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TODM: Train Once Deploy Many Efficient Supernet-Based RNN-T..:
Shangguan, Yuan
;
Yang, Haichuan
;
Li, Danni
...
http://arxiv.org/abs/2309.01947. , 2023
Link:
http://arxiv.org/abs/2309.01947
RT Journal T1 <Title>TODM: Train Once Deploy Many Efficient Supernet-Based RNN-T Compression For On-device ASR Models</Title> UL https://suche.suub.uni-bremen.de/peid=base-ftarxivpreprints:oai:arXiv.org:2309.01947&Exemplar=1&LAN=DE A1 Shangguan, Yuan A1 Yang, Haichuan A1 Li, Danni A1 Wu, Chunyang A1 Fathullah, Yassir A1 Wang, Dilin A1 Dalmia, Ayushi A1 Krishnamoorthi, Raghuraman A1 Kalinli, Ozlem A1 Jia, Junteng A1 Mahadeokar, Jay A1 Lei, Xin A1 Seltzer, Mike A1 Chandra, Vikas YR 2023 K1 Computer Science - Computation and Language K1 Computer Science - Machine Learning K1 Computer Science - Sound K1 Electrical Engineering and Systems Science - Audio and Speech Processing JF http://arxiv.org/abs/2309.01947 LK http://arxiv.org/abs/2309.01947 DO http://arxiv.org/abs/2309.01947 SF ELIB - SuUB Bremen
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