Speech Prosody and Articulatory Dynamics in Spoken Language

描述(由申请人提供)：语言的一个强有力的交际方面是韵律，它使用音调、响度、局部调频和停顿来表示其信息和情感内容。由于神经损伤，如中风或自闭症谱系障碍导致的言语产生缺陷，通常以韵律异常为特征。该研究计划的长期目标是了解语言结构和交际语境如何制约说话过程中发音运动的时空实现。我们的语言学家兼工程师团队在发音模式的层面上研究了韵律的“签名”。这一建议的具体目的是理解和模拟说话者如何根据语流中断的认知源来差异化地调制发音手势的时空组织，以及当说话者彼此交互时，交际语境如何影响发音中的语音流的时间流。我们概述了一种研究策略，研究语音开始/停止与发音控制和协调之间的关系。除了语言结构之外，演讲还可以出于各种原因开始、停顿或停止 短语边缘。语流中的一些中断可能是认知上的“有计划的”，例如对话中的对话者话轮转换。语音流中的其他干扰可能是“计划外的”，例如中断和单词查找挑战。我们的方法调查了在话轮转换和结构化对话中的打断以及由于认知言语规划原因而出现的停顿附近的声道中的语音清晰度。我们用短语连接和停顿的计算建模以及机器学习方法来对不同来源的语音中断进行分类，以补充这项实验工作。具体的目标将通过使用磁力计系统收集的发音运动数据来跟踪口腔内的运动，并使用我们团队的语音产生计算模型来实现。实验工作和伴随而来的发音发现的计算模拟将提供发音模式是如何被更大的话语信息结构和交际语境中的言语规划需求塑造的方式的轮廓。

DESCRIPTION (provided by applicant): One powerfully communicative aspect of language is prosody, which is the use of pitch, loudness, local rate modulation, and pauses in speech to signal its informational and affective content. Speech production deficits due to neurological damage such as stroke or due to Autism Spectrum Disorder are often characterized by prosodic irregularities. The long term objective of the proposed research program is to understand how linguistic structure and communicative context condition the spatiotemporal realization of articulatory movement during speaking. Our linguist-engineer team studies the "signatures" of prosody at the level of articulatory patterning. The specific aims of this proposal are to understand and model how speakers differentially modulate the spatiotemporal organization of articulatory gestures as a function of the cognitive source of a break in the speech stream and how the communicative context influences the temporal flow of the speech stream in articulation as speakers interact with one another. We outline a research strategy that investigates the relation between speech initiation/cessation and the control and coordination of articulation. Speech may start, pause, or cease for a variety of reasons in addition to linguistically structured phrase edges. Some breaks in the speech stream may be cognitively "planned," such as interlocutor turn-taking in discourse. Other disruptions in the speech stream might be "unplanned," such as interruptions and word finding challenges. Our approach investigates the articulation of speech in the vocal tract at turn-taking and interruptions in structured dialogue and in the vicinity of pauses that occur for cognitive speech planning reasons. We complement this experimental work with computational modeling of phrasal junctures and pauses, and with machine learning approaches to classifying breaks in speech arising from differing sources. The specific aims will be pursued by using articulatory movement data collected with magnetometer systems for tracking movement inside the mouth and by using our team's computational model of speech production. The experiment work and the concomitant computational modeling of the articulatory findings will provide a profile of the manner in which articulatory patterning is shapd by the larger informational structuring of utterances and by the demands of speech planning in a communicative context.