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Emotion recognition in Arabic speech

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Abstract

Automatic emotion recognition from speech signals without linguistic cues has been an important emerging research area. Integrating emotions in human–computer interaction is of great importance to effectively simulate real life scenarios. Research has been focusing on recognizing emotions from acted speech while little work was done on natural real life utterances. English, French, German and Chinese corpora were used for that purpose while no natural Arabic corpus was found to date. In this paper, emotion recognition in Arabic spoken data is studied for the first time. A realistic speech corpus from Arabic TV shows is collected. The videos are labeled by their perceived emotions; namely happy, angry or surprised. Prosodic features are extracted and thirty-five classification methods are applied. Results are analyzed in this paper and conclusions and future recommendations are identified.

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Authors and Affiliations

  1. Department of Computer Science, Beirut Arab University, Beirut, Lebanon

    Samira Klaylat

  2. Electrical and Computer Engineering Department, Beirut Arab University, Beirut, Lebanon

    Ziad Osman

  3. Electrical and Computer Engineering Department, American University of Beirut, Beirut, Lebanon

    Lama Hamandi

  4. Electrical and Computer Engineering Department, Rafik Hariri University, Mechref, Lebanon

    Rached Zantout

Authors
  1. Samira Klaylat
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  2. Ziad Osman
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  3. Lama Hamandi
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  4. Rached Zantout
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Correspondence to Samira Klaylat.

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Klaylat, S., Osman, Z., Hamandi, L. et al. Emotion recognition in Arabic speech. Analog Integr Circ Sig Process 96, 337–351 (2018). https://doi.org/10.1007/s10470-018-1142-4

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  • DOI: https://doi.org/10.1007/s10470-018-1142-4

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