signal to the sampling rate FH. A subtractor 106 subtracts the decoded signal from the sound signal with the sampling rate FH. An extended layer encoder 107 encodes the signal outputted from the subtractor 106 by using parameters of the decoding result outputted from the local decoder 103. <P>COPYRIGHT: (C)2005,JPO&amp;NCIPI

Description

  The present invention relates to an encoding device that compresses and encodes an acoustic signal such as a musical tone signal or a voice signal with high efficiency, and is particularly suitable for scalable encoding capable of decoding musical tones and voices even from a part of an encoded code. The present invention relates to an encoding device.

  An acoustic coding technique for compressing a musical sound signal or a voice signal at a low bit rate is important for the effective use of a transmission path capacity such as radio waves and a recording medium in mobile communication. There are systems such as G726 and G729 standardized by ITU (International Telecommunication Union) for voice coding for coding voice signals. These systems target narrowband signals (300 Hz to 3.4 kHz) and can perform high-quality encoding at a bit rate of 8 kbit / s to 32 kbit / s.

  In addition, ITU G722, G722.1, 3GPP (The 3rd Generation Partnership Project) AMR-WB, etc. exist as standard systems for wideband signals (50 Hz to 7 kHz). These systems can encode a wideband audio signal with high quality at a bit rate of 6.6 kbit / s to 64 kbit / s.

  Here, there is CELP (Code Excited Linear Prediction) as an effective method for encoding a speech signal at a low bit rate and with high efficiency. CELP is a method of encoding based on a model that is an engineering simulation of a human speech generation model. Specifically, CELP passes an excitation signal represented by a random number through a pitch filter corresponding to the strength of periodicity and a synthesis filter corresponding to vocal tract characteristics, and the square error between the output signal and the input signal is an auditory characteristic. The encoding parameter is determined so as to be minimum under the weighting of.

  Many of the recent standard speech coding schemes perform coding based on CELP. For example, G729 can encode a narrowband signal at 8 kbit / s, and AMR-WB can encode a wideband signal at 6.6 kbit / s to 23.85 kbit / s.

  On the other hand, in the case of musical tone encoding that encodes a musical tone signal, the musical tone signal is converted into the frequency domain, as in the layer III method and the AAC method standardized by the Moving Picture Expert Group (MPEG), and the psychoacoustics A method of encoding using a model is common. These systems are known to cause almost no degradation at 64 kbit / s to 96 kbit / s per channel for a signal with a sampling rate of 44.1 kHz.

  This musical tone encoding is a method for encoding music with high quality. Musical sound encoding can perform high-quality encoding even for audio signals having music or environmental sound in the background described above. The target signal band can also correspond to a CD quality of about 22 kHz.

  However, when encoding using the audio encoding method to a signal that is mainly an audio signal and music or environmental sound is superimposed on the background, only the signal in the background area is affected by the influence of the music or environmental sound in the background area. There is also a problem that the audio signal is deteriorated and the overall quality is lowered.

  This problem occurs because the speech coding method is based on a method specialized for a speech model called CELP. In addition, the signal band that can be supported by the speech coding system is up to 7 kHz, and there is a problem that it cannot sufficiently cope with a signal having a component of a band larger than that.

  In the musical sound encoding system, it is necessary to use a higher bit rate in order to realize high quality encoding. In the musical sound encoding system, there is a problem that the quality of the decoded signal is greatly deteriorated if the encoding is performed while the bit rate is reduced to about 32 kbit / s. Therefore, there is a problem that it cannot be used in a communication network with a low transmission rate.

  The present invention has been made in view of such a point, and an encoding apparatus capable of encoding with high quality at a low bit rate even if the signal is mainly a sound and music or environmental sound is superimposed on the background. The purpose is to provide.

The encoding apparatus according to the present invention includes a base layer encoding unit that obtains a first encoded code by encoding a low-frequency part that is a band part lower than a predetermined frequency of an input signal, and decodes the first encoded code. Local decoding means for generating a decoded signal, subtracting means for subtracting the decoded signal from the input signal to obtain a subtracted signal, parameters generated during the decoding process of the local decoding means, or Spectral characteristic calculation means for calculating a spectral characteristic of a filter composed of parameters obtained by converting parameters for all bands, and spectral characteristics of the filter so that the quantization accuracy of the low band part is lower than that of other bands Deformation means for deforming, vector quantization means for determining a vector quantization bit allocation or vector search weight using the transformed spectral characteristics, and It adopts a configuration comprising the subtraction signal based on the weight of the bets allocation or the vector search and enhancement layer coding means for obtaining a second encoded code by encoding the.

  According to the present invention, encoding can be performed with high quality at a low bit rate.

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

(Embodiment 1)
FIG. 1 is a block diagram showing the configuration of the signal processing apparatus according to Embodiment 1 of the present invention. A signal processing apparatus 100 in FIG. 1 includes a downsampler 101, a base layer encoder 102, a local decoder 103, an upsampler 104, a delay unit 105, a subtractor 106, and an enhancement layer encoding. It is mainly composed of a unit 107 and a multiplexer 108.

  The downsampler 101 downsamples the sampling rate of the input signal from the sampling rate FH to the sampling rate FL, and outputs an acoustic signal at the sampling rate FL to the base layer encoder 102. Here, the sampling rate FL is a frequency lower than the sampling rate FH.

  Base layer encoder 102 encodes an audio signal having sampling rate FL, and outputs the encoded code to local decoder 103 and multiplexer 108.

  Local decoder 103 decodes the encoded code output from base layer encoder 102, and outputs the decoded signal to upsampler 104 and enhancement layer encoder 107.

  The upsampler 104 raises the sampling rate of the decoded signal to FH and outputs it to the subtractor 106.

  The delay unit 105 delays the input acoustic signal of the sampling rate FH by a predetermined time, and then performs a subtracter 106. By making this delay time the same value as the time delay caused by the downsampler 101, the base layer encoder 102, and the upsampler 104, a phase shift in the next subtraction process is prevented.

  The subtractor 106 subtracts the decoded signal from the acoustic signal having the sampling rate FH, and outputs the subtraction result to the enhancement layer encoder 107.

  The enhancement layer encoder 107 encodes the signal output from the subtractor 106 using the decoding result parameter output from the local decoder 103 and outputs the result to the multiplexer 108. The multiplexer 108 multiplexes and outputs the signals encoded by the base layer encoder 102 and the enhancement layer encoder 107.

  Next, base layer coding and enhancement layer coding will be described. FIG. 2 is a diagram illustrating an example of components of the input signal. In FIG. 2, the vertical axis indicates the information amount of the signal component, and the horizontal axis indicates the frequency. FIG. 2 shows in which frequency band audio information and background music / background noise information included in the input signal are present.

  The audio information has a lot of information in a low frequency region, and the amount of information decreases as it goes to a high region. On the other hand, the background music / background noise information has relatively less low-frequency information than the audio information, and the information contained in the high frequency is large.

  Therefore, the signal processing apparatus according to the present invention uses a plurality of encoding methods and performs different encoding for each region where each encoding method is suitable.

  FIG. 3 is a diagram illustrating an example of a signal processing method of the signal processing device according to the present embodiment. In FIG. 3, the vertical axis indicates the information amount of the signal component, and the horizontal axis indicates the frequency.

