The USTC system for voice conversion challenge 2016: Neural network based approaches for spectrum, aperiodicity and F0 conversion

Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

Volumn 08-12-September-2016, Issue , 2016, Pages 1642-1646

  Chen, Ling Hui ^a,b   Liu, Li Juan ^b   Ling, Zhen Hua ^a   Jiang, Yuan ^b   Dai, Li Rong ^a  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b IFLYTEK RESEARCH   (China)

Author keywords

DNN; Frequency warping; LSTM; RNN; Voice conversion

Indexed keywords

RECURRENT NEURAL NETWORKS; SPEECH COMMUNICATION;

DEEP NEURAL NETWORKS; FREQUENCY WARPING; LONG SHORT TERM MEMORY; LSTM; NETWORK-BASED APPROACH; RECURRENT NEURAL NETWORK (RNN); SPECTRAL ENVELOPES; VOICE CONVERSION;

SPEECH PROCESSING;

EID: 84994337398     PISSN: 2308457X     EISSN: 19909772     Source Type: Conference Proceeding    
DOI: 10.21437/Interspeech.2016-456     Document Type: Conference Paper

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