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Conference Papers Year : 2012

Combining criteria for the detection of incorrect entries of non-native speech in the context of foreign language learning

Abstract

This article analyzes the detection of incorrect entries of nonnative speech in the context of foreign language learning. The purpose is to detect and reject incorrect entries (i.e. those for which the speech signal does not correspond at all to the associated text) while being tolerant to the mispronunciations of non-native speech. The proposed approach exploits the comparison between two text-to-speech alignments : one constrained by the text which is being checked, with another one unconstrained, corresponding to a phonetic decoding. Several comparison criteria are described and combined via a logistic regression function. The article analyzes the influence of different settings, such as the impact of non-native pronunciation variants, the impact of learning the decision functions on native or on non-native speech, as well as the impact of combining various comparison criteria. The performance evaluations are conducted both on native and on non-native speech.
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Dates and versions

hal-00753458 , version 1 (25-03-2016)

Identifiers

  • HAL Id : hal-00753458 , version 1

Cite

Luiza Orosanu, Denis Jouvet, Dominique Fohr, Irina Illina, Anne Bonneau. Combining criteria for the detection of incorrect entries of non-native speech in the context of foreign language learning. SLT 2012 - 4th IEEE Workshop on Spoken Language Technology, Dec 2012, Miami, United States. ⟨hal-00753458⟩
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