Jayenthiran Pukuraj
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HI
I’m working on an ASR-based project for my liguistic training targeted toward English language learners.
The goal is to capture non-native pronunciations (specifically Indian learners of British English) and retain the mispronunciations in the decoding output, rather than mapping them to the nearest canonical word.
I’m looking for guidance on:
A suitable British English speech dataset, preferably one that includes either native British pronunciation or Indian-accented speech with British targets.
Decoding techniques or modifications in Kaldi that would allow the ASR system to reflect mispronunciations as they are, without auto-correcting to the nearest valid English word. Ideally, this should preserve phoneme-level or subword deviations.
Any known acoustic/language model settings or post-processing strategies to avoid "forced correction" and instead reflect pronunciation variation in the hypothesis.
please help me on this.