Towards Fast and Accurate Streaming End-to-End ASR

Chang Shuo-yiin
Chang Shuo-yiin
He Yanzhang
He Yanzhang
Strohman Trevor
Strohman Trevor

ICASSP, pp. 6069-6073, 2020.

Cited by: 2|Bibtex|Views104|DOI:https://doi.org/10.1109/ICASSP40776.2020.9054715
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Other Links: arxiv.org|academic.microsoft.com|dblp.uni-trier.de

Abstract:

End-to-end (E2E) models fold the acoustic, pronunciation and language models of a conventional speech recognition model into one neural network with a much smaller number of parameters than a conventional ASR system, thus making it suitable for on-device applications. For example, recurrent neural network transducer (RNN-T) as a streami...More

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