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Improving End-to-end Speech Recognition with Pronunciation-assisted Sub-word Modeling

2018-11-10 · Hainan Xu, Shuoyang Ding, Shinji Watanabe

Most end-to-end speech recognition systems model text directly as a sequence of characters or sub-words. Current approaches to sub-word extraction only consider character sequence frequencies, which at times produce inferior sub-word segmentation that might lead to erroneous speech recognition output. We propose pronunciation-assisted sub-word modeling (PASM), a sub-word extraction method that leverages the pronunciation information of a word. Experiments show that the proposed method can greatly improve upon the character-based baseline, and also outperform commonly used byte-pair encoding methods.

📄 PDF Abstract BibTeX arXiv:1811.04284

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Automatic Speech Recognition (ASR)speech-recognitionSpeech Recognition

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