Voice query-by-example for resource-limited languages using an ergodic hidden Markov model of speech
An ergodic hidden Markov model (EHMM) can be useful in extracting underlying structure embedded in connected speech without the need for a time-aligned transcribed corpus. In this research, we present a query-by-example (QbE) spoken term detection system based on an ergodic hidden Markov model of s...
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| Format: | Others |
| Language: | en_US |
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Georgia Institute of Technology
2014
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| Online Access: | http://hdl.handle.net/1853/50363 |