Using Automatic Speech Recognition to Improve Reading Comprehension...

缺乏阅读理解能力已成为一个关键的 国家问题;工作场所文盲花费数十亿美元 企业再培训、工业事故和 降低竞争力。 虽然智能辅导 系统可以帮助，他们无法看到或听到学生 限制了他们诊断和补救的有效性 理解力不足。 该试点项目将测试解决以下问题的可行性： 这种基本的局限性， 最新进展使跨学科方法成为可能 在高速计算，自动语音处理， 阅读研究和人工智能。 它将 监控幼儿小学科学口语阅读 材料，使用连接语音的自动识别 和韵律特征（如犹豫和语调）， 提取教师识别的信息并阅读 专家们认为这在教学上是有用的。 成功将奠定 为后续工作奠定了基础， 交互式教学软件。 这项工作的意义包括打开一个强大的 基于双向的学生与计算机之间的新通道 语音交流，实现创新教程 技术领域的应用， 至关重要。 受影响的包括数百万1-3年级的儿童， 口语阅读是最重要的 然而结果 应适用于工业培训，成人文盲， 英语作为第二语言，以及外语学习。

Deficiency in reading comprehension has become a critical national problem; workplace illiteracy costs billions of dollars in corporate retraining, industrial accidents, and reduced competitiveness. Although intelligent tutoring systems could help, their inability to see or hear students limits their effectiveness in diagnosing and remediating deficits in comprehension. This pilot project will test the feasibility of addressing this fundamental limitation by using a novel interdisciplinary approach made possible by recent advances in high-speed computing, automated speech processing, reading research, and artificial intelligence. It will monitor children's oral reading of elementary science material, using automated recognition of connected speech and prosodic features (such as hesitation and intonation) to extract information identified by teachers and reading experts as pedagogically useful. Success will lay the foundation for follow-on work to exploit this information in interactive instructional software. The significance of this work includes opening a powerful new channel between student and computer based on two-way speech communication, enabling innovative tutorial applications in technical areas where comprehension is vital. Those affected include millions of children in grades 1-3, where oral reading is most important. However, the results should apply to industrial training, adult illiteracy, English as a second language, and foreign language study.