Exploring ASR fine-tuning on limited domain-specific data for low-resource languages
Franco Mak,
Avashna Govender,
Jaco Badenhorst
Abstract:The majority of South Africa's eleven languages are low-resourced, posing a major challenge to Automatic Speech Recognition (ASR) development. Modern ASR systems require an extensive amount of data that is extremely difficult to find for lowresourced languages. In addition, available speech and text corpora for these languages predominantly revolve around government, political and biblical content. Consequently, this hinders the ability of ASR systems developed for these languages to perform well especially wh… Show more
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