A review of classification methods and databases used for speech emotion recognition

  • Authors

    • Shrikala Madhav Deshmukh Amity University Mumbai
    • Sita Devulapalli Amity University Mumbai
    https://doi.org/10.14419/ijet.v7i4.28292

    Received date: March 11, 2019

    Accepted date: March 14, 2019

    Published date: April 3, 2019

  • Artificial Neural Networks (ANN), Convolutional Neural Networks (CNNs), Classification Methods, Database, Gaussian Mixture Model (GMM), Hidden Markov Model (HMM), Neural Network Classifier, Recurrent Neural Network (RNN), Speech Emotion Recognition (SER),

  • Abstract

    In today’s world speech is the ideal way to interact with people. Speech emotion recognition (SER) has an increasingly significant role in the interactions among human beings and computers. For improving human machine interaction, it is very ideal to recognize emotions automatically because attention is aimed at study of the emotions. This paper is a review of classification methods and databases used for speech emotion recognition. Here two important fields in speech emotion recognition are addressed. First is the choice of appropriate classification method and second is the creation of emotional speech database or choosing appropriate database. The main purpose behind this review paper is to analyze the efficiency of several techniques widely used among the field of speech emotion recognition.

  • References

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  • How to Cite

    Madhav Deshmukh, S., & Devulapalli, S. (2019). A review of classification methods and databases used for speech emotion recognition. International Journal of Engineering and Technology, 7(4), 5517-5520. https://doi.org/10.14419/ijet.v7i4.28292