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Gender-Based Emotion Recognition: A Machine Learning Technique

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Intelligent Data Engineering and Analytics

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 266))

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Abstract

Speech emotion recognition is a mechanism to perform interaction between human and machine. Speech is a most attractive and effective way for expressing emotion as well as attitude. This paper focuses on identifying impact of gender on different basic emotions during exchange of speech. To analyze above different emotional features, emotion speech Hindi database simulated by Indian Institute of Technology Kharagpur, Mel-frequency cepstral coefficient feature extraction method and a classification method are processed. The analysis shows the machine recognizes the female speech more efficiently than male emotion speech recognition irrespective of the method. Simulation also carried out for text independent data. The simulation is carried out by using Indian Institute of Technology Speech emotion for Hindi database. Simulation clearly shows the recognition always happens good when it is performed by female speech than male. And also it doesn’t matter, whether it is text dependent or text independent.

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Author information

Authors and Affiliations

  1. Faculty of Management Studies, Sri Sri University, Cuttack, Odisha, India

    Biswajit Nayak & Bhubaneswari Bisoyi

  2. School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

    Prasant Kumar Pattnaik

  3. School of Management, KIIT University, Bhubaneswar, Odisha, India

    Biswajit Das

Authors
  1. Biswajit Nayak
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  2. Bhubaneswari Bisoyi
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  3. Prasant Kumar Pattnaik
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  4. Biswajit Das
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Corresponding author

Correspondence to Biswajit Nayak .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  2. Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia

    Peter Peer

  3. College of Computing, Michigan Technological University, Michigan, MI, USA

    Jinshan Tang

  4. Shri Ramswaroop Memorial College of Engineering and Management (SRMCEM), Lucknow, India

    Vikrant Bhateja

  5. Department of Electronics and Communication Engineering, National Institute of Technology (NIT) Mizoram, Aizawl, Mizoram, India

    Anumoy Ghosh

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Nayak, B., Bisoyi, B., Pattnaik, P.K., Das, B. (2022). Gender-Based Emotion Recognition: A Machine Learning Technique. In: Satapathy, S.C., Peer, P., Tang, J., Bhateja, V., Ghosh, A. (eds) Intelligent Data Engineering and Analytics. Smart Innovation, Systems and Technologies, vol 266. Springer, Singapore. https://doi.org/10.1007/978-981-16-6624-7_26

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