Plosive spotting with margin classifiers

Joseph Keshet; Dan Chazan; Ben Zion Bobrovsky

Plosive spotting with margin classifiers

Joseph Keshet, Dan Chazan, Ben Zion Bobrovsky

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper presents a novel algorithm for precise spotting of plosives. The algorithm is based on a pattern matching technique implemented with margin classifiers, such as support vector machines (SVM). A special hierarchical treatment to overcome the problem of fricative and false silence detection is presented. It uses the loss-based multi-class decisions. Furthermore, a method for smoothing the overall decisions by sequential linear programming is described. The proposed algorithm was tested on the TIMIT corpus, which produced a very high spotting accuracy. The algorithm presented here is applied to plosives detection, but can easily be adapted to any class of phonemes.

Original language	English
Title of host publication	EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology
Editors	Borge Lindberg, Henrik Benner, Paul Dalsgaard, Zheng-Hua Tan
Publisher	International Speech Communication Association
Pages	1637-1640
Number of pages	4
ISBN (Electronic)	8790834100, 9788790834104
State	Published - 2001
Event	7th European Conference on Speech Communication and Technology - Scandinavia, EUROSPEECH 2001 - Aalborg, Denmark Duration: 3 Sep 2001 → 7 Sep 2001

Publication series

Name	EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology

Conference

Conference	7th European Conference on Speech Communication and Technology - Scandinavia, EUROSPEECH 2001
Country/Territory	Denmark
City	Aalborg
Period	3/09/01 → 7/09/01

Cite this

Keshet, J., Chazan, D., & Bobrovsky, B. Z. (2001). Plosive spotting with margin classifiers. In B. Lindberg, H. Benner, P. Dalsgaard, & Z-H. Tan (Eds.), EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology (pp. 1637-1640). (EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology). International Speech Communication Association.

Keshet, Joseph ; Chazan, Dan ; Bobrovsky, Ben Zion. / Plosive spotting with margin classifiers. EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology. editor / Borge Lindberg ; Henrik Benner ; Paul Dalsgaard ; Zheng-Hua Tan. International Speech Communication Association, 2001. pp. 1637-1640 (EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology).

@inproceedings{b734bfb65c3d4eb48aa3f9f151aef88f,

title = "Plosive spotting with margin classifiers",

abstract = "This paper presents a novel algorithm for precise spotting of plosives. The algorithm is based on a pattern matching technique implemented with margin classifiers, such as support vector machines (SVM). A special hierarchical treatment to overcome the problem of fricative and false silence detection is presented. It uses the loss-based multi-class decisions. Furthermore, a method for smoothing the overall decisions by sequential linear programming is described. The proposed algorithm was tested on the TIMIT corpus, which produced a very high spotting accuracy. The algorithm presented here is applied to plosives detection, but can easily be adapted to any class of phonemes.",

author = "Joseph Keshet and Dan Chazan and Bobrovsky, {Ben Zion}",

year = "2001",

language = "אנגלית",

series = "EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology",

publisher = "International Speech Communication Association",

pages = "1637--1640",

editor = "Borge Lindberg and Henrik Benner and Paul Dalsgaard and Zheng-Hua Tan",

booktitle = "EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology",

note = "null ; Conference date: 03-09-2001 Through 07-09-2001",

}

Keshet, J, Chazan, D & Bobrovsky, BZ 2001, Plosive spotting with margin classifiers. in B Lindberg, H Benner, P Dalsgaard & Z-H Tan (eds), EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology. EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology, International Speech Communication Association, pp. 1637-1640, 7th European Conference on Speech Communication and Technology - Scandinavia, EUROSPEECH 2001, Aalborg, Denmark, 3/09/01.

Plosive spotting with margin classifiers. / Keshet, Joseph; Chazan, Dan; Bobrovsky, Ben Zion.

EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology. ed. / Borge Lindberg; Henrik Benner; Paul Dalsgaard; Zheng-Hua Tan. International Speech Communication Association, 2001. p. 1637-1640 (EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - This paper presents a novel algorithm for precise spotting of plosives. The algorithm is based on a pattern matching technique implemented with margin classifiers, such as support vector machines (SVM). A special hierarchical treatment to overcome the problem of fricative and false silence detection is presented. It uses the loss-based multi-class decisions. Furthermore, a method for smoothing the overall decisions by sequential linear programming is described. The proposed algorithm was tested on the TIMIT corpus, which produced a very high spotting accuracy. The algorithm presented here is applied to plosives detection, but can easily be adapted to any class of phonemes.

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Keshet J, Chazan D, Bobrovsky BZ. Plosive spotting with margin classifiers. In Lindberg B, Benner H, Dalsgaard P, Tan Z-H, editors, EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology. International Speech Communication Association. 2001. p. 1637-1640. (EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology).

Plosive spotting with margin classifiers

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