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dc.contributor.author Lebar Bajec, Iztok
dc.contributor.author Bajec, Marko
dc.contributor.author Bajec, Žan
dc.contributor.author Rizvič, Mitja
dc.date.accessioned 2022-12-02T10:48:47Z
dc.date.available 2022-12-02T10:48:47Z
dc.date.issued 2022-12-01
dc.identifier.uri http://hdl.handle.net/11356/1737
dc.description This Conformer CTC BPE E2E Automated Speech Recognition model was trained following the NVIDIA NeMo Conformer-CTC 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 training, development and test datasets were based on the Artur dataset and consisted of 630.38, 16.48 and 15.12 hours of transcribed speech in standardised form, respectively. The model was trained for 200 epochs and reached WER 0.0429 on the development and WER 0.0558 on the test dataset.
dc.language.iso slv
dc.publisher Faculty of Computer and Information Science, University of Ljubljana
dc.relation.isreferencedby https://github.com/clarinsi/Slovene_ASR_e2e
dc.rights Apache License 2.0
dc.rights.uri https://opensource.org/licenses/Apache-2.0
dc.rights.label PUB
dc.source.uri https://rsdo.slovenscina.eu/en/speech-technologies
dc.subject speech recognition
dc.subject NeMo
dc.subject model
dc.title Slovene Conformer CTC BPE E2E Automated Speech Recognition model RSDO-DS2-ASR-E2E 2.0
dc.type toolService
metashare.ResourceInfo#ContentInfo.detailedType tool
metashare.ResourceInfo#ResourceComponentType#ToolServiceInfo.languageDependent true
has.files yes
branding CLARIN.SI data & tools
demo.uri https://www.slovenscina.eu/en/razpoznavalnik
contact.person Iztok Lebar Bajec ilb@fri.uni-lj.si Faculty of Computer and Information Science, University of Ljubljana
sponsor Ministry of Culture C3340-20-278001 Development of Slovene in a Digital Environment Other
files.count 1
files.size 451528391


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