Open Source German Distant Speech Recognition: Corpus and Acoustic Model

被引：17
|
作者：
Radeck-Arneth, Stephan [1 ,2 ]
Milde, Benjamin [1 ]
Lange, Arvid [1 ,2 ]
Gouvea, Evandro
Radomski, Stefan [1 ]
Muehlhaeuser, Max [1 ]
Biemann, Chris [1 ]
机构：
[1] Tech Univ Darmstadt, Dept Comp Sci, Language Technol Grp, Darmstadt, Germany
[2] Tech Univ Darmstadt, Dept Comp Sci, Telecooperat Grp, Darmstadt, Germany
来源：
TEXT, SPEECH, AND DIALOGUE (TSD 2015) | 2015年 / 9302卷
关键词：
German speech recognition; Open source; Speech corpus; Distant speech recognition; Speaker-independent;
D O I：
10.1007/978-3-319-24033-6_54
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We present a new freely available corpus for German distant speech recognition and report speaker-independent word error rate (WER) results for two open source speech recognizers trained on this corpus. The corpus has been recorded in a controlled environment with three different microphones at a distance of one meter. It comprises 180 different speakers with a total of 36 hours of audio recordings. We show recognition results with the open source toolkit Kaldi (20.5% WER) and PocketSphinx (39.6% WER) and make a complete open source solution for German distant speech recognition possible.
引用
收藏
页码：480 / 488
页数：9
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