  The base layer encoder 102 is designed to efficiently express audio information in the frequency band between 0 and FL, and the audio information in this region can be encoded with high quality. However, the coding quality of background music / background noise information in the frequency band between 0 and FL is not high. The enhancement layer encoder 107 encodes a portion that cannot be encoded by the base layer encoder 102 and a signal in a frequency band between FL and FH.

  Therefore, by combining the base layer encoder 102 and the enhancement layer encoder 107, high quality encoding can be realized in a wide band. Furthermore, it is possible to realize a scalable function in which audio information can be decoded only with the encoded code of at least the base layer encoding means.

  In this way, useful parameters generated by encoding in the local decoder 103 are given to the enhancement layer encoder 107, and the enhancement layer encoder 107 performs encoding using these parameters. .

  Since this parameter is generated from the encoded code, when decoding the signal encoded by the signal processing apparatus of the present embodiment, the same parameter can be obtained in the process of acoustic decoding, and this parameter is added. Thus, there is no need to transmit to the decoding side. For this reason, the enhancement layer encoding means can improve the efficiency of the encoding process without increasing the additional information.

  For example, among the parameters decoded in the local decoder 103, whether the input signal is a signal having a strong periodicity such as a vowel or a signal having a strong noise such as a consonant is used as a parameter used in the enhancement layer encoder 107. There is a configuration that uses a voiced / unvoiced flag representing. Using voiced / unvoiced flags, bit allocation is performed with emphasis on the low frequency rather than high frequency in the enhancement layer in the voiced segment, and bit allocation is performed with emphasis on the high frequency than low frequency in the unvoiced segment. Can be adapted.

  As described above, according to the signal processing apparatus of the present embodiment, a component having a frequency lower than a predetermined frequency is extracted from the input signal, is encoded suitable for speech encoding, and the obtained encoded code is decoded. By using the encoding suitable for the musical tone encoding, it is possible to perform encoding at a low bit rate with high quality.

  The sampling rates FH and FL may be any value as long as FH is larger than FL, and the values are not limited. For example, encoding can be performed with a sampling rate of FH = 24 kHz and FL = 16 kHz.

(Embodiment 2)
In the present embodiment, an example will be described in which LPC coefficients representing the spectrum of an input signal are used as parameters used by enhancement layer encoder 107 among parameters decoded by local decoder 103 of Embodiment 1. .

  The signal processing apparatus according to the present embodiment performs encoding using CELP in the base layer encoder 102 in FIG. 1, and performs encoding using the LPC coefficient representing the spectrum of the input signal in the enhancement layer encoder 107. Do.

  Here, first, the detailed operation of the base layer encoder 102 will be described, and then the basic configuration of the enhancement layer encoder 107 will be described. The basic configuration here is for simplifying the description of the embodiment in the future, and indicates a configuration in which the encoding parameter of the local decoder 103 is not used. Thereafter, the LPC coefficient is decoded by the local decoder 103 which is a feature of the present embodiment, and the enhancement layer encoder 107 using the LPC coefficient will be described.

  FIG. 4 is a diagram illustrating an example of the configuration of the base layer encoder 102. The base layer encoder 102 in FIG. 4 includes an LPC analyzer 401, an auditory weighting unit 402, an adaptive codebook searcher 403, an adaptive gain quantizer 404, a target vector generator 405, and a noise codebook search. 406, a noise gain quantizer 407, and a multiplexer 408.

  The LPC analyzer 401 obtains an LPC coefficient from the input signal sampled at the sampling rate FL in the downsampler 101 and outputs the LPC coefficient to the audibility weighting unit 402.

  The perceptual weighting unit 402 weights the input signal based on the LPC coefficient obtained by the LPC analyzer 401, and applies the weighted input signal to the adaptive codebook searcher 403, the adaptive gain quantizer 404, and the target vector generator. Output to the device 405.

  Adaptive codebook searcher 403 searches the adaptive codebook using the perceptually weighted input signal as a target signal, and outputs the searched adaptive vector to adaptive gain quantizer 404 and target vector generator 405. Then, adaptive codebook searcher 403 outputs the code of the adaptive vector determined to have the least quantization distortion to multiplexer 408.

  Adaptive gain quantizer 404 quantizes the adaptive gain to be multiplied by the adaptive vector output from adaptive codebook searcher 403 and outputs the result to target vector generator 405. The code is output to the multiplexer 408.

  The target vector generator 405 performs vector subtraction on the input signal output from the perceptual weighting unit 402 by the result obtained by multiplying the adaptive vector by the adaptive gain, and the noise codebook searcher 406 and the noise gain quantizer using the subtraction result as the target vector. Output to 407.

  The noise codebook searcher 406 searches the noise codebook for a noise vector that minimizes distortion with the target vector output from the target vector generator 405. Then, noise codebook searcher 406 provides the searched noise vector to noise gain quantizer 407 and outputs the code to multiplexer 408.

  The noise gain quantizer 407 quantizes the noise gain multiplied by the noise vector searched by the noise codebook searcher 406 and outputs the code to the multiplexer 408.

  The multiplexer 408 multiplexes the LPC coefficients, the adaptive vector, the adaptive gain, the noise vector, and the coding code of the noise gain, and outputs the multiplexed code to the local decoder 103 and the multiplexer 108.

  Next, the operation of base layer encoder 102 in FIG. 4 will be described. First, the sampling rate FL signal output from the downsampler 101 is input, and the LPC analyzer 401 determines the LPC coefficient. The LPC coefficient is converted into a parameter suitable for quantization such as an LSP coefficient and quantized. An encoded code obtained by this quantization is supplied to the multiplexer 408, and an LSP coefficient after quantization is calculated from the encoded code and converted into an LPC coefficient.

  By this conversion, the LPC coefficient after quantization is obtained. Using this quantized LPC coefficient, the adaptive codebook, adaptive gain, noise codebook, and noise gain are encoded.

  Next, the audibility weighting unit 402 weights the input signal based on the LPC coefficient obtained by the LPC analyzer 401. This weighting is performed for the purpose of shaping the spectrum so that the spectrum of the quantization distortion is masked by the spectrum envelope of the input signal.

  Next, an adaptive codebook search unit 403 searches for an adaptive codebook using the perceptually weighted input signal as a target signal. A signal obtained by repeating a past sound source sequence with a pitch period is called an adaptive vector, and an adaptive codebook is composed of adaptive vectors generated with a predetermined range of pitch periods.

When the perceptually weighted input signal is t (n) and the signal obtained by convolving the impulse response of the synthesis filter composed of LPC coefficients with the adaptive vector of pitch period i is pi (n), the following equation (1) The pitch period i of the adaptive vector that minimizes the evaluation function D is sent to the multiplexer 408 as a parameter. Here, N indicates a vector length.

Next, the adaptive gain quantizer 404 quantizes the adaptive gain multiplied by the adaptive vector. The adaptive gain β is expressed by the following equation (2). This β is scalar quantized, and the code is sent to the multiplexer 408.

Next, the target vector generator 405 subtracts the influence of the adaptive vector from the input signal to generate a target vector used by the noise codebook searcher 406 and the noise gain quantizer 407. Here, pi (n) is a signal obtained by convolving a synthesis filter with an adaptive vector when the evaluation function D represented by Equation 1 is minimized, and βq is scalar quantized with the adaptive vector β represented by Equation 2. The target vector t2 (n) is expressed by the following equation (3), where

  The target vector t2 (n) and the LPC coefficient are given to the noise codebook searcher 406, and a noise codebook search is performed.

