使用不同特征集的希伯来语韵律特征标准

Ben Fishman, I. Opher
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引用次数: 0

摘要

韵律在人类日常交流中是必不可少的,它提供了意图和意义的重要信息。它用于微妙的表达,如讽刺,也用于表示更常见的表达,如问题或声明,甚至可以表明说话者的生理或情绪状况。在我们之前的工作中,我们提出了一个韵律特征标准(PFC),用于评估从语音信号中提取的特征的韵律性质。PFC分数为我们提供了一种对特征进行排序的方法,并确定声学或光谱特征是否携带韵律信息。在本文中,我们继续探索这一机制,使用OpenSMILE工具包,这是一个广泛用于声学分析和韵律研究的标准特征集。我们的实验是使用专门为韵律研究设计的希伯来语语音数据集进行的。我们分别对每个特征应用PFC,从而对不同的特征进行排序。然后,我们将这个排名与基于分类的相同特征排名进行比较。此外,我们还展示了使用多个特征表示的降维来可视化PFC思想。这两个测试都验证了PFC分数的使用,用于评估特定韵律类特征的韵律性质。
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Prosodic Feature Criterion for Hebrew Using Different Feature Sets
Prosody is essential for everyday human communication and provides important information about intention and meaning. It is used for subtle expressions such as sarcasm as well as for denoting more common expressions like questions or declarations and even can indicate the physiological or emotional condition of a speaker. In our previous work we presented a Prosodic Feature Criterion (PFC) for evaluating the prosodic nature of a feature that was extracted from speech signal. The PFC score provides us with a way to rank the features and determine whether an acoustic or spectral feature carries prosodic information. In this paper we continue to explore this mechanism, using the OpenSMILE toolkit, which is a standard set of features widely used for acoustic analysis and prosody research. Our experiments are carried out using a dataset of Hebrew utterances specifically designed for prosody research. We apply the PFC over each feature separately, thus ranking the different features. We then compare this ranking with classification based ranking of the same features. In addition we show visualization of the PFC idea using dimension reduction of multiple features representation. Both these tests, validate the use of the PFC score, for evaluating the prosodic nature of a feature in regards to specific prosody classes.
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