Abstract
In this study, we evaluate our proposed methods for enhancing alaryngeal speech based on statistical voice conversion techniques. Voice conversion based on a Gaussian mixture model has been applied to the conversion of alaryngeal speech into normal speech (AL-to-Speech). Moreover, one-to-many eigenvoice conversion (EVC) has also been applied to AL-to-Speech to enable the recovery of the original voice quality of laryngectomees even if only one arbitrary utterance of the original voice is available. VC/EVC-based AL-to-Speech systems have been developed for several types of alaryngeal speech, such as esophageal speech (ES), electrolaryngeal speech (EL), and body-conducted silent electrolaryngeal speech (silent EL). These proposed systems are compared with each other from various perspectives. The experimental results demonstrate that our proposed systems yield significant enhancement effects on each type of alaryngeal speech.
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