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dc.contributor.author Žgank, Andrej
dc.contributor.author Verdonik, Darinka
dc.contributor.author Boto, Sanja
dc.contributor.author Donaj, Gregor
dc.date.accessioned 2026-09-14T16:29:21Z
dc.date.available 2026-09-14T16:29:21Z
dc.date.issued 2026-08-31
dc.identifier.uri http://hdl.handle.net/11356/2484
dc.description This resource provides automatic speech recognition (ASR) models for the Slovenian Gail Valley dialect, developed using the open-source WeNet 3.1 framework. The models were trained on 84.25 hours of speech from the Corpus of the Gail Valley dialect Zila 1.0 (http://hdl.handle.net/11356/2257). The system employs a hybrid CTC/attention architecture with a Conformer encoder and Transformer decoder. The log-Mel filterbank features were used for training. The final averaged model achieves a word error rate of 24.64% and a character error rate of 12.05%. Models are provided in WeNet and ONNX formats, supporting local, server-based, and GPU-accelerated inference and deployment.
dc.language.iso slv
dc.publisher University of Maribor, Faculty of Electrical Engineering and Computer Science
dc.publisher Mohorjeva družba / Hermagoras Verein
dc.relation.isreferencedby https://doi.org/10.63317/3fhhk948chhm
dc.rights Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.rights.uri https://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rights.label PUB
dc.source.uri https://lingua.mohorjeva.at/zila-digital-zila-digital
dc.subject automatic speech recognition
dc.subject dialect
dc.title Gail Valley dialect E2E Automatic Speech Recognition model Zila 1.0
dc.type toolService
metashare.ResourceInfo#ContentInfo.detailedType tool
metashare.ResourceInfo#ResourceComponentType#ToolServiceInfo.languageDependent true
has.files yes
branding CLARIN.SI data & tools
contact.person Andrej Zgank andrej.zgank@um.si University of Maribor, Faculty of Electrical Engineering and Computer Science
sponsor European Regional Development Fund within the framework of the Interreg Slovenia–Austria Programme 2021–2027 and the State of Carinthia SI-AT00017, ATU25358305 INTERREG-Projekt "LINGUA" SI-AT00017 Other
files.count 1
files.size 548440202


 Datoteke v tem vnosu

Icon
Ime
ZilaASRmodels.zip
Velikost
523.03 MB
Format
application/zip
Opis
Gail Valley ASR models Zila
MD5
88d4b29235102acd02ddf3ea2159e8e4
 Prenesi datoteko  Predogled
 Predogled datoteke  
  • ZilaASRmodels
    • copyright.txt401 B
    • Doc
      • Zila-ASR-DOC_v1.0.pdf248 kB
    • readme.txt1 kB
    • Zila-runtime
      • copyright.txt401 B
      • final.zip188 MB
      • train_units.txt68 kB
    • Zila-ONNX
      • train.yaml1 kB
      • copyright.txt401 B
      • onnx-gpu-model
        • config.yaml64 B
        • decoder.onnx51 MB
        • encoder.onnx137 MB
      • global_cmvn2 kB
      • train_unigram.model318 kB
      • train_units.txt68 kB
    • Zila-devel
      • train.yaml1 kB
      • copyright.txt401 B
      • avg_10.pt188 MB
      • global_cmvn2 kB
      • train_unigram.model318 kB
      • train_units.txt68 kB

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