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Multilingual Non-Native Speech Recognition Using Phonetic Confusion-Based Acoustic Model Modi?cation and Graphemic Constraints

Overview This paper presents an automated approach for non-native speech recognition. The paper introduces a new phonetic confusion concept that associates sequences of Native Language (NL) phones to Spoken Language (SL) phones. Phonetic confusion rules are automatically extracted from a non-native speech database for a given NL and SL using both NL's and SL's ASR systems. These rules are used to modify the acoustic models (HMMs) of SL's ASR by adding acoustic models of NL's phones according to these rules. As pronunciation errors that non-native speakers produce depend on the writing of the words, the paper has also used graphemic constraints in the phonetic confusion extraction process. In the lexicon, the phones in words' pronunciations are linked to the corresponding graphemes (characters) of the word.

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Publisher: LORIA
File Format: PDF
Date Published: Dec 13, 2008
Format: White Papers
Topics: Voice Recognition

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