NDLI: A 3.3kbps CWI speech coding algorithm based on biothogonal wavelet transform

Content Provider	IEEE Xplore Digital Library
Author	Jing Wang Sheng-Hui Zhao Jing-Ming Kuang
Copyright Year	2007
Description	Author affiliation: Beijing Inst. of Technol., Beijing (Jing Wang; Sheng-Hui Zhao; Jing-Ming Kuang)
Abstract	This paper presents a 3.3kbps Characteristic Waveform Interpolation (CWI) speech coding algorithm based on biorthogonal Wavelet Transform (WT). The amplitude spectral surface of characteristic waveforms is decomposed into a series of reduced time resolution surfaces with B-spline biorthogonal wavelet filter banks. This multi-scale characteristic leads to more efficient quantization by exploiting each surface's perceptual importance and inherent transmission rate requirements. At the CWI encoder, the complex alignment operation is removed and the amplitude spectrum is decomposed without phase spectrum. At the decoder, different scale space is reconstructed separately and random or fixed phase is combined to the spectrum based on voiced degree. Compared with traditional CWI algorithm using lowpass filtering CW decomposition, the proposed WT-CWI algorithm can get lower coding rate and improve coding result. Subjective A-B listening tests indicate that the synthesis speech quality of the proposed 3.3kbps WT-CWI coding algorithm is far better than that of traditional 4.25kbit/s CWI speech coder.
Starting Page	408
Ending Page	411
File Size	204804
Page Count	4
File Format	PDF
ISBN	9781424410651
DOI	10.1109/ICWAPR.2007.4421718
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-11-02
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wavelet transforms wavelet transform Quantization characteristic waveform decomposition waveform interpolation Speech synthesis Spline Interpolation Surface reconstruction Speech coding Surface waves Filtering algorithms Filter bank voiced degree
Content Type	Text
Resource Type	Article

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