Voice banking and voice reconstruction for MND patients

C. Veaux, J. Yamagishi, Simon King
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引用次数: 5

Abstract

When the speech of an individual becomes unintelligible due to a degenerative disease such as motor neuron disease (MND), a voice output communication aid (VOCA) can be used. To fully replace all functions of speech communication: communication of information, maintenance of social relationships and displaying identity, the voice must be intelligible, natural-sounding and retain the vocal identity of the speaker. Attempts have been made to capture the voice before it is lost, using a process known as voice banking. But, for patients with MND, the speech deterioration frequently coincides or quickly follows diagnosis. Using model-based speech synthesis, it is now possible to retain the vocal identity of the patient with minimal data recordings and even deteriorating speech. The power of this approach is that it is possible to use the patient's recordings to adapt existing voice models pre-trained on many speakers. When the speech has begun to deteriorate, the adapted voice model can be further modified in order to compensate for the disordered characteristics found in the patient's speech. We present here an on-going project for voice banking and voice reconstruction based on this technology.
脑残障患者的语音银行和语音重建
当由于运动神经元疾病(MND)等退行性疾病而无法理解说话时,可以使用语音输出通信辅助设备(VOCA)。要想完全取代言语交际的所有功能:信息的交流、社会关系的维护和身份的展示,声音必须是可理解的、自然的,并保留说话人的声音身份。人们已经尝试在语音丢失之前捕获语音,这一过程被称为语音银行。但是,对于患有MND的患者来说,语言能力的退化往往与诊断同时发生或很快发生。使用基于模型的语音合成,现在可以用最少的数据记录甚至恶化的语音来保留患者的声音身份。这种方法的强大之处在于,它可以使用患者的录音来适应在许多扬声器上预先训练的现有语音模型。当语音开始恶化时,可以进一步修改适应的语音模型,以补偿患者语音中发现的紊乱特征。我们在此介绍一个正在进行的基于该技术的语音银行和语音重建项目。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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