Data processing of a bitstream signal

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

Reexamination Certificate

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C704S211000, C704S212000, C341S076000, C341S077000, 37, 37

Reexamination Certificate

active

06289306

ABSTRACT:

FIELD OF THE INVENTION
BACKGROUND OF THE INVENTION
The invention relates to: a data processing apparatus for data processing an audio signal, to a data processing method, a transmitter comprising the data processing apparatus, a transmitter in the form of a recording apparatus, a record carrier, to second data processing apparatus for reconverting an input signal into a replica of the audio signal, to a receiver including the second data processing apparatus, and to a receiver in the form of a reproducing apparatus and to a transmission signal including a data compressed residual bitstream signal.
Data processing an audio signal is well known in the art. Reference is made in this respect to EP-A 402,973, document D1 . The document describes a subband coder, in which an audio signal is A/D converted with a specific sampling frequency, such as 44.1 kHz, and the resulting samples in the form of eg. 24 bits wide words of the audio signal, are supplied to a subband splitter filter. The subband splitter filter splits the wideband digital audio signal into a plurality of relatively narrow band subband signals. Using a psycho acoustic model, a masked threshold is derived and blocks of samples of the subband signals are subsequently quantised with a specific number of bits per sample for each block of the subband signals, in response to the masked threshold, resulting in a significant data compression of the audio signal to be transmitted. The data compression carried out is based on ‘throwing away’ those components in the audio signal that are inaudible and is thus a lossy compression method. The data compression described in document D1 is a rather intelligent data compression method and requires a substantial number of gates or instructions, when implemented in hardware or software respectively, so that it is expensive. Moreover, the subsequent expansion apparatus also requires a substantial number of gates or instructions, when realized in hardware or software respectively. Those skilled in the art are directed to: “A digital decimating filter for analog-to-digital conversion of hi-fi audio signals”, by J. J. van der Kam in Philips Techn. Rev. 42, no. 6/7, April 1986, pp. 230-8, document D2; “A higher order topology for interpolative modulators for oversampling A/D converters”, by Kirk C. H. Chao et al in IEEE Trans. on Circuits and Systems, Vol 37, no. 3, March 1990, pp. 309-18, document D3; “A method for the construction of minimum-redundancy codes”, by D. A. Huffman in Proc. of the IRE, Vol. 40(10), September 1952, document D4; “An introduction to arithmetic coding” by G. G. Langdon, IBM J. Res. Develop., Vol. 28(2), March 1984, document D5; “A universal algorithm for sequential data compression” by J. Ziv et al, IEEE Trans. on Inform. Theory, Vol. IT-23, 1977, document D6; EP patent application no. 96202807.2, filing date Oct. 10, 1996 (PHN 16.029), document D7.
The above citations are hereby incorporated in whole by reference.
SUMMARY OF THE INVENTION
The invention aims at providing a data processing apparatus for processing an audio signal such that it can be data compressed by a lossless coder in a relatively simple way. Further, the invention aims at providing a corresponding data processing apparatus for reconverting the processed bitstream signal into a replica of the audio signal.
The data processing apparatus in accordance with the invention includes
input apparatus for receiving the audio signal,
conversion apparatus for carrying out a conversion on the audio signal so as to obtain a 1-bit bitstream signal, the conversion means includes sigma-delta modulator means,
prediction apparatus for carrying out a prediction step on a signal so as to obtain a predicted bitstream signal,
signal combination apparatus for combining the bitstream signal and the predicted bitstream signal so as to obtain a residual bitstream signal, and
output apparatus for supplying the residual bitstream signal.
The invention is based on the following recognition. Bitstream signals take up a considerable amount of capacity. To illustrate this: in a current proposal for a new standard for an optical audio disk, the disk will contain two channels of bitstream converted audio signals, sampled at 64.f
s
, where f
s
=44.1 kHz. This corresponds to a rate four times higher than a current CD audio disk. As discussed in an earlier filed but not yet published patent application no. 96202807.2 in the name of applicant, document D7, already low complexity lossless coding algorithms, such as fixed Huffman table coding, are able to reduce this capacity to a certain extent. Experiments have revealed that even higher lossless compression ratios can be obtained using more sophisticated, more complex algorithms, such as Lempel-Ziv.
Mainly in audio/speech coding, linear prediction is known to be a powerful technique. By removing redundancy from a speech/audio signal prior to quantization, the entropy of signal after quantization can be significantly reduced. The signals at the input and output of a predictor are either in a floating point or a multi bit representation.
In lossless coding of bitstream signals, the complexity of the algorithm, especially at the decoder side is of importance. However, generally, the performance of the lossless coding algorithm is closely related to its complexity.
In accordance with the invention, prediction is used on bitstream signals. ie. signals with only two different representation symbols, either ‘0’ or ‘1’. This has the advantage of an increase of lossless compression performance, for only a marginal extra complexity.
Experiments have revealed that even a third order prediction has considerable effect on the statistics of the resulting signal. By means of prediction already, as a preprocessing step, prior to data compression, the probability of a ‘1’-bit can be brought down from 50% to about 20%. The effect of this is that the output of the apparatus in accordance with the invention contains long runs of ‘zeroes’, which can be exploited by simple Huffman coding or run-length coding.
The audio signal can be applied in analog form or in digital form. When AID converting, in accordance with the invention, an analog audio signal with a 1-bit A/D converter (also named: bitstream converter or sigma-delta modulator), the audio signal to be A/D converted is sampled with a frequency which is generally a multiple of the frequency of 44.1 kHz or 48 kHz. The output signal of the 1-bit A/D converter is a binary signal, named bitstream signal. When the audio signal is supplied in digital form, sampled at eg. 44.1 kHz, the samples being expressed in eg. 16 bits per sample, this digital audio signal is oversampled with a frequency which is again a multiple of this sampling frequency of 44.1 kHz (or 48 kHz), which results in the 1-bit bitstream signal.
Converting an audio signal into a 1-bit bitstream signal has a number of advantages. Bitstream conversion is a high quality encoding method, with the possibility of a high quality decoding or a low quality decoding with the further advantage of a simpler decoding circuit. Reference is made in this respect to the publications “A digital decimating filter for analog-to-digital conversion of hi-fi audio signals”, by J. J. van der Kam, document D2 above, and “A higher order topology for interpolative modulators for oversampling A/D converters”, by Kirk C. H. Chao et al, document D3 in the
1-bit D/A converters are used in CD players, as an example, to reconvert the bitstream audio signal into an analog audio signal. The audio signal recorded on a CD disk is however not data compressed, prior to recording on the disk.
It is well known in the art that the resulting bitstream signal of the 1-bit A/D converter is, roughly, a random signal which has a ‘noisy-like’ frequency spectrum. Such types of signals are hard to data compress.
Surprisingly, however, it was established that by applying a prediction step, prior to data compression, eg. using a lossless coder, a significant data reduction could be obtained, in spite of the noisy character of the b

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