Improving Continuous Speech Recognition System Performance with Grapheme Modelling
| Type of publication: | Idiap-RR |
| Citation: | magimai05a |
| Number: | Idiap-RR-16-2005 |
| Year: | 2005 |
| Institution: | IDIAP |
| Abstract: | This paper investigates automatic speech recognition system using context-dependent graphemes as subword units based on the conventional HMM/GMM system as well as TANDEM system. Experimental studies conducted on two different continuous speech recognition tasks show that systems using only context-dependent graphemes can yield competitive performance when compared to state-of-the-art context-dependent phoneme-based automatic speech recognition system. We further demonstrate that a system using both context-dependent phoneme and grapheme subword units can out perform either of these systems alone. |
| Userfields: | ipdmembership={speech}, |
| Keywords: | |
| Projects: |
Idiap |
| Authors: | |
| Added by: | [UNK] |
| Total mark: | 0 |
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