基于人工神经网络的语音合成

E. V. Raghavendra, P. Vijayaditya, K. Prahallad
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引用次数: 19

摘要

统计参数综合由于其适应性强和综合规模大,近年来越来越受到人们的欢迎。在统计参数合成中,倒谱系数、基频(f0)和持续时间是合成语音的主要成分。目前的研究主要集中在谱线系数上。duration和f0取自原始数据。在本文中,我们试图解决双重问题。第一个问题是如何利用人工神经网络从文本中预测梅尔倒谱系数。第二个问题是从文本中预测共振子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Speech synthesis using artificial neural networks
Statistical parametric synthesis becoming more popular in recent years due to its adaptability and size of the synthesis. Mel cepstral coefficients, fundamental frequency (f0) and duration are the main components for synthesizing speech in statistical parametric synthesis. The current study mainly concentrates on mel cesptral coefficients. Durations and f0 are taken from the original data. In this paper, we are attempting on two fold problem. First problem is how to predict mel cepstral coefficient from text using artificial neural networks. The second problem is predicting formants from the text.
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