  Here, an algebraic codebook is a typical configuration of the noise codebook provided in the noise codebook searcher 406. An algebraic codebook is represented by a vector having a very small number of pulses having an amplitude of 1. Further, in the algebraic codebook, positions that can be taken for each pulse are determined in advance without overlapping. The algebraic codebook is characterized in that the optimal combination of the pulse position and the pulse code (polarity) can be determined with a small amount of calculation.

When the target vector is t2 (n) and the noise vector corresponding to the code j is cj (n), the noise vector index j that minimizes the evaluation function D of the following equation (4) is sent to the multiplexer 408 as a parameter. It is done.

Next, the noise gain quantizer 407 performs quantization of the noise gain multiplied by the noise vector. The noise gain γ is expressed by the following equation (5). This γ is scalar quantized and the code is sent to the multiplexer 408.

  The multiplexer 408 multiplexes the transmitted LPC coefficients, adaptive codebook, adaptive gain, noise codebook, and noise gain coding code, and outputs the multiplexed code to the local decoder 103 and the multiplexer 108.

  Then, the above process is repeated while a new input signal exists. If there is no new input signal, the process ends.

  Next, the enhancement layer encoder 107 will be described. FIG. 5 is a diagram illustrating an example of the configuration of the enhancement layer encoder 107. The enhancement layer encoder 107 in FIG. 5 includes an LPC analyzer 501, a spectrum envelope calculator 502, an MDCT unit 503, a power calculator 504, a power normalizer 505, a spectrum normalizer 506, and a Bark. It is mainly composed of a scale normalizer 508, a Bark scale shape calculator 507, a vector quantizer 509, and a multiplexer 510.

  The LPC analyzer 501 performs LPC analysis on the input signal and outputs the obtained LPC analysis coefficient to the spectrum envelope calculator 502 and the multiplexer 510. The spectrum envelope calculator 502 calculates a spectrum envelope from the LPC coefficients and outputs it to the vector quantizer 509.

  The MDCT unit 503 performs MDCT transform (Modified Discrete Cosine Transform) on the input signal and outputs the obtained MDCT coefficients to the power calculator 504 and the power normalizer 505. The power calculator 504 obtains the power of the MDCT coefficient, quantizes it, and outputs it to the power normalizer 505 and the multiplexer 510.

  The power normalizer 505 normalizes the MDCT coefficient with the quantized power and outputs the normalized power to the spectrum normalizer 506. The spectrum normalizer 506 normalizes the MDCT coefficient normalized by power using the spectrum envelope, and outputs the normalized MDCT coefficient to the Bark scale shape calculator 507 and the Bark scale normalizer 508.

  The Bark scale shape calculator 507 quantizes the spectrum shape after calculating the shape of the spectrum divided at equal intervals in the Bark scale, and the quantized spectrum shape is converted into the Bark scale normalizer 508 and the vector quantization. And output to the multiplexer 509 and the multiplexer 510.

  Bark scale normalizer 508 quantizes Bark scale shape B (k) of each band and outputs the encoded code to multiplexer 510. Then, the Bark scale normalizer 508 decodes the Bark scale shape to generate normalized MDCT coefficients, and outputs them to the vector quantizer 509.

  The vector quantizer 509 vector-quantizes the normalized MDCT coefficient output from the Bark scale normalizer 508 to obtain a representative value with the smallest distortion, and outputs this index to the multiplexer 510 as an encoded code.

  The multiplexer 510 multiplexes the encoded code and outputs it to the multiplexer 108.

  Next, the operation of enhancement layer encoder 107 in FIG. 5 will be described. The subtraction signal obtained by the subtractor 106 in FIG. 1 is subjected to LPC analysis by the LPC analyzer 501. Then, an LPC coefficient is calculated by LPC analysis. The LPC coefficient is converted into a parameter suitable for quantization such as an LSP coefficient, and then quantization is performed. The encoded code related to the LPC coefficient obtained here is given to the multiplexer 510.

The spectrum envelope calculator 502 calculates a spectrum envelope according to the following equation (6) based on the decoded LPC coefficients. Here, α _q indicates the decoded LPC coefficient, NP indicates the order of the LPC coefficient, and M indicates the spectral resolution.

  The spectrum envelope env (m) obtained by Expression (6) is used by a spectrum normalizer 506 and a vector quantizer 509 described later.

Next, the MDCT unit 503 performs MDCT conversion on the input signal to obtain MDCT coefficients. The MDCT transform has a feature that frame boundary distortion does not occur because the adjacent frames before and after and the analysis frame are completely overlapped by half, and an orthogonal basis is used in which the first half of the analysis frame is an odd function and the second half is an even function. is there. When performing MDCT, the input signal is multiplied by a window function such as a sin window. When the MDCT coefficient is X (m), the MDCT coefficient is calculated according to the following equation (7). Here, x (n) represents a signal obtained by multiplying the input signal by the window function.

Next, the power calculator 504 obtains and quantizes the power of the MDCT coefficient X (m). Then, the power normalizer 505 normalizes the MDCT coefficient with the power after the quantization using Expression (8). Here, M indicates the order of the MDCT coefficient.

After quantizing the power pow of the MDCT coefficient, this encoded code is sent to the multiplexer 510. After decoding the power of the MDCT coefficient using the encoded code, the MDCT coefficient is normalized using the value according to the following equation (9). Here, X1 (m) represents the MDCT coefficient after power normalization, and powq represents the power of the MDCT coefficient after quantization.

Next, the spectrum normalizer 506 normalizes the MDCT coefficients normalized by power using the spectrum envelope. The spectrum normalizer 506 performs normalization according to the following equation (10).

Next, the Bark scale shape calculator 507 quantizes the spectrum shape after calculating the shape of the spectrum divided into bands at equal intervals on the Bark scale. The Bark scale shape calculator 507 sends this encoded code to the multiplexer 510 and normalizes the MDCT coefficient X2 (m), which is the output signal of the spectrum normalizer 506, using the decoded value. The Bark scale and the Herz scale are associated with each other by a conversion formula represented by the following formula (11). Here, B represents a Bark scale and f represents a Herz scale.

The Bark scale shape calculator 507 calculates the shape according to the following equation (12) for each subband that is divided into bands at equal intervals on the Bark scale. Here, fl (k) represents the lowest frequency of the kth subband, fh (k) represents the highest frequency of the kth subband, and K represents the number of subbands.

Then, the Bark scale normalizer 508 quantizes the Bark scale shape B (k) of each band, sends the encoded code to the multiplexer 510, decodes the Bark scale shape, and normalizes the MDCT coefficient X3 (m). Is generated according to the following equation (13). Here, Bq (k) represents the Bark scale shape after quantization of the kth subband.

  Next, the vector quantizer 509 performs vector quantization of the output X3 (m) of the Bark scale normalizer 508. The vector quantizer 509 divides X3 (m) into a plurality of vectors, obtains a representative value with the smallest distortion using a codebook corresponding to each vector, and sends this index to the multiplexer 510 as an encoded code.

