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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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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DOI: https://doi.org/10.1007/978-981-16-6624-7_26
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