ASR Corpus Design for Resource-Scarce Languages

被引：0

作者：

Barnard, Etienne ^{[1
]}

Davel, Marelie ^{[1
]}

van Heerden, Charl ^{[1
]}

机构：

[1] CSIR, Meraka Inst, Human Language Technol Res Grp, Pretoria, South Africa

来源：

INTERSPEECH 2009: 10TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2009, VOLS 1-5 | 2009年

关键词：

speech recognition; corpus design;

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：

We investigate the number of speakers and the amount of data that is required for the development of useable speaker-independent speech-recognition systems in resource-scarce languages. Our experiments employ the Lwazi corpus, which contains speech in the eleven official languages of South Africa. We find that a surprisingly small number of speakers (fewer than 50) and around 10 to 20 hours of speech per language are sufficient for the purposes of acceptable phone-based recognition.

引用

页码：2823 / 2826

页数：4

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