An E2E ASR model with mixed wordpieces and phonemes improves foreign proper noun recognition via phoneme-level contextual biasing, showing 16% gain over grapheme-only and 8% over wordpiece-only baselines.
Créteil", we tokenize it into phonemes using the French pronunciation lexicon, i.e. “Créteil
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Phoneme-Based Contextualization for Cross-Lingual Speech Recognition in End-to-End Models
An E2E ASR model with mixed wordpieces and phonemes improves foreign proper noun recognition via phoneme-level contextual biasing, showing 16% gain over grapheme-only and 8% over wordpiece-only baselines.