ASR corpus design for resource-scarce languages
نویسندگان
چکیده
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.
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Efficient Harvesting of Internet Audio for Resource-Scarce ASR
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