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1 Ergebnisse
1
3M: An Effective Multi-view, Multi-granularity, and Multi-a..:
, In:
2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
,
Chao, Fu-An
;
Lo, Tien-Hong
;
Wu, Tzu-I
.. - p. 575-582 , 2022
Link:
https://doi.org/10.23919/APSIPAASC55919.2022.9979979
RT T1 <cTitle>2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)</cTitle>: T1 <Title>3M: An Effective Multi-view, Multi-granularity, and Multi-aspect Modeling Approach to English Pronunciation Assessment</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9979979&Exemplar=1&LAN=DE A1 Chao, Fu-An A1 Lo, Tien-Hong A1 Wu, Tzu-I A1 Sung, Yao-Ting A1 Chen, Berlin YR 2022 SN 2640-0103 K1 Training K1 Computational modeling K1 Self-supervised learning K1 Information processing K1 Benchmark testing K1 Speech K1 computer-assisted pronunciation training K1 pronunciation assessment K1 goodness of pronunciation K1 segmental and suprasegmental features K1 self-supervised learning SP 575 OP 582 LK http://dx.doi.org/https://doi.org/10.23919/APSIPAASC55919.2022.9979979 DO https://doi.org/10.23919/APSIPAASC55919.2022.9979979 SF ELIB - SuUB Bremen
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