  The vector quantizer 509 determines two important parameters using the spectral information of the input signal when performing vector quantization. One of the parameters is quantization bit allocation, and the other is weighting at the time of codebook search. The quantization bit allocation is determined using the spectrum envelope env (m) obtained by the spectrum envelope calculator 502.

  Further, when the quantization bit allocation is determined using the spectrum envelope env (m), the number of bits allocated to the spectrum corresponding to the frequencies 0 to FL can be set to be small.

  As one implementation example thereof, there is a method in which a maximum number of bits MAX_LOWBAND_BIT that can be allocated to frequencies 0 to FL is set, and a limit is set so that the number of bits allocated to this band does not exceed the maximum number of bits MAX_LOWBAND_BIT.

  In this implementation, since encoding is already performed in the base layer at frequencies 0 to FL, there is no need to allocate many bits, and quantization in this band is intentionally coarse to reduce bit allocation. Therefore, the overall quality can be improved by distributing and quantizing the extra bits to the frequencies FL to FH. The bit allocation may be determined by combining the spectrum envelope env (m) and the aforementioned Bark scale shape Bq (k).

Further, a distortion scale using a weight calculated from the spectrum envelope env (m) obtained by the spectrum envelope calculator 502 and the quantized Bark scale shape Bq (k) obtained by the Bark scale shape calculator 507 is used. To perform vector quantization. Vector quantization is realized by obtaining the index j of the code vector C that minimizes the distortion D defined by the following equation (14). Here, w (m) represents a weighting coefficient.

Further, the weighting function w (m) can be expressed as the following equation (15) using the spectrum envelope env (m) and the Bark scale shape Bq (k). Here, p is a constant between 0 and 1, and Herz_to_Bark () is a function for converting the Herz scale to the Bark scale.

  Further, when determining the weighting function w (m), it is possible to set so that the weighting function allocated to the spectrum corresponding to the frequencies 0 to FL is reduced. As one implementation example, the maximum value of the weight function w (m) corresponding to the frequency 0 to FL is preset as MAX_LOWBAND_WGT, and the value of the weight function w (m) of this band does not exceed MAX_LOWBAND_WGT. There is a method of setting a limit as described above. In this implementation, encoding is already performed in the base layer at frequencies 0 to FL, and the quantization accuracy in this band is intentionally lowered to relatively increase the accuracy of quantization of frequencies FL to FH. Can improve the overall quality.

  Finally, the multiplexer 510 multiplexes the encoded code and outputs it to the multiplexer 108. Then, the above process is repeated while a new input signal exists. If there is no new input signal, the process ends.

  As described above, according to the signal processing apparatus of the present embodiment, a component having a frequency equal to or lower than a predetermined frequency is extracted from the input signal, is encoded using the code-excited linear prediction method, and the obtained encoded code is decoded. By performing encoding by MDCT conversion using the result, it is possible to perform encoding with high quality at a low bit rate.

  In the above, an example in which the LPC analysis coefficient is analyzed from the subtraction signal obtained by the subtractor 106 has been described. However, the signal processing apparatus of the present invention uses the LPC coefficient decoded by the local decoder 103. It may be encoded.

  FIG. 6 is a diagram illustrating an example of the configuration of the enhancement layer encoder 107. 5 identical to those in FIG. 5 are assigned the same reference numerals as in FIG. 5 and detailed descriptions thereof are omitted.

  The enhancement layer encoder 107 in FIG. 6 includes a conversion table 601, an LPC coefficient mapping unit 602, a spectrum envelope calculator 603, and a modification unit 604, and converts the LPC coefficients decoded by the local decoder 103. It differs from the enhancement layer encoder 107 in FIG.

  The conversion table 601 stores the base layer LPC coefficients and the enhancement layer LPC coefficients in association with each other.

  LPC coefficient mapping section 602 refers to conversion table 601, converts the base layer LPC coefficients input from base layer encoder 102 into enhancement layer LPC coefficients, and outputs them to spectrum envelope calculator 603.

  The spectrum envelope calculator 603 obtains a spectrum envelope based on the LPC coefficient of the enhancement layer and outputs the spectrum envelope to the deforming unit 604. The deformation unit 604 deforms the spectrum envelope and outputs it to the spectrum normalizer 506 and the vector quantizer 509.

  Next, the operation of enhancement layer encoder 107 in FIG. 6 will be described. The LPC coefficient of the base layer is obtained for a signal whose signal band is 0 to FL, and does not match the LPC coefficient used for the signal (signal band 0 to FH) that is the target of the enhancement layer. However, there is a strong correlation between the two. Therefore, the LPC coefficient mapping unit 602 separately designs a conversion table 601 that represents the correspondence between the LPC coefficients for signals in the signal bands 0 to FL and the LPC coefficients for signals in the signal bands 0 to FH using this correlation. Keep it. Using this conversion table 601, the enhancement layer LPC coefficients are obtained from the base layer LPC coefficients.

  FIG. 7 is a diagram illustrating an example of calculating the extended LPC coefficient. The conversion table 601 includes J candidates {Yj (m)} representing LPC coefficients (order M) of the enhancement layer and the same order (= K) as the LPC coefficients of the base layer associated with {Yj (m)}. ) Are candidates {yj (k)}. {Yj (m)} and {yj {k}} are prepared and prepared in advance from large-scale musical sounds, voice data, and the like. When the base layer LPC coefficient x (k) is input, the LPC coefficient most similar to x (k) is determined from {yj (k)}. The mapping of the enhancement layer LPC coefficients to the enhancement layer LPC coefficients can be realized by outputting the enhancement layer LPC coefficients Yj (m) corresponding to the LPC coefficient index j determined to be the most similar. it can.

  Next, the spectrum envelope calculator 603 obtains a spectrum envelope based on the enhancement layer LPC coefficients determined in this way. Then, the spectrum envelope is deformed by the deforming unit 604. Then, processing is performed by regarding this deformed spectrum envelope as the spectrum envelope of the above-described embodiment.

As an implementation example of the deforming unit 604 that deforms the spectrum envelope, there is a process of reducing the influence of the spectrum envelope corresponding to the signal bands 0 to FL to be encoded in the base layer. When the spectral envelope is env (m), the transformed spectral envelope env ′ (m) is expressed by the following equation (16). Here, p represents a constant between 0 and 1.

  Encoding is already performed in the base layer at frequencies 0 to FL, and the spectrum of frequencies 0 to FL of the subtraction signal to be encoded in the enhancement layer is nearly flat. Nevertheless, such an effect is not considered in the mapping of LPC coefficients as described in the present embodiment. Therefore, the quality can be improved by using a method of correcting the spectrum envelope using the equation (16).

  Thus, according to the signal processing apparatus of the present embodiment, the enhancement layer LPC coefficients are obtained using the LPC coefficients quantized by the base layer encoder, and the spectrum envelope is calculated from the enhancement layer LPC analysis. Thus, the need for LPC analysis and quantization is eliminated, and the number of quantization bits can be reduced.

(Embodiment 3)
FIG. 8 is a block diagram showing the configuration of the enhancement layer encoder of the signal processing apparatus according to Embodiment 3 of the present invention. 5 identical to those in FIG. 5 are assigned the same reference numerals as in FIG. 5 and detailed descriptions thereof are omitted.

