Please use this identifier to cite or link to this item:
http://hdl.handle.net/10174/34466
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| Title: | Optimized European Portuguese Speech-To-Text using Deep Learning |
| Authors: | Medeiros, Eduardo
Corado, Leonel
Rato, Luis
Quaresma, Paulo
Salgueiro, Pedro |
| Keywords: | speech
text
transfer
deep learning
portuguese |
| Issue Date: | Oct-2022 |
| Publisher: | APRP |
| Citation: | Medeiros, E., Corado,L., Rato, L., Quaresma, P., Salgueiro, P., Optimized European Portuguese Speech-To-Text using Deep Learning, RECPAD2022, 28th Portuguese Conference on Pattern Recognition, School of Technology and Management – Politécnico de Leiria, 2022. |
| Abstract: | We have developed an ASR system for European Portuguese implement ing the QuartzNet [3] architecture with the NeMo [4] framework. Two approaches were used in this work: from scratch and using transfer learning. The experiments were data-driven focused instead of algorithm finetuning. Experiments confirm that models developed using transfer learning have shown better results (WER=0.0513) than developing models from scratch (WER=0.1945). |
| URI: | http://hdl.handle.net/10174/34466 |
| Type: | article |
| Appears in Collections: | INF - Artigos em Livros de Actas/Proceedings
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