Segment-based Acoustic Models with Multi-level Search Algorithms for Continuous Speech Recognition

NSF/DARPA图像理解和语音识别联合倡议的这一奖项是为了表彰用于大词汇量非特定说话人连续语音识别的多级声学和语音模型的研究。奥斯滕多夫和罗利切克博士将使用BBN系统和技术公司的隐马尔可夫语音识别系统作为基准，并将增加多级语音分段建模以提高性能。这笔拨款包括对几名研究生和本科生的支持，以及语音识别研究所需的工作站硬件和软件。

This award in the NSF/DARPA Joint Initiative on Image Understanding and Speech Recognition is for research on multilevel acoustic and phonetic models for large-vocabulary speaker-independent continuous speech recognition. Drs. Ostendorf and Rohlicek will use the hidden-Markov speech recognition system at BBN Systems and Technologies Corporation as a baseline, and will add multilevel phonetic segment modeling to improve performance. The grant includes support for several graduate and undergraduate students, as well as workstation hardware and software needed for speech recognition research.