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F0 Contour Modeling for Arabic Text-to-Speech Synthesis Using Fujisaki Parameters and Neural Networks

机译:使用Fujisaki参数和神经网络的F0轮廓建模,用于阿拉伯文本到语音的合成

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Speech synthesis quality depends on its naturalness and intelligibility. These abstract concepts are the concern of phonology. In terms of phonetics, they are transmitted by prosodic components, mainly the fundamental frequency (F0) contour. F0 contour modeling is performed either by setting rules or by investigating databases, with or without parameters and following a timely sequential path or a parallel and super-positional scheme. In this study, we opted to model the F0 contour for Arabic using the Fujisaki parameters to be trained by neural networks. Statistical evaluation was carried out to measure the predicted parameters accuracy and the synthesized F0 contour closeness to the natural one. Findings concerning the adoption of Fujisaki parameters to Arabic F0 contour modeling for text-to-speech synthesis were discussed.Keywords: F0 contour, Arabic TTS, Fujisaki parameters, neural networks, Phrase command, Accent command.
机译:语音合成质量取决于其自然性和清晰度。这些抽象概念是语音学的关注点。就语音而言,它们是通过韵律分量(主要是基频(F0)等高线)传输的。 F0轮廓建模可以通过设置规则或通过调查数据库(有或没有参数)并遵循及时的顺序路径或平行和超位置方案来执行。在这项研究中,我们选择使用由神经网络训练的Fujisaki参数为阿拉伯语的F0轮廓建模。进行统计评估以测量预测参数的准确性和合成的F0轮廓与自然轮廓的接近度。讨论了将Fujisaki参数用于阿拉伯F0轮廓建模以进行文本到语音合成的发现。

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