Application of Hybrid CTC/2D-Attention end-to-end Model in Speech Recognition During the COVID-19 Pandemic

Mingzhe E and Bin Zhao
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Bin Zhao: Hubei University of Technology, 430068, China

Biomedical Journal of Scientific & Technical Research, 2021, vol. 38, issue 3, 30297-30304

Abstract: Recent research in the field of speech recognition has shown that end-to-end speech recognition frameworks have greater potential than traditional frameworks. Aiming at the problem of unstable decoding performance in end-to-end speech recognition, a hybrid end-to-end model of connectionist temporal classification.

Keywords: Covid-19; Infectious Disease; Disease Control; Incubation Period; Spread Rate of Covid-19; Population; Unemployment Tradeoff; Virus; Vaccines; Covid-19 Mutation (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:abf:journl:v:38:y:2021:i:3:p:30297-30304

DOI: 10.26717/BJSTR.2021.38.006145

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