HiTZ
/

Automatic Speech Recognition
NeMo
PyTorch
Basque
speech
audio
Transducer
Conformer
NeMo
Transformer
Eval Results
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- license: cc-by-4.0
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  language:
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  - eu
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  library_name: nemo
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  Copyright (c) 2024 HiTZ Basque Center for Language Technology - Aholab Signal Processing Laboratory, University of the Basque Country UPV/EHU.
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  ## Licensing Information
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- [Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)
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  ## Funding
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  This project with reference 2022/TL22/00215335 has been parcially funded by the Ministerio de Transformación Digital and by the Plan de Recuperación, Transformación y Resiliencia – Funded by the European Union – NextGenerationEU [ILENIA](https://proyectoilenia.es/) and by the project [IkerGaitu](https://www.hitz.eus/iker-gaitu/) funded by the Basque Government.
 
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  ## References
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  - [1] [Conformer: Convolution-augmented Transformer for Speech Recognition](https://arxiv.org/abs/2005.08100)
 
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+ license: apache-2.0
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  language:
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  - eu
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  library_name: nemo
 
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  Copyright (c) 2024 HiTZ Basque Center for Language Technology - Aholab Signal Processing Laboratory, University of the Basque Country UPV/EHU.
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  ## Licensing Information
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+ [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)
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  ## Funding
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  This project with reference 2022/TL22/00215335 has been parcially funded by the Ministerio de Transformación Digital and by the Plan de Recuperación, Transformación y Resiliencia – Funded by the European Union – NextGenerationEU [ILENIA](https://proyectoilenia.es/) and by the project [IkerGaitu](https://www.hitz.eus/iker-gaitu/) funded by the Basque Government.
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+ This model was trained at [Hyperion](https://scc.dipc.org/docs/systems/hyperion/overview/), one of the high-performance computing (HPC) systems hosted by the DIPC Supercomputing Center.
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  ## References
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  - [1] [Conformer: Convolution-augmented Transformer for Speech Recognition](https://arxiv.org/abs/2005.08100)