Face-domain-specific automatic speech recognition models

  Authors

Dobrišek, Simon ; Križaj, Janez ; Ivanovska, Marija and Grm, Klemen

  Item identifier

http://hdl.handle.net/11356/1749

 Project URL

https://rsdo.slovenscina.eu/govorne-tehnologije

 Referenced by

https://github.com/clarinsi/rsdo_fdsasr_v2

 Date issued

2023-02-24

 Type

toolService

 Language(s)

Slovenian

 Description

This entry contains all the files required to implement face-domain-specific automatic speech recognition (ASR) applications using the Kaldi ASR toolkit (https://github.com/kaldi-asr/kaldi), including the acoustic model, language model, and other relevant files. It also includes all the scripts and configuration files needed to use these models for implementing face-domain-specific automatic speech recognition. The acoustic model was trained using the relevant Kaldi ASR tools (https://github.com/kaldi-asr/kaldi) and the Artur speech corpus (http://hdl.handle.net/11356/1776; http://hdl.handle.net/11356/1772). The language model was trained using the domain-specific text data involving face descriptions obtained by translating the Face2Text English dataset (https://github.com/mtanti/face2text-dataset) into the Slovenian language. These models, combined with other necessary files like the HCLG.fst and decoding scripts, enable the implementation of face-domain-specific ASR applications. Two speech corpora ("test" and "obrazi") and two Kaldi ASR models ("graph_splosni" and "graph_obrazi") can be selected for conducting speech recognition tests by setting the variable "graph" and "test_sets" in the "local/test_recognition.sh" script. Acoustic speech features can be extracted and speech recognition tests can be conducted using the "local/test_recognition.sh" script. Speech recognition test results can be obtained using the "results.sh" script. The KALDI_ROOT environment variable also needs to be set in the script "path.sh" to set the path to the Kaldi ASR toolkit installation folder.

 Publisher

Faculty of Electrical Engineering, University of Ljubljana

 Acknowledgement

Ministry of Culture C3340-20-278001 "Development of Slovene in a Digital Environment"

 Subject(s)

automatic speech recognition acoustic model language model Kaldi ASR toolkit

 Collection(s)

CLARIN.SI data & tools

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