Error Approximation and Minimum Phone Error Acoustic Model Estimation

Minimum phone error (MPE) acoustic parameter estimation involves calculation of edit distances (errors) between correct and incorrect hypotheses. In the context of large vocabulary continuous speech recognition, this error calculation becomes prohibitively expensive and so errors are approximated. This paper introduces a novel error approximation technique. Analysis shows that this approximation yields a higher correlation to the Levenshtein error metric than a previously-used approximation. Experimental evaluations on a large vocabulary recognition task demonstrate that the novel approximation also delivers significant performance improvements over the previously-used approximation when applied to MPE acoustic model estimation.

• Type: Journal
• Year: 2010
• Where: TASLP
• Authors: Matt Gibson 0002, Thomas Hain
• Keywords: Approximation, Large Vocabulary, Minimum Phone Error, Software Engineering, TASLP 2010