一个宽带语音模型过程作为测试信号

M. R. Serafat, U. Heute
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引用次数: 2

摘要

如果使用自然语音作为测试信号,语音编码系统的客观质量评估或其他自适应语音传输系统测试中的一些主要问题是说话人的依赖性、再现性和测量结果的可比性。使用合适的语音模型处理可以避免这个问题。在本文中,我们提出了一种宽频带语音模型过程,它具有与自然语音相同的长、短时特征。该过程的生成器的控制部分包括几个训练好的马尔可夫链(mc),以使过程的时变特性适应于自然语音的时变特性。此外,由于自然宽带语音具有不对称的概率密度函数(PDF),因此特别注意必要的概率密度函数不对称性。
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A wide-band speech-model process as a test signal
Some of the major problems in objective quality assessment of speech coding systems or in testing other adaptive speech transmission systems are the speaker dependence, reproducibility, and the comparability of the measurement results, if natural speech is used as the test signal. This problem can be avoided by using suitable speech-model processes. In this paper, we present a wide-band speech-model process, which includes the same long- and short-time characteristics as natural speech. The controlling part of the generator of this process involves several trained Markov chains (mc) to adapt the time-varying properties of the process to those of natural speech. Furthermore, special care is taken of the necessary probabilty density function (PDF) asymmetries, because the natural wide-band speech has an asymmetric PDF.
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