Robust Knowledge Discovery from Parallel Speech and Text Sources

从并行语音和文本源中进行稳健的知识发现

• 批准号: 9982329
• 负责人: Frederick Jelinek
• 金额: $ 54.64万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-03-01 至 2005-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9982329&HistoricalAwards=false
• 关键词: Robust; Knowledge; Discovery; Parallel; Speech

The goal of this project is to enable information retrieval systems to handle speech-based information by considerably enhancing speech recognition technology. The PI's approach is to align collections of stories from text and speech sources in multiple languages, and to develop methods which exploit the resulting parallelism. The PI will improve acoustic and language models, and will develop iterative recognition methods to facilitate capture of cross-lingual information resident in text and speech. Voice-of-America broadcasts in English, Greek, and a third language to be determined, will provide the data source for this research.

该项目的目标是通过大大增强语音识别技术，使信息检索系统能够处理基于语音的信息。 PI的方法是将来自多种语言的文本和语音来源的故事集合对齐，并开发利用由此产生的并行性的方法。 PI将改进声学和语言模型，并将开发迭代识别方法，以促进捕获驻留在文本和语音中的跨语言信息。 美国之音用英语、希腊语和第三种语言（待定）广播，将为这项研究提供数据来源。