Papers by Gernot Kubin

1 papers
Conversational Speech Recognition Needs Data? Experiments with Austrian German (2022.lrec-1)

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Challenge: Recent advances in self-supervision have allowed such scenarios to take advantage of large amounts of otherwise unrelated data.
Approach: They characterise an Austrian German conversational task using a non-pre-trained baseline and a leave-one-conversation out technique.
Outcome: The proposed model fine-tunes well with a non-pre-trained baseline and shows that the advantage of pre-training arises from the larger database rather than the self-supervision.

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