Acoustic-Phonetic Knowledge and Speech Recognition

在国家科学基金会的支持下，卡罗尔·埃斯皮-威尔逊博士将进行为期三年的跨学科研究。该项目结合了工程学、语音科学和计算语言学的知识和技术，开发了一个强大的自动语音识别系统，该系统适用于大量不同的人群。该项目包括开发(a)针对语音信号中语言信息的声学参数，以及(b)将当前语音知识与强大的统计框架集成在一起的新识别范式。基于知识的语音识别系统是语音感知早期阶段的一个模型。它的发展是一种工具，用于理解和应对由于性别、年龄和情绪状态的差异而在说话者内部和之间发生的语言变化。新的见解将在语音产生，语音感知和声学语音学领域获得。此外，系统的不同组件可以作为语音分析工具，用于各种应用，包括语音编码、自动语音转录、语音增强和语音病理学家及其客户的语音训练辅助工具。

With National Science Foundation support, Dr. Carol Espy-Wilson will conduct three years of interdisciplinary research. This project combines knowledge and techniques from engineering, speech science, and computational linguistics to develop a robust automatic speech recognition system that works well for a large and diverse population. This project includes the development of (a) acoustic parameters that target the linguistic information in the speech signal, and (b) a new paradigm for recognition that integrates current speech knowledge with a powerful statistical framework. The knowledge-based speech recognition system serves as a model of the early stages of speech perception. Its development is a tool for understanding and coping with variation in speech that occurs within and across speakers due to differences in gender, age and emotional states. New insights will be gained in the areas of speech production, speech perception, and acoustic phonetics. Further, different components of the system can serve as speech analysis tools to be used in various applications including speech coding, automatic speech transcription, speech enhancement, and speech training aids for speech pathologists and their clients.