Vector Predictive Coding of Speech at 16 kbits/s

Cuperman, V.; Gersho, A.

doi:10.1109/tcom.1985.1096372

Cited by 157 publications

(43 citation statements)

References 22 publications

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“…A more comprehensive journal paper on the approach has been submitted for publication [9]. The major -.result of this study was that a performance comparable to the best obtainable by any waveform speech coder at the rate 16 Kb/s has been obtained for the first time using VQ.…”

Section: Predictive Vector Codingmentioning

confidence: 89%

Techniques for Vector Quantization.

Gersho¹

1984

Self Cite

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Section: Predictive Vector Codingmentioning

confidence: 89%

Techniques for Vector Quantization.

Gersho¹

1984

Self Cite

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“…Traditional memory-based quantization alternatives are e.g., differential pulse-code modulation (DPCM) [2], predictive VQ (PVQ) [6], [7], vector predictive quantization [8], [9], finite-state VQ (FSVQ) [10], and safety-net quantization [11]. Recent approaches are Gaussian mixture modeling (GMM) [12], and PSQ [3].…”

Section: A Previous Effortsmentioning

confidence: 99%

Power series quantization for noisy channels

Persson

Eriksson

2010

IEEE Trans. Commun.

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Abstract-A recently proposed method for transmission of correlated sources under noise-free conditions, power series quantization (PSQ), uses a separate linear or nonlinear predictor for each quantizer region, and has shown to increase performance compared to several common quantization schemes for sources with memory. In this paper, it is shown how to apply PSQ for transmission of a source with memory over a noisy channel.A channel-optimized PSQ (COPSQ) encoder and codebook optimization algorithms are derived. The suggested scheme is shown to increase performance compared with previous state-ofthe-art methods.Index Terms-Channel-optimized quantization, noisy channels, memory-based quantization, spectrum coding.

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“…Este artigo propoe uma nova tecnica de projeto de diciona rios de vetores esparsos baseada no esquema de excitacao multipulso [1], [4], e na tecnica LBG de treinamento [16]. o treinamento eexecutado em malha fechada, de modo ana logo ao metodo de treinamento de dicionario estocastico nao estruturado descrito em [7]. Diciondrio multipulso, ou sim plesmente dicionario :MP, e0 nome dado ao dicionario pro jetado com a tecnica aqui proposta.…”

Section: ~---J-----------------------_unclassified

“…e calculado 0 valor otimo para a, urn novo vetor-alvo para busca no dicionario fixo e definido como Y =x-aHbL · (6) Em seguida, identifica-se, entao, qual vetor-codigo do di cionario fixo rninirniza 0 erro Ily -,f3HcilV Pode ser mo strado que este vetor-codigo tern seu Indice dado por (7) e 0 ganho ,f3 deve ter 0 seguinte valor: …”

Section: Ew(n) A(z)unclassified

Dicionário Estocástico Multipulso para Codificadores CELP

Silva¹,

Alcaim²

1998

Journal of Communication and Information Systems

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Resumo -Este artigo apresenta uma nova tecnica de projeto de dicionarios de vetores esparsos para codificadores CELP (Code Excited Linear Prediction), baseada no esquema de ex citacao multipulso e no algoritmo LBG (Linde-Buzo-Gray) de treinamento. 0 dicionario resultante -denorninado multi pulso ou, simplesmente, :MP-possui as vantagens inerentes aos dicionarios esparsos convencionais. Seu grande merito e ter ainda a vantagem de poder ser otimizado atraves de urn procedimento de treinamento. Atraves de simulacoes, 0 di cionario :MP foi comparado com os dicionarios gaussiano e "vector-sum" (VS). Os resultados mostraram que, dentre os tres tipos de dicionario testados, 0 dicionario :MP e0 que tern melhor desempenho em termos da qualidade da voz codifi cada. Neste artigo, sao apresentadas tambem comparacoes quanta acomplexidade associada aos tres dicionarios, Abstract -This paper presents a new algorithm to design co debooks of sparse vectors for code excited linear prediction (CELP) speech encoders. The algorithm is based on multi pulse excitations and on the LBG codebook training algo rithm. The codebooks, which are referred to as multi pulse (:MP) codebooks, have the inherent advantages of sparse co debooks. Moreover, they can be optimized by a closed-loop training procedure. We present a comparative analysis of the:MP codebook with vector-sum (VS) and Gaussian code books. Simulation results show that the :MP codebook yields the best performance in terms of speech quality. Complexities of these codebooks are also compared.Palavras chaves -Codificacao de Voz, CELP, Otimizacao de Dicionario.

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Vector Predictive Coding of Speech at 16 kbits/s

Cited by 157 publications

References 22 publications

Techniques for Vector Quantization.

Techniques for Vector Quantization.

Power series quantization for noisy channels

Dicionário Estocástico Multipulso para Codificadores CELP

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