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A feature selection model for speech emotion recognition using clustering-based population generation with hybrid of equilibrium optimizer and atom search optimization algorithm

  • 1222: Intelligent Multimedia Data Analytics and Computing
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Abstract

Speech plays an important role among the human communication and also a dominant source of medium for human computer interaction (HCI) to exchange information. Hence, it has always been an important research topic in the fields of Artificial Intelligence (AI) and Machine Learning (ML). However, in the traditional machine learning approach, when the dimension of the feature vector becomes quite large, it takes a huge amount of storage space and processing time for the learning algorithms. To address this problem, we have proposed a hybrid wrapper feature selection algorithm, called CEOAS, using clustering-based Equilibrium Optimizer (EO) and Atom Search Optimization (ASO) algorithm for recognizing different human emotions from speech signals. We have extracted Linear Prediction Coding (LPC) and Linear Predictive Cepstral Coefficient (LPCC) from the audio signals. Our proposed model helps to reduce the feature dimension as well as improves the classification accuracy of the learning model. The model has been evaluated on four standard benchmark datasets namely, SAVEE, EmoDB, RAVDESS, and IEMOCAP and impressive recognition accuracies of 98.01%, 98.72%, 84.62% and 74.25% respectively have been achieved which are better than many state-of-the-art algorithms.

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Acknowledgements

We would like to thank the Center for Microprocessor Applications for Training Applications and Research (CMATER) research laboratory of the Computer Science and Engineering Department, Jadavpur University, Kolkata, India for providing us the infrastructural support.

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The authors hereby declare that no funding from any research organisations or research companies has been provided to conduct this research work.

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Authors and Affiliations

  1. Department of Electrical Engineering, Jadavpur University, 188, Raja S.C. Mallick Road, Kolkata, 700032, West Bengal, India

    Soham Chattopadhyay

  2. Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, Kolkata, 700064, West Bengal, India

    Arijit Dey

  3. Department of Information Technology, Jadavpur University, Jadavpur University Second Campus, Plot No. 8, Salt Lake Bypass, LB Block, Sector III, Salt Lake City, Kolkata, 700106, West Bengal, India

    Pawan Kumar Singh

  4. Institute of IR 4.0, The National University of Malaysia, 43600, Bangi, Malaysia

    Ali Ahmadian

  5. Department of Mathematics, Near East University, Nicosia, TRNC, Mersin 10, Turkey

    Ali Ahmadian

  6. Department of Computer Science and Engineering, Jadavpur University, 188, Raja S.C. Mallick Road, Kolkata, 700032, West Bengal, India

    Ram Sarkar

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  1. Soham Chattopadhyay
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Correspondence to Pawan Kumar Singh.

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Chattopadhyay, S., Dey, A., Singh, P.K. et al. A feature selection model for speech emotion recognition using clustering-based population generation with hybrid of equilibrium optimizer and atom search optimization algorithm. Multimed Tools Appl 82, 9693–9726 (2023). https://doi.org/10.1007/s11042-021-11839-3

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