Rapid adaptation using linear spectral transformation for embedded speech recognisers

Y. Cho, D. Yook

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Embedded speech recognisers are typically used in unknown mobile environments where the acoustic conditions frequently change. Since a large amount of adaptation data is not usually available for such environments, the adaptation methods for the acoustic models of these recognisers must improve the recognition performance with only a small amount of adaptation data. In this Letter, we show that maximum likelihood linear spectral transformation provides the advantage of rapid adaptation using a very limited amount of adaptation data for the embedded acoustic models.

Original languageEnglish
Pages (from-to)1040-1042
Number of pages3
JournalElectronics Letters
Volume44
Issue number17
DOIs
Publication statusPublished - 2008

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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