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Assessing the Use of Prosody in Constituency Parsing of Imperfect Transcripts
[article]
2021
arXiv
pre-print
This work explores constituency parsing on automatically recognized transcripts of conversational speech. The neural parser is based on a sentence encoder that leverages word vectors contextualized with prosodic features, jointly learning prosodic feature extraction with parsing. We assess the utility of the prosody in parsing on imperfect transcripts, i.e. transcripts with automatic speech recognition (ASR) errors, by applying the parser in an N-best reranking framework. In experiments on
arXiv:2106.07794v1
fatcat:bhgiarjcefe63fgym42yesi4rm