Towards end-to-end speech recognition with transfer learning

Abstract A transfer learning-based end-to-end speech recognition approach is presented in two levels in our framework. Firstly, a feature extraction approach combining multilingual deep neural network (DNN) training with matrix factorization algorithm is introduced to extract high-level features. Se...

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Autors principals:	Chu-Xiong Qin, Dan Qu, Lian-Hai Zhang
Format:	Artigo
Idioma:	Inglês
Publicat:	SpringerOpen 2018-11-01
Col·lecció:	EURASIP Journal on Audio, Speech, and Music Processing
Matèries:	Speech recognition End-to-end Transfer learning
Accés en línia:	http://link.springer.com/article/10.1186/s13636-018-0141-9
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