projecte-aina/stt_ca-es_conformer_transducer_large

NVIDIA Conformer-Transducer Large (ca-es)

Table of Contents

Click to expand

• Model Description
• Intended Uses and Limitations
• How to Get Started with the Model
• Training Details
• Citation
• Additional Information

Summary

The "stt_ca-es_conformer_transducer_large" is an acoustic model based on "NVIDIA/stt_es_conformer_transducer_large" suitable for Bilingual Catalan-Spanisg Automatic Speech Recognition.

Model Description

This model transcribes speech in lowercase Catalan and Spanish alphabet including spaces, and was Fine-tuned on a Bilingual ca-es dataset comprising of 7426 hours. It is a "large" variant of Conformer-Transducer, with around 120 million parameters. See the model architecture section and NeMo documentation for complete architecture details.

Intended Uses and Limitations

This model can be used for Automatic Speech Recognition (ASR) in Catalan and Spanish. It is intended to transcribe audio files in Catalan and Spanish to plain text without punctuation.

Installation

To use this model, Install NVIDIA NeMo. We recommend you install it after you've installed the latest Pytorch version.

pip install nemo_toolkit['all']

For Inference

To transcribe audio in Catalan or in Spanish language using this model, you can follow this example:

import nemo.collections.asr as nemo_asr

nemo_asr_model = nemo_asr.models.EncDecRNNTBPEModel.restore_from(model)
transcription = nemo_asr_model.transcribe([audio_path])[0][0]
print(transcription)

Training Details

Training data

The model was trained on bilingual datasets in Catalan and Spanish, for a total of 7426 hours.

Training procedure

This model is the result of finetuning the base model "Nvidia/stt_es_conformer_transducer_large" by following this tutorial.

Citation

If this model contributes to your research, please cite the work:

@misc{mena2024whisperlarge3catparla,
      title={Bilingual ca-es ASR Model: stt_ca-es_conformer_transducer_large.}, 
      author={Messaoudi, Abir; Külebi, Baybars},
      organization={Barcelona Supercomputing Center},
      url={https://huggingface.co/projecte-aina/stt_ca-es_conformer_transducer_large},
      year={2024}
}

Additional Information

Author

The fine-tuning process was performed during 2024 in the Language Technologies Unit of the Barcelona Supercomputing Center by Abir Messaoudi.

Contact

For further information, please send an email to [email protected].

Copyright

Copyright(c) 2024 by Language Technologies Unit, Barcelona Supercomputing Center.

License

CC-BY-4.0

Funding

This work has been promoted and financed by the Generalitat de Catalunya through the Aina project.

The training of the model was possible thanks to the computing time provided by Barcelona Supercomputing Center through MareNostrum 5.