NVIDIA Conformer-Transducer Large (ca-es)
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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
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.
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Model tree for projecte-aina/stt_ca-es_conformer_transducer_large
Base model
nvidia/stt_es_conformer_transducer_largeCollection including projecte-aina/stt_ca-es_conformer_transducer_large
Evaluation results
- Test WER on CV Benchmark Catalan Accentstest set self-reported2.503
- Test WER on Mozilla Common Voice 17.0test set self-reported3.880