Improving Continuous Speech Recognition System Performance with Grapheme Modelling

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.


Year:
2005
Publisher:
IDIAP
Keywords:
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 Record created 2006-03-10, last modified 2018-03-17

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