Paper Info
Title
Exemplar-based voice conversion in noisy environment
Abstract
This paper presents a voice conversion (VC) technique for noisy environments, where parallel exemplars are introduced to encode the source speech signal and synthesize the target speech signal. The parallel exemplars (dictionary) consist of the source exemplars and target exemplars, having the same texts uttered by the source and target speakers. The input source signal is decomposed into the source exemplars, noise exemplars obtained from the input signal, and their weights (activities). Then, by using the weights of the source exemplars, the converted signal is constructed from the target exemplars. We carried out speaker conversion tasks using clean speech data and noise-added speech data. The effectiveness of this method was confirmed by comparing its effectiveness with that of a conventional Gaussian Mixture Model (GMM)-based method.
Year
DOI
Venue
2012
10.1109/SLT.2012.6424242
Spoken Language Technology Workshop
Keywords
Field
DocType
matrix decomposition,signal denoising,source separation,speaker recognition,speech coding,speech synthesis,clean speech data,exemplar-based voice conversion,noise-added speech data,noisy environment,nonnegative matrix factorization,parallel exemplars,source exemplars,source signal decomposition,source speakers,source speech signal encoding,speaker conversion tasks,target exemplars,target speakers,target speech signal synthesis,text utterance,exemplar-based,noise robustness,non-negative matrix factorization,sparse coding,voice conversion
Speech processing,Speech synthesis,Speech coding,Pattern recognition,Voice activity detection,Computer science,Matrix decomposition,Speech recognition,Speaker recognition,Artificial intelligence,Mixture model,Source separation
Conference
ISSN
ISBN
Citations 
2639-5479
978-1-4673-5124-9
38
PageRank 
References 
Authors
1.11
10
3
Name
Order
Citations
PageRank
Ryoichi Takashima19512.16
Tetsuya Takiguchi2858.77
Yasuo Ariki3381.11