@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://preview.aclanthology.org/add-emnlp-2024-awards/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."
}