Title
Alaryngeal Speech Enhancement Based on One-to-Many Eigenvoice Conversion
Abstract
In this paper, we present novel speaking-aid systems based on one-to-many eigenvoice conversion (EVC) to enhance three types of alaryngeal speech: esophageal speech, electrolaryngeal speech, and body-conducted silent electrolaryngeal speech. Although alaryngeal speech allows laryngectomees to utter speech sounds, it suffers from the lack of speech quality and speaker individuality. To improve the speech quality of alaryngeal speech, alaryngeal-speech-to-speech (AL-to-Speech) methods based on statistical voice conversion have been proposed. In this paper, one-to-many EVC capable of flexibly controlling the converted voice quality by adapting the conversion model to given target natural voices is further implemented for the AL-to-Speech methods to effectively recover speaker individuality of each type of alaryngeal speech. These proposed systems are compared with each other from various perspectives. The experimental results demonstrate that our proposed systems are capable of effectively addressing the issues of alaryngeal speech, e.g., yielding significant improvements in speech quality of each type of alaryngeal speech.
Year
DOI
Venue
2014
10.1109/TASLP.2013.2286917
Audio, Speech, and Language Processing, IEEE/ACM Transactions  
Keywords
Field
DocType
eigenvalues and eigenfunctions,speech enhancement,AL-to-speech methods,EVC,alaryngeal speech enhancement,alaryngeal-speech-to-speech methods,body-conducted silent electrolaryngeal speech,electrolaryngeal speech,esophageal speech,laryngectomees,one-to-many eigenvoice conversion,speaker individuality,speaking-aid systems,speech quality,speech sounds,statistical voice conversion,voice quality,Alaryngeal speech,eigenvoice conversion,laryngectomees,speech enhancement,voice conversion
Speech enhancement,Audio signal,Speech processing,Alaryngeal speech,Esophageal speech,Speech quality,Computer science,Speech recognition,Sound quality,One-to-many
Journal
Volume
Issue
ISSN
22
1
2329-9290
Citations 
PageRank 
References 
12
0.61
21
Authors
4
Name
Order
Citations
PageRank
Hironori Doi1453.34
Tomoki Toda21874167.18
Nakamura, K.3385.99
Saruwatari, H.465290.81