carlosdanielhernandezmena
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README.md
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# faster-whisper-large-v3-ca-3catparla
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```bash
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```
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```python
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from faster_whisper import WhisperModel
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print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
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```
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```bibtex
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@misc{mena2024fastwhis3catparla,
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title={Acoustic Model in Catalan: faster-whisper-large-v3-ca-3catparla.},
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}
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```
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---
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# faster-whisper-large-v3-ca-3catparla
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## Table of Contents
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<details>
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<summary>Click to expand</summary>
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- [Model description](#model-description)
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- [Intended uses and limitations](#intended-uses-and-limitations)
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- [How to use](#how-to-use)
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- [Training](#training)
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- [Evaluation](#evaluation)
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- [Citation](#citation)
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- [Additional information](#additional-information)
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</details>
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## Summary
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The "faster-whisper-large-v3-ca-3catparla" is an acoustic model based on a [faster-whisper](https://github.com/guillaumekln/faster-whisper/tree/master) version of [projecte-aina/whisper-large-v3-ca-3catparla](https://huggingface.co/projecte-aina/whisper-large-v3-ca-3catparla) suitable for Automatic Speech Recognition in Catalan.
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## Model Description
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The "faster-whisper-large-v3-ca-3catparla" is the result of converting the [projecte-aina/whisper-large-v3-ca-3catparla](https://huggingface.co/projecte-aina/whisper-large-v3-ca-3catparla) into a lighter model using a python module called [faster-whisper](https://github.com/guillaumekln/faster-whisper/tree/master).
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The specific dataset used to create the [projecte-aina/whisper-large-v3-ca-3catparla](https://huggingface.co/projecte-aina/whisper-large-v3-ca-3catparla) model is called ["3CatParla"](https://huggingface.co/datasets/projecte-aina/3catparla_asr).
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## Intended Uses and Limitations
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This model can used for Automatic Speech Recognition (ASR) in Catalan. The model is intended to transcribe audio files in Catalan to plain text without punctuation.
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## How to Get Started with the Model
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### Installation
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In order to use this model, you may install [faster-whisper](https://github.com/guillaumekln/faster-whisper/tree/master)
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Create a virtual environment:
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```bash
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python -m venv /path/to/venv
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```
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Activate the environment:
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```bash
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source /path/to/venv/bin/activate
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```
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Install the modules:
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```bash
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pip install faster-whisper
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```
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### For Inference
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In order to transcribe audio in Catalan using this model, you can follow this example:
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```python
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from faster_whisper import WhisperModel
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print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
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```
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## Conversion Details
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### Conversion procedure
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This model is not a direct result of training. It is a conversion of a [Whisper](https://huggingface.co/openai/whisper-large-v3) model using [faster-whisper](https://github.com/guillaumekln/faster-whisper/tree/master). The procedure to create the model is as follows:
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```bash
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ct2-transformers-converter --model projecte-aina/whisper-large-v3-ca-3catparla
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--output_dir faster-whisper-large-v3-ca-3catparla
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--copy_files preprocessor_config.json
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--quantization float16
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```
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## Citation
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If this model contributes to your research, please cite the work:
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```bibtex
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@misc{mena2024fastwhis3catparla,
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title={Acoustic Model in Catalan: faster-whisper-large-v3-ca-3catparla.},
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}
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```
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## Additional Information
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### Author
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The conversion process was perform during July (2024) in the [Language Technologies Unit](https://huggingface.co/BSC-LT) of the [Barcelona Supercomputing Center](https://www.bsc.es/) by [Carlos Daniel Hernández Mena](https://huggingface.co/carlosdanielhernandezmena).
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### Contact
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For further information, please send an email to <langtech@bsc.es>.
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### Copyright
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Copyright(c) 2024 by Language Technologies Unit, Barcelona Supercomputing Center.
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### License
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[Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0)
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### Funding
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This work has been promoted and financed by the Generalitat de Catalunya through the [Aina project](https://projecteaina.cat/).
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The conversion of the model was possible thanks to the compute time provided by [Barcelona Supercomputing Center](https://www.bsc.es/) through MareNostrum 5.
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