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 language | English |
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Pages (from-to) | 1040-1042 |
Number of pages | 3 |
Journal | Electronics Letters |
Volume | 44 |
Issue number | 17 |
DOIs | |
Publication status | Published - 2008 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering