Emotionlines: An emotion corpus of multi-party conversations

Sheng Yeh Chen, Chao Chun Hsu, Chuan Chun Kuo, Ting Hao Kenneth Huang, Lun Wei Ku

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Feeling emotion is a critical characteristic to distinguish people from machines. Among all the multi-modal resources for emotion detection, textual datasets are those containing the least additional information in addition to semantics, and hence are adopted widely for testing the developed systems. However, most of the textual emotional datasets consist of emotion labels of only individual words, sentences or documents, which makes it challenging to discuss the contextual flow of emotions. In this paper, we introduce EmotionLines, the first dataset with emotions labeling on all utterances in each dialogue only based on their textual content. Dialogues in EmotionLines are collected from Friends TV scripts and private Facebook messenger dialogues. Then one of seven emotions, six Ekman's basic emotions plus the neutral emotion, is labeled on each utterance by 5 Amazon MTurkers. A total of 29,245 utterances from 2,000 dialogues are labeled in EmotionLines. We also provide several strong baselines for emotion detection models on EmotionLines in this paper.

Original languageEnglish (US)
Title of host publicationLREC 2018 - 11th International Conference on Language Resources and Evaluation
EditorsHitoshi Isahara, Bente Maegaard, Stelios Piperidis, Christopher Cieri, Thierry Declerck, Koiti Hasida, Helene Mazo, Khalid Choukri, Sara Goggi, Joseph Mariani, Asuncion Moreno, Nicoletta Calzolari, Jan Odijk, Takenobu Tokunaga
PublisherEuropean Language Resources Association (ELRA)
Pages1597-1601
Number of pages5
ISBN (Electronic)9791095546009
StatePublished - Jan 1 2019
Event11th International Conference on Language Resources and Evaluation, LREC 2018 - Miyazaki, Japan
Duration: May 7 2018May 12 2018

Publication series

NameLREC 2018 - 11th International Conference on Language Resources and Evaluation

Other

Other11th International Conference on Language Resources and Evaluation, LREC 2018
CountryJapan
CityMiyazaki
Period5/7/185/12/18

All Science Journal Classification (ASJC) codes

  • Linguistics and Language
  • Education
  • Library and Information Sciences
  • Language and Linguistics

Fingerprint Dive into the research topics of 'Emotionlines: An emotion corpus of multi-party conversations'. Together they form a unique fingerprint.

  • Cite this

    Chen, S. Y., Hsu, C. C., Kuo, C. C., Huang, T. H. K., & Ku, L. W. (2019). Emotionlines: An emotion corpus of multi-party conversations. In H. Isahara, B. Maegaard, S. Piperidis, C. Cieri, T. Declerck, K. Hasida, H. Mazo, K. Choukri, S. Goggi, J. Mariani, A. Moreno, N. Calzolari, J. Odijk, & T. Tokunaga (Eds.), LREC 2018 - 11th International Conference on Language Resources and Evaluation (pp. 1597-1601). (LREC 2018 - 11th International Conference on Language Resources and Evaluation). European Language Resources Association (ELRA).