Fine-tuned MMS outperforms XLS-R on fieldwork ASR with less than one hour of training data, while XLS-R reaches parity beyond one hour.
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Breaking the Transcription Bottleneck: Fine-tuning ASR Models for Extremely Low-Resource Fieldwork Languages
Fine-tuned MMS outperforms XLS-R on fieldwork ASR with less than one hour of training data, while XLS-R reaches parity beyond one hour.