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Proceedings ArticleDOI

Multimode coding: application to CELP

TLDR
A novel approach to narrow- and medium-band speech coding that can dynamically balance the transmission rate between the excitation and the spectral parameters is introduced, improving the subjective speech quality.
Abstract
The authors introduce a novel approach to narrow- and medium-band speech coding that can dynamically balance the transmission rate between the excitation and the spectral parameters. The coding algorithm, called multimode coding, operates several coding blocks, each of which has a different bit assignment in parallel, and selects the optimum coding block frame by frame based on an evaluation of the reproduced speech quality. This coding algorithm is applied to 4.8 and 8.0 kb/s CELP coders, and 2.0-2.4 dB of SNRseg improvement is achieved over conventional CELP coders. The spectral distortion measure is added as an evaluation function, improving the subjective speech quality. >

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Citations
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PatentDOI

Variable rate vocoder

TL;DR: In this paper, a variable rate coding of frames of digitized speech samples is proposed, comprising the steps of determining a level of speech activity for a frame of digitised speech samples, selecting an encoding rate from a set of rates based upon the determined level of activity within said frame, and coding said frame according to a predetermined coding format for said selected rate wherein each rate has a corresponding different coding format.
Journal ArticleDOI

Speech coding: a tutorial review

TL;DR: The objective of this paper is to provide a tutorial overview of speech coding methodologies with emphasis on those algorithms that are part of the recent low-rate standards for cellular communications.
Journal ArticleDOI

Advances in speech and audio compression

TL;DR: Current activity in speech compression is dominated by research and development of a family of techniques commonly described as code-excited linear prediction (CELP) coding, which offer a quality versus bit rate tradeoff that significantly exceeds most prior compression techniques.
Proceedings ArticleDOI

Conditional entropy-constrained vector quantization of linear predictive coefficients

TL;DR: It is shown in the LPC case that when a conditional entropy coder is used i.e., when the entropy code used for the current codeword is conditioned on the previouscodeword, then a conditional version of entropy constrained vector quantizer (ECVQ) outperforms a conditional versions of the straightforward approach by over 27%.
Patent

Apparatus for quantizing linear predictive coding coefficients, sound encoding apparatus, apparatus for de-quantizing linear predictive coding coefficients, sound decoding apparatus, and electronic device therefore

TL;DR: In this paper, a quantization path determiner that determines a path from a first path not using interframe prediction and a second path using the inter-frame prediction, based on a criterion before quantization of the input signal, is provided.
References
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Proceedings ArticleDOI

Code-excited linear prediction(CELP): High-quality speech at very low bit rates

TL;DR: A code-excited linear predictive coder in which the optimum innovation sequence is selected from a code book of stored sequences to optimize a given fidelity criterion, indicating that a random code book has a slight speech quality advantage at low bit rates.
Journal ArticleDOI

ADPCM with a multiquantizer for speech coding

TL;DR: A speech coding algorithm with low complexity and a short processing delay is introduced and can be easily applied to 8-kb/s coding and extensible to variable-rate coding.
Proceedings ArticleDOI

A high-efficiency speech coding algorithm based on ADPCM with multi-quantizer

TL;DR: A new 8 to 9.6 kbps ADPCM-MQ coding algorithm that includes tree coding to improve the per-sample quantizing characteristic, and sub-band coding with high frequency band reconstruction to realize a lower bit rate coding is described.
Proceedings ArticleDOI

Stochastic Gaussian model for low-bit rate coding of LPC area parameters

TL;DR: A stochastic model of LPC-derived log areas that eliminates training of the codebook by constructing codebook entries from random sequences and shows that vector quantization using random codebooks can provide a SNR of 20 dB in quantizing 10 log area parameters with 28 bits/frame.