Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/33790
Title: Speech synthesis from surface electromyogram signal
Authors: Lam, YM
Mak, MW 
Leong, PHW
Keywords: Fourier transforms
Electromyography
Linear predictive coding
Speech coding
Issue Date: 2005
Publisher: IEEE
Source: Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005, 21-21 December 2005, Athens, p. 749-754 How to cite?
Abstract: This paper presents a methodology that uses surface electromyogram (SEMG) signals recorded from the cheek and chin to synthesize speech. Simultaneously recorded speech and SEMG signals are blocked into frames and transformed into features. Linear predictive coding (LPC) and short-time Fourier transform coefficients are chosen as speech and SEMG features respectively. A neural network is applied to convert SEMG features into speech features on a frame-by-frame basis. The converted speech features are used to reconstruct the original speech. Feature selection, conversion methodology and experimental results are discussed. The results show that phoneme-based feature extraction and frame-based feature conversion could be applied to SEMG-based continuous speech synthesis
URI: http://hdl.handle.net/10397/33790
ISBN: 0-7803-9313-9
DOI: 10.1109/ISSPIT.2005.1577192
Appears in Collections:Conference Paper

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