Address-vector quantisation applied to speech coding

Srinonchat, Jakkree; Danaher, S.; Murray, Alan F.

doi:10.1109/isspit.2003.1341228

Cited by 4 publications

(3 citation statements)

References 6 publications

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“…Most of the very low bit rate speech coders are based on the prediction parameters model, known as Linear Predictive Coder (LPC), which in this model the short-term speech spectrum is modelled by an all-pole filter [2,3]. However, the LPC parameters are not very efficient for quantisation [4]. In order to the LPC parameters have no bound, so is difficult to define quantization region.…”

Section: Line Spectrum Pairsmentioning

confidence: 99%

New Technique to Reduce Bit Rate of LPC-10 Speech Coder

Srinonchat

2006

TENCON 2006 - 2006 IEEE Region 10 Conference

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There are different optimisation criteria in the design of speech compression algorithms and in development speech coding system. Linear predictive coder (LPC) parameters are widely used in a various speech coding method. Line spectrum pairs (LSP), as alternate representation of LPC presents some useful properties for quantisation and transmission. This work investigates and proposes an efficient new technique and parameters to reduce the bit rate while maintain the reconstruct speech as the original speech in the LPC-10 speech code. The new technique is based on the LSP parameters and vector quantisation technique. The results of this experiments show that this technique can reduce the bit rate by around 2 -66% and also provides the excellent formant frequency similar to the original speech.

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Section: Line Spectrum Pairsmentioning

confidence: 99%

New Technique to Reduce Bit Rate of LPC-10 Speech Coder

Srinonchat

2006

TENCON 2006 - 2006 IEEE Region 10 Conference

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“…The purpose of this paper is to propose a new vocoder with a better compression rate than AMR 7.4Kbit/s mode under the speaker dependent environment. The Speaker Dependent Coding System(SDSC) [10] has designed for a particular speaker by traing speech samples of the speaker. The Centroid Neural Network as an unsupervised learning algorithm is proposed for training speech signals for SDSC in this paper.…”

Section: Introductionmentioning

confidence: 99%

A New Vocoder based on AMR 7.4kbit/s Mode in Speaker Dependent Coding System

Huong

Min

Park

et al. 2008

2008 Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed

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A new Code Excited Linear Predictive (CELP) vocoder based on Adaptive Multi Rate (AMR) 7.4kbit/s mode is proposed in this paper. The proposed vocoder achieves a better compression rate in an environment of Speaker Dependent Coding System (SDSC) and is efficiently used for systems, such as OGM(Outgoing message) and TTS(Text To Speech), that stores the speech data of a particular speaker. In order to enhance the compression rate of a coder, a new Line Spectral Pairs(LSP) codebook is employed by using Centroid Neural Network (CNN) algorithm. Moreover, applying the predicted pulses used in fixed code book searching enhances the quality of synthesis speech. In comparison with original (traditional) AMR 7.4 Kbit/s coder, the new coder shows a superior compression rate and an equivalent quality to AMR coder in term of informal subjective testing Mean Opinion Score(MOS).

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“…Speech signals were modelled in form of the LPC and LSP coefficients [6] [7]. Then these coefficients classified and clustered into the clustering codebooks.…”

Section: Performancementioning

confidence: 99%

Improvement of the Clustering Technique to Design a Codebook in Speech Coding

Srinonchat

2005 5th International Conference on Information Communications &Amp; Signal Processing

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Clustering algorithms are used in data compression or coding to classify data into groups with similar properties. This paper studies a new clustering technique aimed at enhancing the performance of the cluster process to provide more accuracy and also endeavours to use as few cluster centres as possible to represent the data group. Two clustering methods are studied here and applied to the speech signal. The results show that the new cluster technique can reduce the number of cluster centres, used to represent the speech signals, up to maximum 45% without significantly degrading the speech quality in speech coding system.

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Address-vector quantisation applied to speech coding

Cited by 4 publications

References 6 publications

New Technique to Reduce Bit Rate of LPC-10 Speech Coder

New Technique to Reduce Bit Rate of LPC-10 Speech Coder

A New Vocoder based on AMR 7.4kbit/s Mode in Speaker Dependent Coding System

Improvement of the Clustering Technique to Design a Codebook in Speech Coding

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