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A Prediction Model for End-of-Utterance Based on Prosodic Features and Phrase-Dependency in Spontaneous Japanese

机译:基于韵律特征和短语相关性的自发日语话语结局预测模型

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This study aims to reveal a clue for predicting end-of-utterance in spontaneous Japanese speech. In casual everyday conversation, participants must predict the ends of utterances of a speaker to perform smooth turn-taking with small gaps or overlaps. Syntactic and prosodic factors are considered to project the end of utterance of speech, and participants utilize these factors to predict the end-of-utterance. In this paper, we focused on the dependency structure among bunsetsu-phrases as a syntactic feature and F0, intensity, and mora duration for bunsetsu-phrases as prosodic features. We investigated the relationship between the position of a bunsetsu-phrase in an utterance and these features. The results showed that a single feature cannot be an authoritative clue that determines the position of bunsetsu-phrases. Next, we constructed a Bayesian hierarchical model to estimate the bunsetsu-phrase position from the syntactic and prosodic features. The results of the model indicated that prosodic features vary in usefulness according to speakers. This suggests that the different combinations of syntactic and prosodic features for each speaker are relevant to predict the ends of utterances.
机译:这项研究旨在揭示预测自发日语语音发音结束的线索。在日常的日常交谈中,参与者必须预测说话者的讲话的结束时间,以便以较小的间隙或重叠进行平稳的转弯。句法和韵律因素被认为可以预测语音的结束,参与者可以利用这些因素来预测语音的结束。在本文中,我们着眼于Bunsetsu短语之间的依存结构作为句法特征,而Bunsetsu短语的F0,强度和m持续时间作为韵律特征。我们调查了在话语中的Bunsetsu短语的位置与这些特征之间的关系。结果表明,单个功能不能成为确定Bunsetsu短语位置的权威线索。接下来,我们构建了一个贝叶斯分层模型,以从句法和韵律特征中估计出宾语短语的位置。该模型的结果表明,韵律特征在有用性方面因说话者而异。这表明每个说话人的句法和韵律特征的不同组合与预测话语的结束有关。

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