The "stt_los_conformer_transducer_large" is an acoustic model based on "NVIDIA/stt_es_conformer_transducer_large" suitable for Multilingual Automatic Speech Recognition in the languages for Spain (LoS): Catalan, Spanish, Galician, and Euskera
Model Description
This model transcribes speech in lowercase Catalan, Spanish, Galician, and Euskera alphabet including spaces, and was fine-tuned on a multilingual LoS dataset comprising 2700 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, Spanish, Galician, and Euskera. It is intended to transcribe audio files in those languages 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 using this model, you can follow this example:
python
1import nemo.collections.asr as nemo_asr
23nemo_asr_model = nemo_asr.models.EncDecRNNTBPEModel.restore_from(model)4transcription = nemo_asr_model.transcribe([audio_path])[0].text
5print(transcription)
Training Details
Training data
The specific datasets used to create the model are:
In Catalan:
This work is funded by the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the project ILENIA with reference 2022/TL22/00215337.
The training of the model was possible thanks to the computing time provided by Barcelona Supercomputing Center through MareNostrum 5.
