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A generative model of pause duration considering the relation between utterances before and after a pause

机译:暂停持续时间的生成模型,考虑了暂停前后的发声之间的关系

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Utterance durations just before and after a pause have been considered to be the only factors affecting pause duration (Preboundary and Postboundary Effects). Recently, using an “XY utterance phrase” composed of two words, we discovered that the ratio of the two utterance durations before and after a pause affects pause duration (Pre-postboundary effect). However, it is not obvious whether such effects are useful for speech processing applications. In this research, we developed a generative model of pause duration based on multiple regression analysis from our experimental data (Primal Model), and derived two additional models with different parameters. Furthermore, we evaluated them, comparing them to a model whose pause duration is constant (Constant Model). The result was that the subjects' impressions, such as “natural,” “like,” and “familiar,” of the Primal Model were more positive than those of the Constant Model. Moreover, when compared with the two additional pause duration models, the Primal Model gave the best results. From these results, we discuss the validity of the Primal Model and the relationship between the parameters and the subjective evaluation.
机译:暂停之前和之后的讲话持续时间被认为是影响暂停持续时间的唯一因素(前边界和后边界影响)。最近,使用由两个词组成的“ XY语音短语”,我们发现,暂停前后的两个语音持续时间之比会影响暂停持续时间(后边界作用)。但是,这种效果是否可用于语音处理应用程序尚不清楚。在这项研究中,我们基于实验数据的多元回归分析(原始模型)开发了一个暂停持续时间的生成模型,并推导了另外两个具有不同参数的模型。此外,我们对它们进行了评估,并将它们与停顿持续时间恒定的模型(恒定模型)进行比较。结果是,主体模型的印象,例如原始模型的“自然”,“喜欢”和“熟悉”,比恒定模型的印象更积极。此外,与两个附加的停顿持续时间模型相比,原始模型提供了最佳结果。从这些结果,我们讨论了原始模型的有效性以及参数与主观评估之间的关系。

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