AN IMPROVED RECURSIVE ALGORITHM FOR AUTOMATIC ALIGNMENT OF COMPLEX LONG AUDIO

摘要：

In this paper we present an approach for automatic alignment of long audio data with varied acoustic conditions to their corresponding transcripts in an effective manner. Accurate time-aligned transcripts provide easier access to audio materials by aiding applications such as the indexing, summarizing and retrieving of audio segments. Accurate time alignments are also necessary for labeling the training data for a speech recognizers acoustic model. We provide an improved recursive technique of speech recognition with a gradually self-adaptive language model and acoustic model.

关键词： Speech alignment dynamic programming acoustic re-estimation language model adaptation

作者: He Kejia Liu Gang Tang Jie Guo Jun

作者单位: Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications, China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Network Infrastructure and Digital Content(2009年IEEE网络基础设施与数字内容国际会议 IEEE IC-NIDC2009)

会议地点: 北京

会议语种:英文

页码: 690-694

在线出版日期: 2009-11-06（万方平台首次上网日期，不代表论文的发表时间）