Order-Free Spoken Term Detection

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)(2015)

引用 8|浏览48
暂无评分
摘要
In this paper, we propose Time-Marked Word (TMW) lists as a replacement for the lattices and Confusion Networks (CNs) widely used as indexing vehicles for Spoken Term Detection (STD). In a TMW list, candidates are simply tagged with posterior probabilities and time information and stored as a large list of words: the additional ordering present in a lattice or CN is discarded. TMW lists compactly summarize a large ASR search space. Representing a large search space is critical for STD metrics such as ATWV that heavily penalize misses of rare keywords. Comparisons on the OpenKWS 2014 Tamil limited language pack task [1] show that the new TMW-based indexing results in better performance while being faster and having a smaller footprint.
更多
查看译文
关键词
keyword search,spoken term detection,keyword spotting,audio indexing,confusion networks
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要