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Esophageal Speech Enhancement Based on Statistical Voice Conversion with Gaussian Mixture Models

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dc.contributor.author Hironori Doi en
dc.contributor.author Keigo Nakamura en
dc.contributor.author Tomoki Toda en
dc.contributor.author Hiroshi Saruwatari en
dc.contributor.author Kiyohiro Shikano en
dc.date.accessioned 2012-07-05T07:00:52Z en
dc.date.available 2012-07-05T07:00:52Z en
dc.date.issued 2010-09 en
dc.identifier.issn 0916-8532 en
dc.identifier.uri http://hdl.handle.net/10061/7845 en
dc.description.abstract This paper presents a novel method of enhancing esophageal speech using statistical voice conversion. Esophageal speech is one of the alternative speaking methods for laryngectomees. Although it doesn't require any external devices, generated voices usually sound unnatural compared with normal speech. To improve the intelligibility and naturalness of esophageal speech, we propose a voice conversion method from esophageal speech into normal speech. A spectral parameter and excitation parameters of target normal speech are separately estimated from a spectral parameter of the esophageal speech based on Gaussian mixture models. The experimental results demonstrate that the proposed method yields significant improvements in intelligibility and naturalness. We also apply one-to-many eigenvoice conversion to esophageal speech enhancement to make it possible to flexibly control the voice quality of enhanced speech. en
dc.language.iso en en
dc.publisher 電子情報通信学会 ja
dc.rights Copyright (C) 2010 電子情報通信学会. ja
dc.subject laryngectomees en
dc.subject esophageal speech en
dc.subject speech enhancement en
dc.subject voice conversion en
dc.subject eigenvoice conversion en
dc.title Esophageal Speech Enhancement Based on Statistical Voice Conversion with Gaussian Mixture Models en
dc.type.nii Journal Article en
dc.textversion publisher en
dc.identifier.ncid AA10826272 en
dc.identifier.jtitle IEICE Transactions on Information and Systems en
dc.identifier.volume E93-D en
dc.identifier.issue 9 en
dc.identifier.spage 2472 en
dc.identifier.epage 2481 en
dc.relation.doi 10.1587/transinf.E93.D.2472 en
dc.identifier.url https://search.ieice.org/ en
dc.identifier.NAIST-ID 73292716 en


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