  The enhancement layer encoder 107 of FIG. 8 includes a spectral fine structure calculator 801, and calculates the spectral fine structure using the pitch period encoded by the base layer encoder 102 and decoded by the local decoder 103. However, it differs from the enhancement layer encoder of FIG. 5 in that the spectrum fine structure is utilized for spectrum normalization and vector quantization.

  The spectral fine structure calculator 801 calculates a spectral fine structure from the pitch period T and pitch gain β encoded in the base layer, and outputs them to the spectrum normalizer 506.

  Specifically, the pitch period T and the pitch gain β are part of the encoded code, and the same information can be obtained in an acoustic decoder not shown here. Therefore, even if encoding is performed using the pitch period T and the pitch gain β, the bit rate does not increase.

The spectral fine structure calculator 801 calculates the spectral fine structure har (m) according to the following equation (17) using the pitch period T and the pitch gain β. Here, M represents the spectral resolution.

  Since the expression (17) becomes an oscillation filter when the absolute value of β is 1 or more, the range that the absolute value of β can take is limited to be less than a predetermined setting value (for example, 0.8) less than 1. There is also a method of providing.

The spectrum normalizer 506 uses the spectrum envelope env (m) obtained by the spectrum envelope calculator 502 and the spectrum fine structure har (m) obtained by the spectrum fine structure calculator 801 to use the following equation (18). Normalize according to

Also, the quantization bit allocation by the vector quantizer 509 is performed by dividing both the spectral envelope env (m) obtained by the spectral envelope calculator 502 and the spectral fine structure har (m) obtained by the spectral fine structure calculator 801. Use to determine. In addition, the spectral fine structure is also used to determine the weighting function w (m) at the time of vector quantization. Specifically, the weight function w (m) is defined according to the following equation (19). Here, p is a constant between 0 and 1, and Herz_to_Bark () is a function for converting the Herz scale to the Bark scale.

  As described above, the signal processing apparatus according to the present embodiment calculates the spectral fine structure using the pitch period encoded by the base layer encoder and decoded by the local decoder, and converts the spectral fine structure into the spectral structure. By utilizing it for normalization and vector quantization, quantization performance can be improved.

(Embodiment 4)
FIG. 9 is a block diagram showing a configuration of an enhancement layer encoder of the signal processing apparatus according to Embodiment 4 of the present invention. 5 identical to those in FIG. 5 are assigned the same reference numerals as in FIG. 5 and detailed descriptions thereof are omitted.

  The enhancement layer encoder 107 in FIG. 9 includes a power estimator 901 and a power fluctuation quantizer 902, and the local decoder 103 uses the encoded code obtained by the base layer encoder 102. The difference from the enhancement layer encoder of FIG. 5 is that a decoded signal is generated, the power of the MDCT coefficient is predicted from the decoded signal of the base layer using the decoded signal, and the amount of change from the predicted value is encoded.

The signal sl (n) decoded by the local decoder 103 in FIG. 5 is input to the power estimator 901. The power estimator 901 estimates the MDCT coefficient power from the decoded signal sl (n). When the estimated value of the power of the MDCT coefficient is powp, powp is expressed as the following equation (20). Here, N is the length of the decoded signal sl (n), and α is a predetermined constant for correction.

Further, in another method using the spectrum inclination obtained from the LPC coefficient of the base layer, the estimated value of the power of the MDCT coefficient is expressed by the following equation (21).

  Here, β represents a variable depending on the spectral tilt obtained from the LPC coefficient of the base layer. When the spectral tilt is large (relatively low power is present), β approaches zero and the spectral tilt is small ( Β has a property of approaching 1 when power is relatively high.

Next, the power fluctuation quantizer 902 normalizes the power of the MDCT coefficient obtained by the MCDT unit 503 with the power estimated value powp obtained by the power estimator 901, and quantizes the fluctuation. The fluctuation amount r is expressed by the following equation (22).

Here, pow indicates the power of the MDCT coefficient, and is calculated by Expression (23). Here, X (m) represents an MDCT coefficient, and M represents a frame length.

The power variation quantizer 902 quantizes the variation r, sends the encoded code to the multiplexer 510, and decodes the quantized variation rq. The power normalizer 505 normalizes the MDCT coefficient using the following equation (24) using the quantized variation rq. Here, X1 (m) represents the MDCT coefficient after power normalization.

  Thus, the signal processing apparatus of the present embodiment uses the correlation between the power of the decoded signal of the base layer and the power of the MDCT coefficient of the enhancement layer, and uses the decoded signal of the base layer to calculate the MDCT coefficient. By predicting the power and encoding the amount of variation from the predicted value, the number of bits required to quantize the power of the MDCT coefficient can be reduced.

(Embodiment 5)
FIG. 10 is a block diagram showing a configuration of a signal processing device according to Embodiment 5 of the present invention. 10 mainly includes a demultiplexer 1001, a base layer decoder 1002, an upsampler 1003, an enhancement layer decoder 1004, and an adder 1005.

  The demultiplexer 1001 separates the encoded code and generates a base layer encoded code and an enhancement layer encoded code. Then, the demultiplexer 1001 outputs the base layer encoded code to the base layer decoder 1002, and outputs the enhancement layer encoded code to the enhancement layer decoder 1004.

  Base layer decoder 1002 decodes the decoded signal of sampling rate FL using the base layer encoded code obtained by demultiplexer 1001, and outputs the decoded signal to upsampler 1003. At the same time, the parameters decoded by base layer decoder 1002 are output to enhancement layer decoder 1004. The upsampler 1003 raises the sampling frequency of the decoded signal to FH and outputs it to the adder 1005.

  The enhancement layer decoder 1004 decodes the decoded signal having the sampling rate FH using the enhancement layer encoded code obtained by the demultiplexer 1001 and the parameters decoded by the base layer decoder 1002, and adds the adder 1005. Output to.

  Adder 1005 performs vector addition of the decoded signal output from upsampling unit 1003 and the decoded signal output from enhancement layer decoder 1004.

  Next, the operation of the signal processing apparatus according to the present embodiment will be described. First, the code encoded in the signal processing apparatus according to any one of Embodiments 1 to 4 is input, and the demultiplexer 1001 separates the code to encode the base layer encoded code and the enhancement layer encoded Generate code.

  Next, base layer decoder 1002 decodes the decoded signal of sampling rate FL using the base layer encoded code obtained by demultiplexer 1001. Then, the upsampler 1003 raises the sampling frequency of the decoded signal to FH.

  The enhancement layer decoder 1004 decodes the decoded signal of the sampling rate FH using the enhancement layer encoded code obtained by the demultiplexer 1001 and the parameters decoded by the base layer decoder 1002.

  The base layer decoded signal up-sampled by the up-sampler 1003 and the enhancement layer decoded signal are added by an adder 1005. Then, the above process is repeated while a new input signal exists. If there is no new input signal, the process ends.

  As described above, the signal processing apparatus according to the present embodiment uses the decoding parameters in the base layer coding by decoding the enhancement layer decoder 1004 using the parameters decoded by the base layer decoder 1002. Thus, a decoded signal can be generated from the encoded code of the acoustic encoding means for encoding the enhancement layer.

  Next, the base layer decoder 1002 will be described. FIG. 11 is a block diagram illustrating an example of base layer decoder 1002. A base layer decoder 1002 in FIG. 11 mainly includes a demultiplexer 1101, a sound source generator 1102, and a synthesis filter 1103, and performs CELP decoding processing.

