Control strategies for articulatory speech synthesis for natural user interfaces

自然用户界面的发音语音合成控制策略

• 批准号: 506576-2017
• 负责人: Fels, Sidney
• 金额: $ 14.45万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Strategic Projects - Group
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=642092
• 关键词: Control; strategies; articulatory; speech; synthesis

We propose to advance the state of the art of articulatory speech synthesis research by building and evaluating neural activation-based models to drive a parameterized, 3D biomechanical-articulatory speech synthesizer. Our industry partner, CTF (http://www.ctfmeg.com) provides expertise in magnetoencephalography (MEG) and multimodal sensing of the brain and neural pathways, contributing to developing novel low degree-of-freedom (DoF) speech control strategies. The proposed research targets ICT - Human Interaction with Digital Information, as we focus on fundamental aspects of speech-based natural user interfaces. We plan to work backwards from our biomechanically driven speech synthesizer to determine control strategies that take advantage of the coupling afforded by biomechanics to reduce the DoF needed for producing natural sounding speech. Creating low DoF control representations is an important step for creating talking heads that move and sound natural for avatar-type interfaces needed for natural user interfaces. We have three central goals for this project: 1) improving our existing biomechanics-to-speech model, 2) developing neural control topologies, and 3) building control models for the coupled biomechanical-neural system. These goals will converge to synthesize a neurally controlled talking head for use in natural user interface evaluations. As a capstone demonstration, we will explore having a person speak in real-time using the neurally controlled talking head while in the MEG. Our team of established researchers span the fields of expertise for this project. Drs. Fels, Stavness and Gick have published together on the biomechanics of the oral, pharyngeal and laryngeal complex and articulatory control of speech. CTF engineers have over a decade of experience advancing the state of the art of MEG for sensing neural activation. Our team's world-class modeling, simulation, HCI, speech synthesis control and MEG expertise provides a leading-edge opportunity for HQP to learn techniques for 3D physics-based simulation, advanced speech control, machine learning and neural sensing.

我们建议通过建立和评估基于神经激活的模型来驱动参数化的3D生物力学-发音语音合成器，从而推进发音语音合成研究的最新进展。我们的行业合作伙伴CTF （http://www.ctfmeg.com）在脑磁图（MEG）和大脑和神经通路的多模态传感方面提供专业知识，有助于开发新的低自由度（DoF）语音控制策略。拟议的研究目标是ICT -人类与数字信息的交互，因为我们关注基于语音的自然用户界面的基本方面。我们计划从我们的生物力学驱动的语音合成器向后工作，以确定控制策略，利用生物力学提供的耦合来减少产生自然声音所需的DoF。创建低自由度控制表示是为自然用户界面所需的化身类型界面创建移动和声音自然的谈话头的重要步骤。我们的项目有三个中心目标：1)改进现有的生物力学-语音模型，2)开发神经控制拓扑，以及3)建立耦合生物力学-神经系统的控制模型。这些目标将收敛到合成一个神经控制的说话头，用于自然用户界面评估。作为一个顶点演示，我们将探索让一个人在MEG中使用神经控制的说话头实时说话。我们的资深研究人员团队跨越了这个项目的专业领域。Drs。Fels， Stavness和Gick共同发表了关于口腔，咽和喉复合体和语音发音控制的生物力学。CTF工程师有超过十年的经验，推动MEG的艺术状态，以感知神经激活。我们的团队拥有世界一流的建模、仿真、HCI、语音合成控制和MEG专业知识，为HQP学习基于3D物理的仿真、高级语音控制、机器学习和神经传感技术提供了领先的机会。