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Esophageal Speech Enhancement Based on Statistical Voice Conversion with Gaussian Mixture Models
Hironori DOI Keigo NAKAMURA Tomoki TODA Hiroshi SARUWATARI Kiyohiro SHIKANO
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2010/09/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Section on Processing Natural Speech Variability for Improved Verbal Human-Computer Interaction)
Category: Voice Conversion
laryngectomees , esophageal speech , speech enhancement , voice conversion , eigenvoice conversion ,
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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.