Speech Technology for Language Learning

这项小型企业创新研究第一阶段计划将探索开发语音互动电脑辅助学习口语所需的技术。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语音项目的一部分。具体来说，本研究将使用统计片段模型来区分学习第二语言的学生正确和不正确的发音。这些模型将以类似于用于独立说话人语音识别的模型的方式进行训练。在第一阶段的研究项目中，将通过收集使用目标语言的学生的试点语音语料库来证明该方法的可行性，根据人类对语音的判断对语料库进行标记，并对该语料库的不同部分进行统计模型的训练和测试。

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.