Modeling context and language variation for non-native speech recognition

Non-native speakers often face difficulty in pronouncing like the native speakers. This paper proposes to model pronunciation variation in non-native speaker’s speech using only acoustics models, without the need for the corpus. Variation in term of context and language will be modeled. The combination of both modeling resulted in the reduction of absolute WER as much as 16% and 6% for native Vietnamese and Chinese speakers of French.

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