Experimental Comparison of Text Information based Punctuation Recovery Algorithms in Real Data
Chen, Xiao; Ke, Dengfeng; Xu, Bo
2013-10
会议名称International Conference on Computer Science and Network Technology
会议录名称Proceedings of the Third International Conference on Computer Science and Network Technology
会议日期12-13
会议地点Dalian
摘要
Punctuation recovery is very important for automatic speech recognition (ASR). It greatly improves readability of transcripts and user experience, and facilitates following natural language processing tasks. The text information based method is one of the basic solutions of punctuation recovery. For analyzing the features of these algorithms, improving them and using them to develop practical system, this paper evaluates text information based punctuation recovery algorithms (HELM, CRF, RNNLM and GTI) in real data. Results show that GTI outperforms other algorithms for punctuation recovery, and ASR’s error is the main cause of performance degradation of all punctuation recovery algorithms. Finally, some suggestions are given.
关键词Punctuation Recovery Real Data Text Information
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/11822
专题数字内容技术与服务研究中心_听觉模型与认知计算
通讯作者Chen, Xiao
作者单位Institute of Automation, Chinese Academy of Sciences
推荐引用方式
GB/T 7714
Chen, Xiao,Ke, Dengfeng,Xu, Bo. Experimental Comparison of Text Information based Punctuation Recovery Algorithms in Real Data[C],2013.
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