Slovene Conformer CTC BPE E2E Automated Speech Recognition model PROTOVERB-ASR-E2E 1.0

  Avtorji

Lebar Bajec, Iztok and Bajec, Marko

  Identifikator vnosa

http://hdl.handle.net/11356/2024

 URL projekta

https://www.inst-krim.si/project/proteverb/

 Datum objave

2025-04-17

 Vrsta

toolService

 Jezik(i)

Slovenian

 Opis

This Conformer CTC BPE E2E Automated Speech Recognition model was trained following the NVIDIA NeMo Conformer-CTC fine-tuning recipe (for details see the official NVIDIA NeMo NMT documentation, https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/asr/intro.html, and NVIDIA NeMo GitHub repository https://github.com/NVIDIA/NeMo). It provides functionality for transcribing Slovene speech to text. The starting point was the Conformer CTC BPE E2E Automated Speech Recognition model RSDO-DS2-ASR-E2E 2.0, which was fine-tuned on the Protoverb closed dataset. The model was fine-tuned for 20 epochs, which improved the performance on the Protoverb test dataset for 9.8% relative WER, and for 3.3% relative WER on the Slobench dataset.

 Izdajatelj

Faculty of Computer and Information Science, University of Ljubljana

 Zahvala

ARIS in MDP V5-2265 "Proteverb – Pravni, etični in tehnološki vidiki obdelave besedilnih in govornih virov podatkov za znanstvene, raziskovalne in razvojne namene"

 Ključne besede

speech recognition NeMo model

 Zbirke

CLARIN.SI data & tools

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