  The demultiplexer 1101 separates various parameters from the base layer encoded code output from the demultiplexer 1001 and outputs the separated parameters to the sound source generator 1102 and the synthesis filter 1103.

  The sound generator 1102 decodes the adaptive vector, the adaptive vector gain, the noise vector, and the noise vector gain, generates a sound source signal using these, and outputs the sound source signal to the synthesis filter 1103. The synthesis filter 1103 generates a synthesized signal using the decoded LPC coefficient.

  Next, the operation of base layer decoder 1002 in FIG. 11 will be described. First, the demultiplexer 1101 separates various parameters from the encoded code for the base layer.

Next, the sound source generator 1102 decodes the adaptive vector, the adaptive vector gain, the noise vector, and the noise vector gain. Then, the sound source generator 1102 generates a sound source vector ex (n) according to the following equation (25). Here, q (n) is an adaptive vector, β _q is an adaptive vector gain, c (n) is a noise vector, and γ _q is a noise vector gain.

Next, the synthesis filter 1103 generates a synthesized signal syn (n) according to the following equation (26) using the decoded LPC coefficient. Here, α _q represents the decoded LPC coefficient, and NP represents the order of the LPC coefficient.

  The decoded signal syn (n) decoded in this way is output to the upsampler 1003 and enhancement layer decoder 1004. Then, the above process is repeated while a new input signal exists. If there is no new input signal, the process ends. Depending on the configuration of CELP, there may be a form in which the synthesized signal is output after passing through a post filter. The post filter here has a post-processing function that makes it difficult to perceive encoding distortion.

  Next, the enhancement layer decoder 1004 will be described. FIG. 12 is a block diagram illustrating an example of enhancement layer decoder 1004. The enhancement layer decoder 1004 in FIG. 12 includes a demultiplexer 1201, an LPC coefficient decoder 1202, a spectrum envelope calculator 1203, a vector decoder 1204, a Bark scale shape decoder 1205, and a multiplier 1206. , A multiplier 1207, a power decoder 1208, a multiplier 1209, and an IMDCT unit 1210.

  The demultiplexer 1201 separates various parameters from the enhancement layer encoded code output from the demultiplexer 1001. The LPC coefficient decoder 1202 decodes the LPC coefficient using the encoded code related to the LPC coefficient, and outputs it to the spectrum envelope calculator 1203.

  The spectrum envelope calculator 1203 calculates a spectrum envelope env (m) according to the equation (6) using the decoded LPC coefficients, and outputs the spectrum envelope env (m) to the vector decoder 1204 and the multiplier 1207.

  The vector decoder 1204 determines the quantized bit allocation based on the spectral envelope env (m) obtained by the spectral envelope calculator 1203, and uses the encoded code obtained from the demultiplexer 1201 and the quantized bit allocation. The normalized MDCT coefficient X3q (m) is decoded. Note that the quantization bit allocation method is the same as that used in enhancement layer coding in any of the coding methods of the first to fourth embodiments.

  Bark scale shape decoder 1205 decodes Bark scale shape Bq (k) based on the encoded code obtained from demultiplexer 1201, and outputs the result to multiplier 1206.

Multiplier 1206 multiplies normalized MDCT coefficient X3q (m) and Bark scale shape Bq (k) according to the following equation (27), and outputs the multiplication result to multiplier 1207. Here, fl (k) represents the lowest frequency of the kth subband, fh (k) represents the highest frequency of the kth subband, and K represents the number of subbands.

The multiplier 1207 multiplies the normalized MDCT coefficient X2 (m) obtained from the multiplier 1206 by the spectrum envelope env (m) obtained by the spectrum envelope calculator 1203 according to the following equation (28), and the multiplication result is obtained. Output to the multiplier 1209.

  The power decoder 1208 decodes the power powq based on the encoded code obtained from the demultiplexer 1201 and outputs the decoding result to the multiplier 1209.

Multiplier 1209 multiplies normalized MDCT coefficient X1 (m) and decoding power powq according to the following equation (29), and outputs the multiplication result to IMDCT section 1210.

  The IMDCT unit 1210 performs an IMDCT transform (Modified Discrete Cosine Transform) on the decoded MDCT coefficient obtained in this manner, and adds the signal decoded in the previous frame and half of the analysis frame. Then, an output signal is generated, and this output signal is output to the adder 1005. Then, the above process is repeated while a new input signal exists. If there is no new input signal, the process ends.

  As described above, according to the signal processing apparatus of the present embodiment, decoding of the enhancement layer decoder is performed using the parameters decoded by the base layer decoder, thereby using the decoding parameters in the base layer coding. Thus, a decoded signal can be generated from the encoded code of the acoustic encoding means for encoding the enhancement layer.

(Embodiment 6)
FIG. 13 is a diagram illustrating an example of the configuration of enhancement layer decoder 1004. However, the same components as those in FIG. 12 are denoted by the same reference numerals as those in FIG. 12, and detailed description thereof is omitted.

  The enhancement layer decoder 1004 of FIG. 13 includes a conversion table 1301, an LPC coefficient mapping unit 1302, a spectrum envelope calculator 1303, and a modification unit 1304. The enhancement layer decoder 1004 receives the LPC coefficients decoded by the local decoder 103. It differs from the enhancement layer decoder 1004 in FIG.

  The conversion table 1301 stores the base layer LPC coefficients and the enhancement layer LPC coefficients in association with each other.

  LPC coefficient mapping section 1302 refers to conversion table 1301, converts the base layer LPC coefficients input from base layer decoder 1002 to enhancement layer LPC coefficients, and outputs the result to spectrum envelope calculator 1303.

  The spectrum envelope calculator 1303 obtains a spectrum envelope based on the LPC coefficients of the enhancement layer and outputs the spectrum envelope to the deforming unit 1304. The transformation unit 1304 transforms the spectrum envelope and outputs it to the multiplier 1207 and the vector decoder 1204. For example, as a modification method, there is a method represented by Expression (16) of the second embodiment.

  Next, the operation of enhancement layer decoder 1004 in FIG. 13 will be described. The LPC coefficient of the base layer is obtained for a signal whose signal band is 0 to FL, and does not match the LPC coefficient used for the signal (signal band 0 to FH) that is the target of the enhancement layer. However, there is a strong correlation between the two. Therefore, the LPC coefficient mapping unit 1302 separately designs a conversion table 1301 representing the correspondence between the LPC coefficients for signals in the signal bands 0 to FL and the LPC coefficients for signals in the signal bands 0 to FH by using this correlation. Keep it. By using this conversion table 1301, the LPC coefficient of the enhancement layer is obtained from the LPC coefficient of the base layer.

  Details of the conversion table 1301 are the same as those of the conversion table 601 of the second embodiment.

  Thus, according to the signal processing apparatus of the present embodiment, the enhancement layer LPC coefficients are obtained using the LPC coefficients quantized by the base layer decoder, and the spectral envelope is calculated from the enhancement layer LPC analysis. Thus, the need for LPC analysis and quantization is eliminated, and the number of quantization bits can be reduced.

