Minimum Phone Error (MPE) model and feature training on Mandarin broadcast news task

Jia Yu Chen*, Chia Yu Wan, Yi Chen, Berlin Chen, Lin Shan Lee

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The Minimum Phone Error (MPE) criterion for discriminative training was shown to be able to offer acoustic models with significantly improved performance. This concept was then further extended to Feature-space Minimum Phone Error (fMPE) and offset fMPE for training feature parameters as well. This paper reviews the concept of MPE and reports the experiments and results in performing MPE, fMPE and offset fMPE on the task of Mandarin Broadcast News, and significant improvements were obtained similar to the results reported for other languages and other tasks by other sites. In addition, a new concept of dimension-weighted offset fMPE is proposed in this work and even better performance than offset fMPE was obtained.

Original languageEnglish
Title of host publicationChinese Spoken Language Processing - 5th International Symposium, ISCSLP 2006, Proceedings
Pages270-281
Number of pages12
DOIs
Publication statusPublished - 2006
Event5th International Symposium on Chinese Spoken Language Processing, ISCSLP 2006 - Singapore, Singapore
Duration: 2006 Dec 132006 Dec 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4274 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Symposium on Chinese Spoken Language Processing, ISCSLP 2006
Country/TerritorySingapore
CitySingapore
Period2006/12/132006/12/16

Keywords

  • Dimension-weighted
  • Discriminative training
  • Featurespace MPE (fMPE)
  • Large-vocabulary continuous speech recognition (LVCSR)
  • Minimum Phone Error (MPE)
  • Offset fMPE

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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