Prosodic Processing for the Automatic Synthesis of Emotional Russian Speech

A. Kaliyev, Yuri N. Matveev, E. Lyakso, S. Rybin
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引用次数: 5

Abstract

Currently, the automatic speech synthesis technology is undergoing significant changes due to new solutions in the field of machine learning. These solutions qualitatively improve the sound of synthesized speech, bringing it closer to natural human speech. Against the backdrop of this, as well as under the influence of business, the development of artificial emotional speech for human-machine interaction systems has received a new strong turn of development. Due to this prosodic processing for the synthesis of Russian emotional speech has become an important research direction for our research group.The article presents an algorithm for predicting pause locations for three categories of emotional speech. In particular, the authors used three corpora of emotional speech, collected according to emotional categories (neutral, excited and depressed), for training classifiers. The obtained results can be used to create a high-quality automatic synthesizer of emotional speech.
情绪性俄语语音自动合成的韵律处理
目前,由于机器学习领域的新解决方案,自动语音合成技术正在发生重大变化。这些解决方案从质量上提高了合成语音的声音,使其更接近自然的人类语音。在这样的背景下,以及在商业的影响下,用于人机交互系统的人工情感语音的发展得到了新的强劲发展。因此,韵律处理对俄语情感语音的合成已成为本课题组的一个重要研究方向。本文提出了一种预测三类情感言语停顿位置的算法。特别地,作者使用了根据情绪类别(中性、兴奋和抑郁)收集的三个情绪语音语料库来训练分类器。所获得的结果可用于创建高质量的情绪语音自动合成器。
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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