(Embodiment 7)
FIG. 14 is a block diagram showing the configuration of the enhancement layer decoder of the signal processing apparatus according to Embodiment 7 of the present invention. However, the same components as those in FIG. 12 are denoted by the same reference numerals as those in FIG. 12, and detailed description thereof is omitted.

  The enhancement layer decoder 1004 of FIG. 14 includes a spectral fine structure calculator 1401, calculates a spectral fine structure using the pitch period decoded by the base layer decoder 1002, and decodes the spectral fine structure. 12 differs from the enhancement layer encoder of FIG. 12 in that acoustic decoding corresponding to acoustic encoding with improved quantization performance is used.

  The spectral fine structure calculator 1401 calculates a spectral fine structure from the pitch period T and the pitch gain β decoded by the base layer decoder 1002 and outputs them to the vector decoder 1204 and the multiplier 1207.

  Specifically, the pitch period T and the pitch gain β are part of the encoded code, and the same information can be obtained in an acoustic decoder not shown here. Therefore, even if encoding is performed using the pitch period T and the pitch gain β, the bit rate does not increase.

  The spectral fine structure calculator 1401 calculates the spectral fine structure har (m) according to the above equation (17) using the pitch period T and the pitch gain β.

Then, using the spectral envelope env (m) obtained by the spectral envelope calculator 1203 and the spectral fine structure har (m) obtained by the spectral fine structure calculator 1401, the quantization bit allocation by the vector decoder 1204 is performed. Is determined. Then, the normalized MDCT coefficient X3 (m) is decoded from the quantization bit allocation and the encoded code obtained from the demultiplexer 1201. Further, in the multiplier 1207, the normalized MDCT coefficient X1 (m) is obtained by multiplying the normalized MDCT coefficient X2 (m) by the spectral envelope env (m) and the spectral fine structure har (m) according to the following equation (30). It is done.

  As described above, the signal processing apparatus according to the present embodiment calculates the spectral fine structure using the pitch period encoded by the base layer encoder and decoded by the local decoder, and converts the spectral fine structure into the spectral structure. By making use of normalization and vector quantization, acoustic decoding corresponding to acoustic coding with improved quantization performance can be performed.

(Embodiment 8)
FIG. 15 is a block diagram showing the configuration of the enhancement layer decoder of the signal processing apparatus according to Embodiment 8 of the present invention. However, the same components as those in FIG. 12 are denoted by the same reference numerals as those in FIG. 12, and detailed description thereof is omitted.

  The enhancement layer decoder 1004 of FIG. 15 includes a power estimator 1501, a power change amount decoder 1502, and a power generator 1503, and predicts the power of MDCT coefficients using the decoded signal of the base layer. However, it differs from the enhancement layer decoder of FIG. 12 in that a decoder corresponding to the encoder that encodes the amount of change from the predicted value is configured.

  In FIG. 10, the decoded parameters are output from base layer decoder 1002 to enhancement layer decoder 1004. In this embodiment, the decoded signal obtained by base layer decoder 1002 The result is output to enhancement layer decoder 1004.

  The power estimator 1501 estimates the power of the MDCT coefficient from the decoded signal sl (n) decoded by the base layer decoder 1002 using Expression (20) or Expression (21).

  The power change amount decoder 1502 decodes the power change amount from the encoded code obtained from the demultiplexer 1201 and outputs it to the power generator 1503. The power generator 1503 calculates power from the power change amount.

The multiplier 1209 obtains the MDCT coefficient according to the following equation (31). Here, rq represents a decoded value of the power change amount, and powp represents a power estimated value. X1 (m) represents an output signal of the multiplier 1207.

  Thus, according to the signal processing apparatus of the present embodiment, it corresponds to the encoder that predicts the power of the MDCT coefficient using the decoded signal of the base layer and encodes the amount of change from the predicted value. By configuring the decoder, the number of bits necessary for the quantization of the power of the MDCT coefficients can be reduced.

(Embodiment 9)
Next, a ninth embodiment of the present invention will be described with reference to the drawings. FIG. 16 is a block diagram showing a configuration of an acoustic signal encoding device according to Embodiment 9 of the present invention. The signal processing device 1603 in FIG. 16 is characterized by being configured by one of the signal processing devices described in the first to fourth embodiments described above.

  As shown in FIG. 16, a communication device 1600 according to Embodiment 9 of the present invention includes an input device 1601, an A / D conversion device 1602, and a signal processing device 1603 connected to a network 1604.

  The A / D conversion device 1602 is connected to the output terminal of the input device 1601. An input terminal of the signal processing device 1603 is connected to an output terminal of the A / D conversion device 1602. An output terminal of the signal processing device 1603 is connected to the network 1604.

  The input device 1601 converts sound waves that can be heard by the human ear into analog signals, which are electrical signals, and supplies the analog signals to the A / D converter 1602. The A / D conversion device 1602 converts the analog signal into a digital signal and gives it to the signal processing device 1603. The signal processing device 1603 generates a code by encoding the input digital signal and outputs the code to the network 1604.

  As described above, according to the communication device of the embodiment of the present invention, it is possible to enjoy the effects as described in the first to fourth embodiments in communication, and to efficiently encode an acoustic signal with a small number of bits. An encoding device can be provided.

(Embodiment 10)
Next, a tenth embodiment of the present invention will be described with reference to the drawings. FIG. 17 is a block diagram showing the configuration of the acoustic signal decoding apparatus according to Embodiment 10 of the present invention. The signal processing device 1703 in FIG. 17 is characterized by being configured by one of the signal processing devices shown in the fifth to eighth embodiments described above.

  As shown in FIG. 17, a communication apparatus 1700 according to Embodiment 10 of the present invention includes a receiving apparatus 1702, a signal processing apparatus 1703, a D / A conversion apparatus 1704, and an output apparatus 1705 connected to a network 1701. is doing.

  An input terminal of the receiving device 1702 is connected to the network 1701. An input terminal of the signal processing device 1703 is connected to an output terminal of the receiving device 1702. The input terminal of the D / A conversion device 1704 is connected to the output terminal of the signal processing device 1703. The input terminal of the output device 1705 is connected to the output terminal of the D / A converter 1704.

  Receiving device 1702 receives a digital encoded acoustic signal from network 1701, generates a digital received acoustic signal, and provides it to signal processing device 1703. The signal processing device 1703 receives the received acoustic signal from the receiving device 1702, performs a decoding process on the received acoustic signal, generates a digital decoded acoustic signal, and supplies the digital decoded acoustic signal to the D / A conversion device 1704. The D / A conversion device 1704 converts the digital decoded audio signal from the signal processing device 1703 to generate an analog decoded audio signal, and provides it to the output device 1705. The output device 1705 converts an analog decoded acoustic signal, which is an electrical signal, into air vibrations and outputs the sound as sound waves to the human ear.

  As described above, according to the communication apparatus of the present embodiment, the effects as shown in the fifth to eighth embodiments described above can be enjoyed in communication, and an acoustic signal encoded efficiently with a small number of bits is decoded. Therefore, a good acoustic signal can be output.

(Embodiment 11)
Next, an eleventh embodiment of the present invention will be described with reference to the drawings. FIG. 18 is a block diagram showing the configuration of the acoustic signal transmission coding apparatus according to Embodiment 11 of the present invention. In the eleventh embodiment of the present invention, the signal processing device 1803 in FIG. 18 is constituted by one of the acoustic encoding means shown in the first to fourth embodiments described above. There are features of the form.

