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Investigation of automatic mixed-lingual affective state recognition system for diverse Indian languages

Publication Type : Journal Article

Publisher : Journal of Intelligent & Fuzzy Systems

Source : Journal of Intelligent & Fuzzy Systems, (Preprint), 1-10.

Url : https://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs189868

Keywords : Affective state, cepstral, mixed-lingual, recognition, Indian languages

Campus : Bengaluru

School : Department of Computer Science and Engineering, School of Engineering

Department : Computer Science, Electronics and Communication

Year : 2021

Abstract : Automatic recognition of human affective state using speech has been the focus of the research world for more than two decades. In the present day, with multi-lingual countries like India and Europe, population are communicating in various languages. However, majority of the existing works have put forth different strategies to recognize affect from various databases, with each comprising single language recordings. There exists a great demand for affective systems to serve the context of mixed-language scenario. Hence, this work focusses on an effective methodology to recognize human affective state using speech samples from a mixed language framework. A unique cepstral and bi-spectral speech features derived from the speech samples classified using random forest (RF) are applied for the task. This work is first of its kind with the proposed approach validated and found to be effective on a self-recorded database with speech samples comprising from eleven various diverse Indian languages. Six different affective states of angry, fear, sad, neutral, surprise and happy are considered. Three affective models have been investigated in the work. The experimental results demonstrate the proposed feature combination in addition to data augmentation show enhanced affect recognition.

Cite this Research Publication : Lalitha, S., & Gupta, D. (2021). Investigation of automatic mixed-lingual affective state recognition system for diverse Indian languages. Journal of Intelligent & Fuzzy Systems, (Preprint), 1-10.

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