Data processing: speech signal processing – linguistics – language – Speech signal processing – For storage or transmission
Patent
1996-03-11
2000-05-09
Hudspeth, David R.
Data processing: speech signal processing, linguistics, language
Speech signal processing
For storage or transmission
G10L 302
Patent
active
060616490
DESCRIPTION:
BRIEF SUMMARY
TECHNICAL FIELD
This invention relates to a signal encoding method and apparatus for encoding input signals, such as audio data, by high-efficiency encoding, a recording medium having the high-efficiency encoded data recorded thereon, a signal transmitting method for transmitting the high-efficiency encoded signals and a signal decoding method and apparatus for decoding the encoded signals transmitted over a transmission channel or reproduced from a recording medium.
BACKGROUND OF THE INVENTION
There are a variety of techniques for high efficiency encoding of audio or speech signals. Examples of these techniques include transform coding in which a frame of digital signals representing the audio signal on the time axis is converted by an orthogonal transform into a block of spectral coefficients representing the audio signal on the frequency axis, and a sub-band coding in which the frequency band of the audio signal is divided by a filter bank into a plurality of sub-bands without forming the signal into frames along the time axis prior to coding. There is also known a combination of sub-band coding and transform coding, in which digital signals representing the audio signal are divided into a plurality of frequency ranges by sub-band coding, and transform coding is applied to each of the frequency ranges.
Among the filters for dividing a frequency spectrum into a plurality of equal-width frequency ranges include the quadrature mirror filter (QMF) as discussed in R. E. Crochiere, Digital Coding of Speech in Sub-bands, 55 Bell Syst. Tech J. No. 8 (1976). With such QMF filter, the frequency spectrum of the signal is divided into two equal-width bands. With the QMF, aliasing is not produced when the frequency bands resulting from the division are subsequently combined together.
In "Polyphase Quadrature Filters--A New Subband Coding Technique", Joseph H. Rothweiler ICASSP 83, Boston, there is shown a technique of dividing the frequency spectrum of the signal into equal-width frequency bands. With the present polyphase QMF, the frequency spectrum of the signals can be divided at a time into plural equal-width frequency bands.
There is also known a technique of orthogonal transform including dividing the digital input audio signal into frames of a predetermined time duration, and processing the resulting frames using a discrete Fourier transform (DFT), discrete cosine transform (DCT) and modified DCT (MDCT) for converting the signal from the time axis to the frequency axis. Discussions on MDCT may be found in J. P. Princen and A. B. Bradley, Subband Transform Coding Using Filter Bank Based on Time Domain Aliasing Cancellation", ICASSP 1987.
By quantizing the signals divided on the band basis by the filter or orthogonal transform, it becomes possible to control the band subjected to quantization noise and psychoacoustically more efficient coding may be performed by utilizing the so-called masking effects. If the signal components are normalized from band to band with the maximum value of the absolute values of the signal components, it becomes possible to effect more efficient coding.
In a technique of quantizing the spectral coefficients resulting from an orthogonal transform, it is known to use sub bands that take advantage of the psychoacoustic characteristics of the human auditory system. That is, spectral coefficients representing an audio signal on the frequency axis may be divided into a plurality of critical frequency bands. The width of the critical bands increase with increasing frequency. Normally, about 25 critical bands are used to cover the audio frequency spectrum of 0 Hz to 20 kHz. In such a quantizing system, bits are adaptively allocated among the various critical bands. For example, when applying adaptive bit allocation to the spectral coefficient data resulting from MDCT, the spectral coefficient data generated by the MDCT within each of the critical bands is quantized using an adaptively allocated number of bits.
There are presently known the following two bit allocation techniques. For ex
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Miyamori Shinji
Oikawa Yoshiaki
Tsutsui Kyoya
Ueno Masatoshi
Hudspeth David R.
Sofocleous M. David
Sony Corporation
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