  As shown in FIG. 18, a communication device 1800 according to Embodiment 11 of the present invention includes an input device 1801, an A / D conversion device 1802, a signal processing device 1803, an RF modulation device 1804, and an antenna 1805.

  The input device 1801 converts sound waves that can be heard by the human ear into analog signals, which are electrical signals, and supplies the analog signals to the A / D converter 1802. The A / D conversion device 1802 converts an analog signal into a digital signal and gives it to the signal processing device 1803. The signal processing device 1803 encodes the input digital signal to generate an encoded acoustic signal, and supplies the encoded acoustic signal to the RF modulation device 1804. The RF modulation device 1804 modulates the encoded acoustic signal to generate a modulated encoded acoustic signal, and supplies the modulated encoded acoustic signal to the antenna 1805. The antenna 1805 transmits the modulation-coded acoustic signal as a radio wave.

  Thus, according to the communication apparatus of the present embodiment, it is possible to enjoy the effects as shown in the first to fourth embodiments described above in wireless communication, and efficiently encode an acoustic signal with a small number of bits. it can.

  Note that the present invention can be applied to a transmission device, a transmission encoding device, or an acoustic signal encoding device that uses an audio signal. The present invention can also be applied to a mobile station apparatus or a base station apparatus.

(Embodiment 12)
Next, an embodiment 12 of the invention will be described with reference to the drawings. FIG. 19 is a block diagram showing a configuration of an acoustic signal receiving / decoding apparatus according to Embodiment 12 of the present invention. In the twelfth embodiment of the present invention, the signal processing apparatus 1903 in FIG. 19 is constituted by one of the acoustic decoding means shown in the fifth to eighth embodiments described above. There are features of the form.

  As shown in FIG. 19, a communication device 1900 according to Embodiment 12 of the present invention includes an antenna 1901, an RF demodulation device 1902, a signal processing device 1903, a D / A conversion device 1904, and an output device 1905.

  The antenna 1901 receives a digital encoded acoustic signal as a radio wave, generates a digital received encoded acoustic signal of an electrical signal, and provides the RF demodulator 1902 with it. The RF demodulator 1902 demodulates the received encoded acoustic signal from the antenna 1901 to generate a demodulated encoded acoustic signal, and provides it to the signal processor 1903.

  The signal processing device 1903 receives the digital demodulated encoded acoustic signal from the RF demodulating device 1902, performs a decoding process, generates a digital decoded acoustic signal, and provides it to the D / A conversion device 1904. The D / A conversion device 1904 converts the digital decoded audio signal from the signal processing device 1903 to generate an analog decoded audio signal, and provides it to the output device 1905. The output device 1905 converts an analog decoded audio signal, which is an electrical signal, into air vibrations and outputs the sound as a sound wave to the human ear.

  As described above, according to the communication apparatus of the present embodiment, the effects as described in the fifth to eighth embodiments described above can be enjoyed in wireless communication, and an acoustic signal encoded efficiently with a small number of bits is decoded. Therefore, a good acoustic signal can be output.

  Note that the present invention can be applied to a receiving device, a receiving decoding device, or an audio signal decoding device using an audio signal. The present invention can also be applied to a mobile station apparatus or a base station apparatus.

  The present invention is not limited to the above-described embodiment, and can be implemented with various modifications. For example, although the case where the signal processing apparatus is used has been described in the above embodiment, the present invention is not limited to this, and the signal processing method may be performed as software.

  For example, a program for executing the signal processing method may be stored in advance in a ROM (Read Only Memory), and the program may be operated by a CPU (Central Processor Unit).

  A program for executing the above signal processing method is stored in a computer-readable storage medium, the program stored in the storage medium is recorded in a RAM (Random Access memory) of the computer, and the computer operates according to the program. You may make it let it.

  In the above description, MDCT transform is used for enhancement layer coding and IMDCT transform is used for enhancement layer decoding. However, the present invention is not limited to this, and any orthogonal transform method can be applied.

The block diagram which shows the structure of the signal processing apparatus which concerns on Embodiment 1 of this invention. The figure which shows an example of the component of an input signal The figure which shows an example of the signal processing method of the signal processing apparatus which concerns on the said embodiment The figure which shows an example of a structure of a base layer encoder The figure which shows an example of a structure of an enhancement layer encoder The figure which shows an example of a structure of an enhancement layer encoder The figure which shows an example of extended LPC coefficient calculation The block diagram which shows the structure of the enhancement layer encoder of the signal processing apparatus which concerns on Embodiment 3 of this invention. FIG. 9 is a block diagram showing the configuration of an enhancement layer encoder of a signal processing device according to Embodiment 4 of the present invention. The block diagram which shows the structure of the signal processing apparatus which concerns on Embodiment 5 of this invention. Block diagram illustrating an example of a base layer decoder Block diagram illustrating an example of an enhancement layer decoder The figure which shows an example of a structure of an enhancement layer decoder The block diagram which shows the structure of the enhancement layer decoder of the signal processing apparatus which concerns on Embodiment 7 of this invention. The block diagram which shows the structure of the enhancement layer decoder of the signal processing apparatus which concerns on Embodiment 8 of this invention. FIG. 9 is a block diagram showing a configuration of an acoustic signal encoding device according to Embodiment 9 of the present invention. FIG. 10 is a block diagram showing a configuration of an acoustic signal decoding apparatus according to Embodiment 10 of the present invention. Block diagram showing the configuration of an acoustic signal transmission encoding apparatus according to Embodiment 11 of the present invention. Block diagram showing the configuration of an acoustic signal receiving and decoding apparatus according to Embodiment 12 of the present invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 101 Downsampler 102 Base layer encoder 103 Local decoder 104,1003 Upsampler 105 Delayer 106 Subtractor 107 Enhancement layer encoder 1002 Base layer decoder 1004 Enhancement layer decoder 1005 Adder

Claims (4)

Base layer encoding means for encoding a low-frequency part, which is a band part lower than a predetermined frequency of an input signal, to obtain a first encoded code;
Local decoding means for decoding the first encoded code to generate a decoded signal;
Subtracting means for obtaining a subtraction signal by subtracting said decoded signal from said input signal,
A spectral characteristic calculation means for calculating a spectral characteristic of a filter formed by a parameter generated in the decoding process of the local decoding means, or a parameter obtained by converting the parameter for all bands;
Deformation means for modifying the spectral characteristics of the filter so that the quantization accuracy of the low-frequency part is lower than other bands ,
Vector quantization means for determining the bit allocation or vector search weight of vector quantization using the transformed spectral characteristics;
Enhancement layer encoding means for encoding the subtraction signal based on the bit allocation or the weight of the vector search to obtain a second encoded code;
An encoding device comprising: The spectrum characteristic calculation means uses an LPC coefficient among the parameters and calculates a spectral envelope of the entire band as the spectrum characteristic.
The encoding device according to claim 1. The spectral characteristic calculation means calculates a spectral fine structure of the entire band as the spectral characteristic using a pitch period and a pitch gain among the parameters.
The encoding device according to claim 1. The vector quantization means limits the bit allocation or the vector search weight so as not to exceed a predetermined upper limit value.
The encoding device according to any one of claims 1 to 3.

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