Guiding Spoken Dialogue with Computers by Responding to Prosodic Cues

为了进行有效、自然的口语对话，计算机需要做的不仅仅是识别和解释口语单词——它们还需要对单词发音中的韵律信息敏感。为了研究检测和利用韵律线索可以帮助计算机引导口语对话的假设，本案例研究将重点放在一项教育任务上，该任务结合了国家内在重要性和引人注目的方法优势：听孩子大声朗读，并提供口语帮助。该研究侧重于改善对话的四个方面——轮流、处理语音修复、防止对话中断和塑造说话者。在阅读任务中，这些方面包括检测一些具有教学意义的事件，例如读者何时完成一篇文章，何时进行自我纠正，何时在识别单词或理解文章时遇到困难。目标是使用韵律线索来帮助检测这些事件，以便使学生与计算机之间的对话更有效地实现其教育目标。预期的结果包括自动阅读助手的改进，稳健韵律现象的发现，检测它们的方法，以及使用它们实现人与计算机之间优美、有效的口语对话的原则。

To carry on effective, natural, spoken dialogue,computers will need to do more than recognize and interpret spoken words -- they will also need to be sensitive to the prosodic information encoded in how the words are spoken. To investigate the hypothesis that detecting and exploiting prosodic cues can help computers guide spoken dialogue, this case study focuses on an educational task that combines intrinsic national importance with compelling methodological advantages: listening to a child read aloud, and providing spoken assistance. The research focusses on improving four aspects of dialogue -- taking turns, handling speech repairs, preventing dialogue breakdown, and modelling the speaker. In the reading task, these aspects include detecting a number of pedagogically significant events, such as when readers complete a passage, correct themselves, or encounter difficulty in identifying a word or comprehending a passage. The goal is to use prosodic cues to help detect these events in order to make the dialogue between student and computer more effective in achieving its educational objectives . Expected outcomes include improvements in the automated reading assistant, the discovery of robust prosodic phenomena, methods for detecting them, and principles for using them to achieve graceful, effective spoken dialogue between humans and computers.