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Voice conversion in cochlear implantation
Author(s) -
Wilkinson Eric P.,
AbdelHamid Ossama,
Galvin John J.,
Jiang Hui,
Fu QianJie
Publication year - 2013
Publication title -
the laryngoscope
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.181
H-Index - 148
eISSN - 1531-4995
pISSN - 0023-852X
DOI - 10.1002/lary.23744
Subject(s) - cochlear implantation , audiology , speech recognition , computer science , communication , medicine , psychology , cochlear implant
Objectives/Hypothesis: Voice conversion algorithms may benefit cochlear implant (CI) users who better understand speech produced by one talker than by another. It is unclear how the source or target talker's fundamental frequency (F0) information may contribute to perception of converted speech. This study evaluated voice conversion algorithms for CI users in which the source or target talker's F0 was included in the converted speech.Study Design: Development and evaluation of computerized voice conversion algorithms in CI patients.Methods: A series of cepstral analysis‐based algorithms were developed and evaluated in six CI users. The algorithms converted talker voice gender (male‐to‐female, or female‐to‐male); either the source or target talker F0 was included in the converted speech. The voice conversion algorithms were evaluated in terms of recognition of IEEE sentences, speech quality, and voice gender discrimination.Results: Voice gender recognition performance showed that listeners strongly cued to the F0 that was included within the converted speech. For both IEEE sentence recognition and voice quality ratings, performance was poorer with the voice conversion algorithms than with original speech. Performance on female‐to‐male conversion was superior to male‐to‐female conversion.Conclusion: The strong cueing to F0 within the voice conversion algorithms suggests that CI users are able to utilize temporal periodicity information for some pitch‐related tasks. Limitations on spectral channel information experienced by CI users may result in poorer performance with voice conversion algorithms due to distortion of speech formant information and degradation of the spectral envelope. Laryngoscope, 2013