@inproceedings{canpolat-etal-2020-turkish,
title = "{T}urkish Emotion Voice Database ({T}ur{EV}-{DB})",
author = "Canpolat, Salih Firat and
Ormano{\u{g}}lu, Zuhal and
Zeyrek, Deniz",
editor = "Beermann, Dorothee and
Besacier, Laurent and
Sakti, Sakriani and
Soria, Claudia",
booktitle = "Proceedings of the 1st Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL)",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources association",
url = "https://aclanthology.org/2020.sltu-1.52/",
pages = "368--375",
language = "eng",
ISBN = "979-10-95546-35-1",
abstract = "We introduce the Turkish Emotion-Voice Database (TurEV-DB) which involves a corpus of over 1700 tokens based on 82 words uttered by human subjects in four different emotions (\textit{angry, calm, happy, sad}). Three machine learning experiments are run on the corpus data to classify the emotions using a convolutional neural network (CNN) model and a support vector machine (SVM) model. We report the performance of the machine learning models, and for evaluation, compare machine learning results with the judgements of humans."
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<abstract>We introduce the Turkish Emotion-Voice Database (TurEV-DB) which involves a corpus of over 1700 tokens based on 82 words uttered by human subjects in four different emotions (angry, calm, happy, sad). Three machine learning experiments are run on the corpus data to classify the emotions using a convolutional neural network (CNN) model and a support vector machine (SVM) model. We report the performance of the machine learning models, and for evaluation, compare machine learning results with the judgements of humans.</abstract>
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%0 Conference Proceedings
%T Turkish Emotion Voice Database (TurEV-DB)
%A Canpolat, Salih Firat
%A Ormanoğlu, Zuhal
%A Zeyrek, Deniz
%Y Beermann, Dorothee
%Y Besacier, Laurent
%Y Sakti, Sakriani
%Y Soria, Claudia
%S Proceedings of the 1st Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL)
%D 2020
%8 May
%I European Language Resources association
%C Marseille, France
%@ 979-10-95546-35-1
%G eng
%F canpolat-etal-2020-turkish
%X We introduce the Turkish Emotion-Voice Database (TurEV-DB) which involves a corpus of over 1700 tokens based on 82 words uttered by human subjects in four different emotions (angry, calm, happy, sad). Three machine learning experiments are run on the corpus data to classify the emotions using a convolutional neural network (CNN) model and a support vector machine (SVM) model. We report the performance of the machine learning models, and for evaluation, compare machine learning results with the judgements of humans.
%U https://aclanthology.org/2020.sltu-1.52/
%P 368-375
Markdown (Informal)
[Turkish Emotion Voice Database (TurEV-DB)](https://aclanthology.org/2020.sltu-1.52/) (Canpolat et al., SLTU 2020)
ACL
- Salih Firat Canpolat, Zuhal Ormanoğlu, and Deniz Zeyrek. 2020. Turkish Emotion Voice Database (TurEV-DB). In Proceedings of the 1st Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL), pages 368–375, Marseille, France. European Language Resources association.