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A statistics-based pitch contour model for Mandarin speech

机译:基于统计的普通话音调等高线模型

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摘要

A statistics-based syllable pitch contour model for Mandarin speech is proposed. This approach takes the mean and the shape of a syllable log-pitch contour as two basic modeling units and considers several affecting factors that contribute to their variations. The affecting factors include the speaker, prosodic state (which essentially represents the high-level linguistic components of F0 and will be explained more clearly in Sec. 1), tone, and initial and final syllable classes. The parameters of the two modeling units were automatically estimated using the expectation-maximization (EM) algorithm. Experimental results showed that the root mean squared errors (RMSEs) obtained in the closed and open tests in the reconstructed pitch period were 0.362 and 0.373 ins, respectively. This model provides a way to separate the effects of several major factors. All of the inferred values of the affecting factors were in close agreement with our prior linguistic knowledge. It also gives a quantitative and more complete description of the coarticulation effect of neighboring tones rather than conventional qualitative descriptions of the tone sandhi rules. In addition, the model can provide useful cues to determine the prosodic phrase boundaries, including those occurring at intersyllable locations, with or without punctuation marks. (C) 2005 Acoustical Society of America.
机译:提出了基于统计的普通话音节音高轮廓模型。这种方法将音节对数音高轮廓的均值和形状作为两个基本建模单元,并考虑了几个影响其变化的影响因素。影响因素包括说话者,韵律状态(本质上代表F0的高级语言成分,并将在第1节中更清楚地说明),语调以及初始和最终音节类别。使用期望最大化(EM)算法自动估计两个建模单元的参数。实验结果表明,在重构音调周期的封闭测试和开放测试中,均方根误差(RMSE)分别为0.362和0.373 ins。该模型提供了一种分离几个主要因素影响的方法。所有影响因素的推论值都与我们先前的语言知识非常一致。它也给出了相邻音调共音效果的定量和更完整的描述,而不是音调变调规则的常规定性描述。另外,该模型可以提供有用的线索来确定韵律短语边界,包括在音节位置处出现的,带有或不带有标点符号的那些。 (C)2005年美国声学学会。

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