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Self-supervised learning has emerged as a key approach for learning generic representations from speech data. Despite promising results in downstream tasks such as speech recognition, speaker verification, and emotion recognition, a significant numbe
Externí odkaz:
http://arxiv.org/abs/2407.21066
Fine-tuning of self-supervised models is a powerful transfer learning method in a variety of fields, including speech processing, since it can utilize generic feature representations obtained from large amounts of unlabeled data. Fine-tuning, however
Externí odkaz:
http://arxiv.org/abs/2212.02780