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:
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.
Runs of BSC-LT stt_los_conformer_transducer_large on huggingface.co
40
Total runs
-2
24-hour runs
22
3-day runs
23
7-day runs
22
30-day runs
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