Automatic Non-native Dialect and Accent Voice Detection of South Indian English
Speech recognition has achieved enormous improvements presently. However, robustness is still one of the big tribulations, e.g. performance of recognition fluctuates penetratingly depending on the speaker, particularly as the speaker has robust accent that is not coated in the training corpus. The speaker variability, such like gender, accent, age, speaking rate, and phone realizations, are vital problems in speech recognition. The mainly South Indian accent identification is a recent challenging problem closely related to other relatively recent fields of the multilinguality area like non native speech identification and language identification. This paper explains an automatic recognition system for English accents from 5 different South Indian State. The approach is based on a corresponding set of random nets with situation independent HMM units. The random topology was in addition substituted by pronunciation transcription constraints so as to integrate accent specific automatic word recognizers.
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