基于隐马尔可夫模型的视觉语音合成器

2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100) Pub Date : 2000-06-05 DOI:10.1109/ICASSP.2000.859323

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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来源期刊

2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100)

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