A high-performance linear predictor employing vector quantization in nonorthogonal domains. With application to speech

    Authors

    W. B. Mikhael;V. Krishnan

    Comments

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    Abbreviated Journal Title

    IEEE Trans. Circuits Syst. I-Fundam. Theor. Appl.

    Keywords

    LP model based speech coding; signal representation in multiple; nonorthogonal domains; vector quantization; BASIS IMAGES; REPRESENTATION; Engineering, Electrical & Electronic

    Abstract

    Linear prediction (LP) is a powerful technique for efficient source-system model based representation of signals, such as speech, and video, with useful applications including compression, and recognition. This has been found to be particularly true when vector quantization is used to code the linear predictor coefficients. Recently, signal processing in multiple nonorthogonal domains has been reported that further enhances the efficiency of signal representation. In this contribution, a novel LP model based coding technique is presented where the advantages of multiple nonorthogonal domain representations of the LP coefficients and the prediction residuals are exploited in conjunction with vector quantization to yield considerable LP coding enhancement. The proposed signal coding technique is applied to one of the most commonly used signals, namely, speech. The resulting performance improvement is clearly demonstrated in terms of reconstruction quality for the same bit rate compared to the existing single domain vector quantization techniques.

    Journal Title

    Ieee Transactions on Circuits and Systems I-Fundamental Theory and Applications

    Volume

    50

    Issue/Number

    6

    Publication Date

    1-1-2003

    Document Type

    Article

    Language

    English

    First Page

    754

    Last Page

    762

    WOS Identifier

    WOS:000183877700003

    ISSN

    1057-7122

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