Plosive spotting with margin classifiers

Joseph Keshet, Dan Chazan, Ben Zion Bobrovsky

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

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 languageEnglish
Title of host publicationEUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology
EditorsBorge Lindberg, Henrik Benner, Paul Dalsgaard, Zheng-Hua Tan
PublisherInternational Speech Communication Association
Pages1637-1640
Number of pages4
ISBN (Electronic)8790834100, 9788790834104
StatePublished - 2001
Externally publishedYes
Event7th European Conference on Speech Communication and Technology - Scandinavia, EUROSPEECH 2001 - Aalborg, Denmark
Duration: 3 Sep 20017 Sep 2001

Publication series

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

Conference

Conference7th European Conference on Speech Communication and Technology - Scandinavia, EUROSPEECH 2001
Country/TerritoryDenmark
CityAalborg
Period3/09/017/09/01

Fingerprint

Dive into the research topics of 'Plosive spotting with margin classifiers'. Together they form a unique fingerprint.

Cite this