CLASS-COMBINED ORD N-GRAM FOR ROBUST LANGUAGE ODELING

Norihiko Kobayashi, Tetsunori Kobayashi

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

We propose a method of robust language model ing for a small amount of training text corpus. In this method, the word bigram and the class bigram are combined using a weighting function of preceding word frequency. We made experiments on speech recogni tion using JNAS speech corpus. As the results, it was proved that the performance of the class combined bi gram is equivalent to that of the word bigram trained with 2.5 larger size of corpus. We also made experi ments using sports news dialogue on TV. Recognition accuracy of the class-combined bigram was 83.3% that was 5.5 point higher than that of the word bigram.

Original languageEnglish
Pages1599-1602
Number of pages4
Publication statusPublished - 1999
Event6th European Conference on Speech Communication and Technology, EUROSPEECH 1999 - Budapest, Hungary
Duration: 1999 Sep 51999 Sep 9

Conference

Conference6th European Conference on Speech Communication and Technology, EUROSPEECH 1999
Country/TerritoryHungary
CityBudapest
Period99/9/599/9/9

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Linguistics and Language
  • Communication

Fingerprint

Dive into the research topics of 'CLASS-COMBINED ORD N-GRAM FOR ROBUST LANGUAGE ODELING'. Together they form a unique fingerprint.

Cite this