基于隐马尔可夫模型的视觉语音合成器

J. J. Williams, A. Katsaggelos, M. Randolph
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引用次数: 5

摘要

本文设计了一种基于隐马尔可夫模型的视觉合成器,用于帮助听力障碍者。这个合成器建立在视听语音识别领域的成果之上。我们描述了如何使用相关HMM来整合独立的声学和视觉HMM,以实现语音到视觉的合成。我们的研究结果表明,与通过缩放来补偿速率差异的技术相比,HMM相关模型可以显著改善同步误差。
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A hidden Markov model based visual speech synthesizer
This paper describes a hidden Markov model (HMM) based visual synthesizer designed to assist persons with impaired hearing. This synthesizer builds on results in the area of audio-visual speech recognition. We describe how a correlation HMM can be used to integrate independent acoustic and visual HMMs for speech-to-visual synthesis. Our results show that an HMM correlating model can significantly improve synchronization errors versus techniques which compensate for rate differences through scaling.
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