Abstract:In this paper, we investigate how the output representation of an end-to-end neural network affects multilingual automatic speech recognition (ASR). We study different representations including character-level, byte-level, byte pair encoding (BPE), and bytelevel byte pair encoding (BBPE) representations, and analyze their strengths and weaknesses. We focus on developing a single end-toend model to support utterance-based bilingual ASR, where speakers do not alternate between two languages in a single utterance… Show more
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