Hubert Base Facebook's Hubert The base model pretrained on 16kHz sampled speech audio. When using the model make sure that your speech input is also sampled at 16Khz. Note : This model does not have a tokenizer as it was pretrained on audio alone. In order to use this model speech recognition , a tokenizer should be created and the model should be fine tuned on labeled text data. Check out this blog for more in detail explanation of how to fine tune the model. Paper Authors: Wei Ning Hsu, Benjamin Bolte, Yao Hung Hubert Tsai, Kushal Lakhotia, Ruslan Salakhutdinov, Abdelrahman Mohamed Abstract Self supervised approaches for speech representation learning are challenged by three unique problems: (1) there are multiple sound units in each input utterance, (2) there is no lexicon of input sound units during the pre training phase, and (3) sound units have variable lengths with no explicit segmentation. To deal with these three problems, we propose the Hidden Unit BERT (HuBERT) approach for self supervised speech representation learning, which utilizes an offline clustering step to provide aligned target labels for a BERT like prediction loss. A key ingredient of our approach is applyin…
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