Gail Valley dialect E2E Automatic Speech Recognition model Zila 1.0

  Authors

Žgank, Andrej ; Verdonik, Darinka ; Boto, Sanja and Donaj, Gregor

  Item identifier

http://hdl.handle.net/11356/2484

 Project URL

https://lingua.mohorjeva.at/zila-digital-zila-digital

 Referenced by

https://doi.org/10.63317/3fhhk948chhm

 Date issued

2026-08-31

 Type

toolService

 Language(s)

Slovenian

 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.

 Publisher

University of Maribor, Faculty of Electrical Engineering and Computer Science

 

Mohorjeva družba / Hermagoras Verein

 Acknowledgement

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"

 Subject(s)

automatic speech recognition dialect

 Collection(s)

CLARIN.SI data & tools

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