RI Core: Medium: Structured variability in vocal tract articulation dynamics in speech
RI Core: Medium: Structured variability in vocal tract articulation dynamics in speech
批准号:
2311676
负责人:
Shrikanth Narayanan
金额:
$120.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-05-15 至 2027-04-30
中文摘要
人类产生并使用语言,以各种各样的方式与他人进行交流和互动,传达他们的思想,表达他们的情感。一个人发出丰富的语音涉及到复杂的运动和发声器官的协调,如舌头和下巴,以一种灵活的方式适应相互作用的环境。然而,如何实现这种灵活性的细节还不完全清楚。语言的产生也会受到各种个人情况的影响,包括疾病和障碍。该项目将通过直接观察和模拟讲话中的发音,为理解人类语言在时间上的变化奠定科学基础,无论是在人际交往中还是在人际交往中——在几个小时、几天、几周、几个月和几年里——是如何变化的。这些知识对于推进语音科学和设计健壮的交互式语音技术都是至关重要的。语音研究的一个长期目标是理解和解决其产生中丰富而普遍的可变性,无论是在个体内部还是在个体之间,以及在不同的互动环境中。我们的研究调查了仅通过语音声学无法解决的问题。直接访问声道发音的动态信息,辅以技术和分析的进步,使我们能够检查与语音产生变异性相关的复杂行为,即它在任务和时间上的灵活性和稳定性。该项目将使用先进的实时磁共振成像(rtMRI)和语音产生过程中人类声道运动的计算建模,以了解跨越时间尺度的口语交流的结构和控制,包括个人经历和人际互动,提供前所未有的机会,观察人类如何在时空细节上彼此协作计划和产生语音。该项目的创新包括在两个地点同时和同步地对交谈者的声道进行成像,以了解对话期间的语音生成行为,绘制单个人的语音生成如何自然地变化,并通常在数小时、数天、数月和数年内变化,以及语音灵活性的个体差异如何预测说话者的稳定性。该研究项目通过利用丰富、定量和动态的rtMRI数据的实证工作,将语音科学与工程相结合,并将广泛共享独特的数据、工具和模型。除了语音技术之外,该项目还具有重要的应用意义,因为规范发音及其可变性的知识可以影响语言障碍的评估和补救,通过帮助为从自闭症到痴呆症的各种临床状况提供强大的基于语言的生物标志物。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Humans produce and use speech to communicate and interact with one another, to convey their thoughts and to their express emotions, in a vast variety of ways. The production of the rich sounds of speech by an individual involves intricate movement and coordination of the vocal organs, such as the tongue and jaw, in a manner that is flexible and adaptive to the context of the interaction. Yet, the details of how this flexibility is achieved are not known completely. Speech production can also be affected by a variety of personal circumstances including illness and disorder. The project will create a scientific foundation for understanding how human speech varies across time, both within and across interpersonal interactions––over hours, days, weeks, months and years––by directly observing and modeling articulation during speech. Such knowledge is fundamental to both advancing speech science and to the design of robust interactive speech technologies. A longstanding goal in speech research is to understand and address the rich and pervasive variability in its production, both within and across individuals and for varied interactional contexts. Our research investigates questions not approachable via speech acoustics alone. Direct access to dynamic information on vocal tract articulation, complemented by technology and analysis advances, allow us to examine complex behavior associated with speech production variability—namely, its flexibility and stability over task and over time. The project will use advanced real-time magnetic resonance imaging (rtMRI) and computational modeling of the human vocal tract motion during speech production to understand the structure and control of spoken language communication across timescales, both within individual experience and across interpersonal interactions, offering an unprecedented opportunity to observe how humans plan and produce speech collaboratively with one another at a spatiotemporal detail not possible before. The project innovations include imaging the vocal tracts of conversing speakers simultaneously and synchronously at two sites to understand speech production behavior during a dialog, mapping how a single individual’s production speech production varies naturally and typically over hours, days, months and years, and how individual differences in speech flexibility are predictive of speaker stability. The research program integrates speech science and engineering through empirical work leveraging rich, quantitative, and dynamic articulatory rtMRI data, and will broadly share the unique data, tools and models. The project also has critical applied significance beyond speech technology, as knowledge of normative articulation and its variability can impact the assessment and remediation of speech disorders by helping derive robust speech-based biomarkers for a variety of clinical conditions across the life span from Autism to dementia.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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会议论文
RI: Small: Speaker-Specific Articulatory Strategies
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批准号:1908865
-
项目类别:Continuing Grant
-
资助金额:$47.4万
-
财政年份:2019
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负责人:Shrikanth Narayanan
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依托单位:
RI: Medium: Collaborative Research: Understanding Individual-Level Speech Variability: From Novel Articulatory Data to Robust Speaker Recognition
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批准号:1514544
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项目类别:Continuing Grant
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资助金额:$119.95万
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财政年份:2015
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负责人:Shrikanth Narayanan
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依托单位:
Be a Scientist!
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批准号:1008372
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项目类别:Continuing Grant
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资助金额:$41.89万
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财政年份:2010
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负责人:Shrikanth Narayanan
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依托单位:
Collaborative Research: Computational Behavioral Science: Modeling, Analysis, and Visualization of Social and Communicative Behavior
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批准号:1029373
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项目类别:Continuing Grant
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资助金额:$150.0万
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财政年份:2010
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负责人:Shrikanth Narayanan
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依托单位:
RI: Large: An Integrated Approach to Creating Context Enriched Speech Translation Systems
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批准号:0911009
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项目类别:Continuing Grant
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资助金额:$220.0万
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财政年份:2009
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负责人:Shrikanth Narayanan
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依托单位:
SGER: Exploring Emotional Vocal Productions Through the Use of Real-Time Magnetic Resonance Imaging
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批准号:0844243
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项目类别:Standard Grant
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资助金额:$0.0万
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财政年份:2008
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负责人:Shrikanth Narayanan
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依托单位:
Collaborative Research: Modeling Creative and Emotive Improvisation in Theater Performance
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批准号:0757414
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项目类别:Standard Grant
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资助金额:$42.16万
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财政年份:2008
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负责人:Shrikanth Narayanan
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依托单位:
CAREER: Modeling and Optimizing User-Centric Mixed-Initiative Spoken Dialog Systems
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批准号:0238514
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项目类别:Continuing Grant
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资助金额:$50.0万
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财政年份:2003
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负责人:Shrikanth Narayanan
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依托单位:
IERI: Collaborative Research: Automating Early Assessment of Academic Standards for Very Young Native and Non-Native Speakers of American English
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批准号:0326228
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项目类别:Standard Grant
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资助金额:$0.0万
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财政年份:2003
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负责人:Shrikanth Narayanan
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依托单位:
ITR: A User-centric Content-based Approach to Indexing, Query and Retrieval of Music through Signal Processing and Knowledge-based Methods
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批准号:0219912
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项目类别:Continuing Grant
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资助金额:$50.0万
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财政年份:2002
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负责人:Shrikanth Narayanan
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依托单位:
国内基金
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