Speech Technology for Language Learning

这个小企业创新研究第一阶段项目将探索所需的技术，使语音交互式计算机辅助学习口语的发展。该项目将利用麻省理工学院开发的最先进的语音识别和理解技术，作为ARPA语音计划的一部分。具体来说，拟议的工作将使用统计段模型来区分正确和不正确的发音学习第二语言的学生。这些模型将以与用于说话者无关语音识别的模型类似的方式进行训练。在第一阶段的研究项目中，这种方法的可行性将通过收集一个学生说目标语言的试点语音语料库来证明，语料库将根据人类对发音的判断进行标记，统计模型将在这个语料库的不同部分上进行训练和测试。

This Small Business Innovation Research Phase I project will explore the technology needed to allow the development of voice-interactive computer aids for learning spoken languages. The project will make use of state-of-the-art speech recognition and understanding technology developed at MIT as part of the ARPA speech program. Specifically, the proposed work will use statistical segmental models to distinguish between correct and incorrect pronunciations by students learning a second language. These models will be trained in a similar way to the models used for speaker-independent speech recognition. In the Phase I research project, the feasibility of this approach will be shown by collecting a pilot speech corpus of students speaking the target language, the corpus will be labeled according to human judgments of pronunciation, and statistical models will be trained and tested on separate portions of this corpus.