May 15, 2024, 4:47 a.m. | Valentin Vielzeuf

cs.CL updates on

arXiv:2405.08402v1 Announce Type: new
Abstract: Self-supervised learning has shown great success in Speech Recognition. However, it has been observed that finetuning all layers of the learned model leads to lower performance compared to resetting top layers. This phenomenon is attributed to the ''autoencoder'' behavior: top layers contain information closer to the input and are less suitable for tasks that require linguistic information, such as Speech Recognition.To better our understanding of this behavior, we propose to study the evolution of high-level …

abstract arxiv autoencoder behavior finetuning focus however leads performance pretraining recognition self-supervised learning speech speech recognition success supervised learning type

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