facebook/hubert-large-ls960-ft

automatic-speech-recognition model by facebook

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Facebook's Hubert The large model fine-tuned on 960h of Librispeech on 16kHz sampled speech audio. When using the model make sure that your speech input is also sampled at 16Khz. The model is a fine-tuned version of hubert-large-ll60k. 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 applying the prediction loss over the masked regions only,…

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Model overview

facebook/hubert-large-ls960-ft is a automatic-speech-recognition model repository published by facebook on Hugging Face. The source reports the transformers library.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task: automatic-speech-recognition
Library: transformers
Recent downloads (30 days): 314,662
Cumulative likes: 78
Hugging Face trending score: 0
Reported safetensors parameters: Not reported
Architecture: HubertForCTC
License: apache-2.0
Access: Not gated by Hugging Face
Created: 2022-03-02T23:29:05.000Z
Last modified: 2022-05-24T10:43:42.000Z

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Reported languages: en

Base-model lineage was not included.

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