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Signal representation for speech sep...

Huang, Ying.

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Signal representation for speech separation.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Signal representation for speech separation./
Author:	Huang, Ying.
Description:	115 p.
Notes:	Source: Masters Abstracts International, Volume: 43-06, page: 2340.
Contained By:	Masters Abstracts International43-06.
Subject:	Engineering, Electronics and Electrical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR01819
ISBN:	9780494018194

Signal representation for speech separation.
Huang, Ying.

Signal representation for speech separation. - 115 p.

Source: Masters Abstracts International, Volume: 43-06, page: 2340.

Thesis (M.Sc.)--University of Guelph (Canada), 2005.

The development of next-generation speech enhancement systems depends on new forms of speech representation that can capture the non-stationarity of speech signal in a way amiable to element-based signal separation processing. Research in this thesis focuses on developing new structure-revealing signal representations that can meet this challenge. The idea is first investigated in developing a Gabor-atom based time-frequency component signal representation. Problems encountered in this stage of investigation lead to the main focal point of the research: the development of a new chirp-decomposition method suitable for speech-like multi-component signal analysis. Research starts from polynomial phase signal (PPS) analysis, followed by studying the complex ambiguity function (CAF) time-frequency distribution for chirp detection. Two new chirp detection algorithms are proposed. One is the principal-chirp Wigner-Hough (PC-WH) transform and another one is the ambiguity auto-term ridge (AAR) detection algorithm. The potential for using the resulting chirp-graph for speech separation is demonstrated in a new speech enhancement system.

ISBN: 9780494018194Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Signal representation for speech separation.
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245 1 0 $a Signal representation for speech separation.
300 $a 115 p.
500 $a Source: Masters Abstracts International, Volume: 43-06, page: 2340.
502 $a Thesis (M.Sc.)--University of Guelph (Canada), 2005.
520 $a The development of next-generation speech enhancement systems depends on new forms of speech representation that can capture the non-stationarity of speech signal in a way amiable to element-based signal separation processing. Research in this thesis focuses on developing new structure-revealing signal representations that can meet this challenge. The idea is first investigated in developing a Gabor-atom based time-frequency component signal representation. Problems encountered in this stage of investigation lead to the main focal point of the research: the development of a new chirp-decomposition method suitable for speech-like multi-component signal analysis. Research starts from polynomial phase signal (PPS) analysis, followed by studying the complex ambiguity function (CAF) time-frequency distribution for chirp detection. Two new chirp detection algorithms are proposed. One is the principal-chirp Wigner-Hough (PC-WH) transform and another one is the ambiguity auto-term ridge (AAR) detection algorithm. The potential for using the resulting chirp-graph for speech separation is demonstrated in a new speech enhancement system.
590 $a School code: 0081.
650 4 $a Engineering, Electronics and Electrical. $3 626636
690 $a 0544
710 2 0 $a University of Guelph (Canada). $3 1018650
773 0 $t Masters Abstracts International $g 43-06.
790 $a 0081
791 $a M.Sc.
792 $a 2005
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