• DocumentCode
    231581
  • Title

    Building a Chinese Natural Emotional Audio-Visual Database

  • Author

    Wei Bao ; Ya Li ; Mingliang Gu ; Minghao Yang ; Hao Li ; Linlin Chao ; Jianhua Tao

  • Author_Institution
    Inst. of Linguistic Sci., Jiangsu Normal Univ., Xuzhou, China
  • fYear
    2014
  • fDate
    19-23 Oct. 2014
  • Firstpage
    583
  • Lastpage
    587
  • Abstract
    Building a spontaneous, multi-modal, rich-annotated emotion database is a challenging work. Although there have been a growing number of emotional corpora available, most of them were recorded in `lab controlled´ environment. This paper presents a recently collected database, CASIA Natural Emotional Audio-Visual Database. This corpus contains two hours spontaneous emotional segments extracted from 219 speakers from films, TV plays and talk shows. The number of the speakers of the corpus makes this database a valuable addition to the existing emotional databases. In total, 24 non-prototypical emotional states are labeled by three first Chinese native speakers. In contrast to other available emotional databases, we provided multi-emotion labels and fake/suppressed emotion labels. To our best knowledge, this database is the first large-scale Chinese natural emotion corpus dealing with multi-modal and natural emotion.
  • Keywords
    audio databases; behavioural sciences computing; natural language processing; visual databases; CASIA natural emotional audio-visual database; Chinese native speakers; Chinese natural emotional audio-visual database; TV plays; emotional corpora; fake-suppressed emotion labels; lab controlled environment; multiemotion labels; multimodal rich-annotated emotion database; nonprototypical emotional states; spontaneous emotional segments; talk shows; Buildings; Databases; Emotion recognition; Films; Speech; TV; Audio-visual database; emotional corpus annotation; spontaneous emotion;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing (ICSP), 2014 12th International Conference on
  • Conference_Location
    Hangzhou
  • ISSN
    2164-5221
  • Print_ISBN
    978-1-4799-2188-1
  • Type

    conf

  • DOI
    10.1109/ICOSP.2014.7015071
  • Filename
    7015071