ASR corpus design for resource-scarce languages

Abstract

We investigate the number of speakers and the amount of data that is required for the development of useable speakerindependent 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. Index Terms: speech recognition, corpus design