Speech Generation for Human-Computer Interaction

本项目的目标是通过提高自动生成的语音质量来提高人机交流的有效性。利用已知的文本生成的副产品--语言结构，本研究在商业合成器中对韵律(即短语、强调和语调)进行了发声水平和对话水平的控制。这种方法--发展意义和韵律结构之间映射的统计模型--是新颖的，因为它强调与可移植到不同任务域/生成器的目标相关联的自动学习算法。这项研究涉及：目标任务域中主动语音的收集和自动韵律标注；使用生成的句法、语义和语篇注释来驱动韵律控制模块；研究韵律在计算机主动性中的作用，例如在澄清或纠错子对话中的作用；以及开发评估语音生成质量及其对人机交互的影响的评估协议。这项研究将通过提供更高质量的语音输出和更灵活的响应生成而使现有的口语界面受益，但它也将为没有视觉显示的人机交互打开应用程序，例如在小型设备中、在基于电话的计算机访问中或为视力受损的人。

The goal of this project is to increase effectiveness of human-computer communication by improving the quality of automatically generated speech. Using the known linguistic structure that is a by-product of text generation, the research investigates both utterance-level and dialog-level control of prosody (i.e. phrasing, emphasis and intonation) i n a commercial synthesizer. The approach -- development of statistical models of the mapping between meaning and prosodic structure -- is novel in its emphasis on automatic learning algorithms associated with the aim of portability to different task domains/generators. The research involves: collection and automatic prosodic labeling of `acted` speech in target task domains; use of generated syntactic, semantic and discourse annotation to drive prosodic control modules; investigation of the role of prosody in computer initiative, e.g. in clarification or error correction subdialogs; and development of evaluation protocols for assessing speech generation quality and its impact on human-computer interaction. The research will benefit existing spoken language interfaces by providing higher quality speech output and more flexibility for response generation, but it will also open up applications for human-computer interaction where a visual display is not available, e.g. in small devices, in telephone-based computer access or for persons who are visually impaired.