Databases, features and classifiers for speech emotion recognition: a review

Author:

Swain MonoramaORCID,Routray Aurobinda,Kabisatpathy P.

Publisher

Springer Science and Business Media LLC

Subject

Computer Vision and Pattern Recognition,Linguistics and Language,Human-Computer Interaction,Language and Linguistics,Software

Reference170 articles.

1. Abrilian, S., Devillers, L., & Martin, J. C. (2006). Annotation of emotions in real-life video interviews: Variability between coders. In 5th international conference on language resources and evaluation (LREC 06), Genoa, pp. 2004–2009.

2. Agrawal, S. S. (2011). Emotions in Hindi speech-analysis, perception and recognition. In International conference on speech database and assessments (Oriental COCOSDA).

3. Agrawal, S. S., Jain, A., & Arora, S. (2009). Acoustic and perceptual features of intonation patterns in Hindi speech. In International workshop on spoken language prosody (IWSLPR-09), Kolkata, pp. 25–27.

4. Alonso, J. B., Cabrera, J., Medina, M., & Travieso, C. M. (2015). New approach in quantification of emotional intensity from the speech signal: Emotional temperature. Experts Systems with Applications, 42, 9554–9564.

5. Amer, M. R., Siddiquie, B., Richey, C., & Divakaran, A. (2014). Emotion detection in speech using deep networks. In IEEE international conference on acoustics, speech and signal processing (ICASSP), pp. 3724–3728.

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