Conference Paper/Proceeding/Abstract 475 views
Continuous speech recognition using syllables
Rhys Jones 
,
John Mason,
Simon Downey
,
John Mason,
Simon Downey
Eurospeech '97, Pages: 1171 - 1174
Swansea University Authors:
Rhys Jones , John Mason
Full text not available from this repository: check for access using links below.
Abstract
The vast majority of work in continuous speech recognition uses phoneme-like units as the basic recognition component. The work presented here investigates the practicability of syllable-like units as the building blocks for recognition. A phonetically annotated telephony database is analysed at the...
| Published in: | Eurospeech '97 |
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| ISSN: | 1018-4074 |
| Published: |
Grenoble, France
European Speech Communication Association: ESCA
1997
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa63336 |
| Abstract: |
The vast majority of work in continuous speech recognition uses phoneme-like units as the basic recognition component. The work presented here investigates the practicability of syllable-like units as the building blocks for recognition. A phonetically annotated telephony database is analysed at the syllable level, and a set of syllable-based Hidden Markov Models (HMMs) are built. Refinements including the introduction of syllable-level bigram probabilities, word- and syllable-level insertion penalties, and the investigation of different model topologies are found to improve recogniser performance. It is found that the syllable-based recogniser gives recognition accuracies of over 60%, which compares with 35% as the baseline accuracy for monophone recognition. It is envisaged that practical applications of syllable recognition could be in a hybrid system, where the most common syllable HMMs would be used in conjunction with whole-word and phoneme models. |
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| College: |
Faculty of Humanities and Social Sciences |
| Start Page: |
1171 |
| End Page: |
1174 |