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Comparison and Analysis of Several Phonetic Decoding Approaches
Abstract : This article analyzes the phonetic decoding performance obtained with different choices of linguistic units. The context is to later use such an approach as a support for helping communication with deaf people, and to run it on an embedded decoder on a portable terminal, which introduces constrains on the model size. As a first step, this paper compares the performance of various approaches on the ESTER2 and ETAPE speech corpora. Two baseline systems are considered, one relying on a large vocabulary speech recognizer, and another one relying on a phonetic n-gram language model. The third model which relies on a syllable-based lexicon and a trigram language model, provides a good tradeoff between model size and phonetic decoding performance. The phone error rate is only 4% worse (absolute) than the phone error rate obtained with the large vocabulary recognizer, and much better than the phone error rate obtained with the phone n-gram language model. Phone error rates are then analyzed with respect to SNR and speaking rate.
https://hal.inria.fr/hal-00834313
Contributor : Denis Jouvet <>
Submitted on : Friday, March 25, 2016 - 5:35:58 PM
Last modification on : Thursday, March 5, 2020 - 4:54:07 PM
Document(s) archivé(s) le : Sunday, June 26, 2016 - 3:22:40 PM
Contributor : Denis Jouvet <>
Submitted on : Friday, March 25, 2016 - 5:35:58 PM
Last modification on : Thursday, March 5, 2020 - 4:54:07 PM
Document(s) archivé(s) le : Sunday, June 26, 2016 - 3:22:40 PM
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