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HuBERT Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units by somilcodes is a document available to read on EtoBox.

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The document presents HuBERT, a self-supervised speech representation learning model that addresses challenges in speech signal processing by using masked prediction of hidden units. It employs an offline clustering step to generate labels for training, allowing the model to learn acoustic and language representations without relying on large labeled datasets. HuBERT demonstrates significant performance improvements over existing models like wav2vec 2.0 on various benchmarks, making it suitable for applicat

Author

somilcodes

Language

EN