Signal encoding method, signal encoding apparatus, signal decodi

Data processing: speech signal processing – linguistics – language – Speech signal processing – For storage or transmission

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Details

704224, 704230, G10L 302, G10L 900

Patent

active

057783390

DESCRIPTION:

BRIEF SUMMARY
TECHNICAL FIELD

This invention relates to a signal encoding method and a signal encoding apparatus for encoding digital signals such as speech, audio or picture signals, etc., a signal decoding method and a signal decoding apparatus for decoding such encoded signal, and a recording medium adapted so that which such encoded signals are recorded therein.


BACKGROUND ART

As a sort of efficient encoding techniques for efficiently carrying out bit compression of time series sample data signals such as audio signals, etc. to encode them, transform encoding using so called spectrum transform processing is known. This transform encoding carries out spectrum transform processing of input signals in block units to encode them. As the representative of this spectrum transform processing, Discrete Cosine Transform (DCT) processing is known.
In such transform encoding, a block distortion such that discontinuous connection (joint) portions between blocks are perceived as noise is in question. To lessen such a block distortion, a method of allowing the end portion of a block to overlap with the adjacent blocks is generally carried out.
In the case of the so called Modified Discrete Cosine Transform (MDCT), since there is employed an approach in which, while allowing an arbitrary block and blocks adjoining in both directions to overlap with each other respectively by halves (half blocks), no double transmission is carried out with respect to samples of the overlap portions, MDCT is suitable for efficient encoding.
Encoding and decoding using such MDCT and IMDCT which is the inverse transform processing thereof are disclosed in, e.g., Mochizuki, Yano, Nishitani "Filter Constraint of Plural Block Size Mixed MDCT", Technical Report of the Institute of Electronics and Communication Engineers of Japan, CAS 90-10, DSP 90-14, pp. 55-60, or Hazu, Sugiyama, Iwatare, Nishitani "Adaptive Block Length Adaptive Transform Coding using MDCT (ATC-ABS)", Institute of Electronics and Information Engineers of Japan, Spring General Meeting Lecture Collection (1990), A-197, etc. Such encoding and decoding will be briefly described below with reference to FIG. 1.
In FIG. 1, an arbitrary block, e.g., the J-th block of time series sample data overlaps with the (J-1)-th block and the (J+1)-th block by halves (50%). When the number of samples of the J-th block is assumed to be N (N is natural number), the J-th block has overlap portion of N/2 number of samples between the J-th block and the (J-1) block, and also has overlap portion of N/2 samples between the J-th block and the (J+1)-th block. Pre-processing filter or window Wh for transform processing is applied to samples of these respective blocks, e.g., arbitrary input time series sample 101 of the J-th block to obtain N number of time series data 102.
As the characteristic of a pre-processing filter or the window Wh for transform processing, the degree of power concentration of data obtained by the transform processing becomes highest is selected in correspondence with the statistical property of an input signal. Then, linear transform processing of MDCT is implemented to time series data 102 of N samples, whereby N/2 number of independent spectrum data 103 on the frequency base which is one half of the number of input samples are obtained. Linear inverse transform processing of IMDCT is implemented to the N/2 number of spectrum data 103 to thereby obtain (reproduce) N number of time series data 104. Synthesis filter or window Wf for inverse transform processing is applied to the time series data 104 to obtain time series data 105 thereafter to add it to output results of blocks before and after thus to restore (reconstruct) original input time series sample data.
In the conventional efficient encoding, there has been employed a method of dividing spectrum data 103 obtained in a manner as described above into several units, at every band, to normalize data at each respective units, and to re-quantize data by taking the characteristic from a viewpoint of the hearing sense into consideration

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Hans Georg Musmnn, "The ISO Coding Standard", GLOBECOM '90, IEEE, pp. 511-517.

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