Distinctive feature based SVM discriminant features for improvements to phone recognition on telephone band speech

Research output: Contribution to conferencePaper

Abstract

Support vector machines (SVM's) can be trained to classify manner transitions between phones and to identify the place of articulation of any given phone with high accuracy. The discriminant outputs of these SVM's can be used as input features for a standard ASR system. There is a significant improvement in correctness and accuracy using these SVM discriminant features when compared to an MFCC based recognizer of equal parameters.

Original languageEnglish (US)
Pages697-700
Number of pages4
StatePublished - Dec 1 2005
Event9th European Conference on Speech Communication and Technology - Lisbon, Portugal
Duration: Sep 4 2005Sep 8 2005

Other

Other9th European Conference on Speech Communication and Technology
CountryPortugal
CityLisbon
Period9/4/059/8/05

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint Dive into the research topics of 'Distinctive feature based SVM discriminant features for improvements to phone recognition on telephone band speech'. Together they form a unique fingerprint.

  • Cite this

    Borys, S., & Hasegawa-Johnson, M. (2005). Distinctive feature based SVM discriminant features for improvements to phone recognition on telephone band speech. 697-700. Paper presented at 9th European Conference on Speech Communication and Technology, Lisbon, Portugal.