基于隐马尔可夫模型的斯洛伐克语统计参数语音合成的说话人自适应

M. Sulír, J. Juhár
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引用次数: 3

摘要

本文描述了基于隐马尔可夫模型的斯洛伐克语统计参数语音合成中说话人自适应的首次实验。描述了基于模型自适应技术的两种新斯洛伐克语语音的实现,包括用于自适应程序的小语料库设计和用于平均语音训练的斯洛伐克语自动语音识别语料库的处理。在进行的听力主观测试中,通过意见评分和语义不可预测句子测试,比较了由定期训练和调整的模型生成的男性和女性语音。所获得的结果表明,这种技术在斯洛伐克语的情况下具有很高的潜力,因为我们设法用少量数据获得了一种新的可理解且听起来相对自然的人工语音。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Speaker adaptation for Slovak statistical parametric speech synthesis based on hidden Markov models
In this paper, the first experiments with the speaker adaptation for Slovak statistical parametric speech synthesis based on the hidden Markov models are described. The implementation of two new Slovak voices based on the model adaptation technique consisted of small speech corpora design, which were used for the adaptation procedure and the processing of Slovak automatic speech recognition corpora, which were used for the average voice training is described. In the performed listening subjective tests, male and female speech generated from the regularly trained and adapted models was compared with the help of the opinion score and the semantically unpredictable sentences tests. The obtained results showed a high potential of this technique in case of Slovak language, because we manage to get a new intelligible and relatively natural sounding artificial speech with the small amount of data.
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