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A review of on-device fully neural end-to-end automatic speech recognition algorithms
[article]
2021
arXiv
pre-print
In this paper, we review various end-to-end automatic speech recognition algorithms and their optimization techniques for on-device applications. Conventional speech recognition systems comprise a large number of discrete components such as an acoustic model, a language model, a pronunciation model, a text-normalizer, an inverse-text normalizer, a decoder based on a Weighted Finite State Transducer (WFST), and so on. To obtain sufficiently high speech recognition accuracy with such conventional
arXiv:2012.07974v3
fatcat:uxpxqcgcvvg7dfrkl2rxekkmse