摘要
针对语音关键词检索中的集外词问题,提出基于最大互信息-最小描述长度(MMI-MDL)的子词集构建算法。根据子词对的互信息挑选聚合对,通过MDL准则判断是否聚合成新的子词。使用该子词集把单词映射成子词的组合用于检索。实验结果表明,与已有的MDL子词集构建算法相比,由MMI-MDL方法得到的子词集对检索性能有较大提高,在相同精确率指标下,集外词的召回率相对MDL算法提高12.1%。
In order to solve the Out-of-Vocabulary(OOV) problem in speech retrieval tasks,this paper presents a construction algorithm of sub-word units based on Maximum Mutual Information and Minimum Description Length(MMI-MDL).It selects candidate pairs according to the mutual information of sub-word pairs,judges whether combining the pairs to a new sub-word through MDL.After getting the sub-word set,map the word into sub-word for retrieval.Experimental results show that compared with the MDL algorithm,the proposed method has a better performance,and achieves a 12.1% relative improvement on the OOV recall rate.
出处
《计算机工程》
CAS
CSCD
2012年第24期251-253,257,共4页
Computer Engineering
基金
国家自然科学基金资助项目(61170197)
清华大学自主科研计划基金资助项目(2011thz0)
关键词
集外词
语音检索
子词
最小描述长度
最大互信息
词格网络
Out-of-Vocabulary(OOV)
speech retrieval
sub-word
Minimum Description Length(MDL)
Max Mutual Information(MMI)
word lattice network