咨询与建议

看过本文的还看了

相关文献

该作者的其他文献

文献详情 >Speaker-adapted confidence mea... 收藏

Speaker-adapted confidence measures for speech recognition of video lectures

为录像讲课 <sup></sup> 的语音识别的改编说话者的信心措施

作     者:Sanchez-Cortina, Isaias Andres-Ferrer, Jesus Sanchis, Alberto Juan, Alfons 

作者机构:Univ Politecn Valencia DSIC MLLP E-46022 Valencia Spain 

出 版 物:《COMPUTER SPEECH AND LANGUAGE》 (计算机语音与语言)

年 卷 期:2016年第37卷

页      面:11-23页

核心收录:

学科分类:08[工学] 0812[工学-计算机科学与技术(可授工学、理学学位)] 

基  金:European Union Spanish MINECO [TIN2009-14511, TIN2012-31723] FPI Scholarship [BES-2010-033005] 

主  题:Confidence measures Speech recognition Speaker adaptation Log-linear models Online video lectures 

摘      要:Automatic speech recognition applications can benefit from a confidence measure (CM) to predict the reliability of the output. Previous works showed that a word-dependent native Bayes (NB) classifier outperforms the conventional word posterior probability as a CM. However, a discriminative formulation usually renders improved performance due to the available training techniques. Taking this into account, we propose a logistic regression (LR) classifier defined with simple input functions to approximate to the NB behaviour. Additionally, as a main contribution, we propose to adapt the CM to the speaker in cases in which it is possible to identify the speakers, such as online lecture repositories. The experiments have shown that speaker-adapted models outperform their non-adapted counterparts on two difficult tasks from English (***) and Spanish (poliMedia) educational lectures. They have also shown that the NB model is clearly superseded by the proposed LR classifier. (C) 2015 Elsevier Ltd. All rights reserved.

读者评论 与其他读者分享你的观点

用户名:未登录
我的评分