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---
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extra_gated_prompt: Please read Apache License, Version 2.0 before downloading this model.
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extra_gated_fields:
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Country: country
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Affiliation: text
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I agree ALL the statements in Apache License, Version 2: checkbox
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extra_gated_button_content: Acknowledge license
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license: apache-2.0
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language:
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- ja
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pipeline_tag: feature-extraction
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tags:
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- hubert
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- speech
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---
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# `imprt/kushinada-hubert-base`
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This is a Japanese HuBERT Base model pre-trained using 62215 hours of audio extracted from large-scale Japanese TV broadcast audio data by voice activity detection.
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This model was trained using code from the [official repository](https://github.com/facebookresearch/fairseq/).
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## Usage
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```python
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import soundfile as sf
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from transformers import AutoFeatureExtractor
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model = "imprt/kushinada-hubert-base"
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feature_extractor = AutoFeatureExtractor.from_pretrained(model)
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audio_file="/path/to/16k_audio_file"
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audio_input, sr = sf.read(audio_file)
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feature_extractor(audio_input, sampling_rate=sr)
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```
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## References
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```bibtex
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@article{journals/corr/abs-2106-07447,
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added-at = {2021-06-16T00:00:00.000+0200},
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author = {Hsu, Wei-Ning and Bolte, Benjamin and Tsai, Yao-Hung Hubert and Lakhotia, Kushal and Salakhutdinov, Ruslan and Mohamed, Abdelrahman},
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biburl = {https://www.bibsonomy.org/bibtex/2435bd8c9ac37a4eab204ded15e9f8918/dblp},
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ee = {https://arxiv.org/abs/2106.07447},
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interhash = {c85407653eddc9c9256c261afe8d6954},
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intrahash = {435bd8c9ac37a4eab204ded15e9f8918},
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journal = {CoRR},
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keywords = {dblp},
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timestamp = {2024-04-08T22:55:35.000+0200},
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title = {HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units.},
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url = {http://dblp.uni-trier.de/db/journals/corr/corr2106.html#abs-2106-07447},
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volume = {abs/2106.07447},
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year = 2021
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}
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```
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## License
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[Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)
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