Longitudinal study of ASR performance on ageing Voices

被引:0
|
作者
Vipperla, Ravichander [1 ]
Renals, Steve [1 ]
Frankel, Joe [1 ]
机构
[1] Univ Edinburgh, Ctr Speech Technol Res, Sch Informat, Edinburgh EH8 9YL, Midlothian, Scotland
关键词
Ageing Voices; longitudinal study; SCOTUS corpus; MLLR;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents the results of a longitudinal study of ASR performance on ageing voices. Experiments were conducted on the audio recordings of the proceedings of the Supreme Court Of The United States (SCOTUS). Results show that the Automatic Speech Recognition (ASR) Word Error Rates (WERs) for elderly voices are significantly higher than those of adult voices. The word error rate increases gradually as the age of the elderly speakers increase. Use of maximum likelihood linear regression (MLLR) based speaker adaptation on ageing voices improves the WER though the performance is still considerably lower compared to adult voices. Speaker adaptation however reduces the increase in WER with age during old age.
引用
收藏
页码:2550 / 2553
页数:4
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