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Modeling and simulation of bacterial foraging variants: acoustic feature selection and classification

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Abstract

The field of human–computer interaction greatly benefits from the significant role of speech emotion recognition (SER), which finds applications across various domains. However, practical applications of SER still face certain challenges. One such challenge is the variation in emotional expressions among individuals, while another issue arises from the presence of indistinguishable emotions, which can impact the stability of SER systems. This study investigates the application of variants of the Bacterial Foraging Optimization Algorithm (BFOA) in the domain of SER. Experiments are conducted on multiple emotion datasets, including Emo-DB, SAVEE, and SUBESCO, to evaluate the effectiveness of the proposed variants. The findings of this study emphasize the potential of BFOA variants as powerful tools for SER.

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Availability of datasets:

[13,14,15] are the sources of the datasets used in the current work.

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Funding

No funding was provided to carry out this work.

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Author notes

  1. T. R. Vijaya Lakshmi and Ch Venkata Krishna Reddy have contributed equally to this work.

Authors and Affiliations

  1. ECE, Mahatma Gandhi Institute of Technology, Gandipet, Hyderabad, Telangana, 500075, India

    T. R. Vijaya Lakshmi

  2. EEE, Chaitanya Bharathi Institute of Technology, Gandipet, Hyderabad, Telangana, 500075, India

    Ch. Venkata Krishna Reddy

Authors
  1. T. R. Vijaya Lakshmi
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  2. Ch. Venkata Krishna Reddy
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Contributions

TRVL designed the SER framework and took the lead to conduct simulations. CVKR aided in interpreting the results and worked on initial draft and proof of the manuscript.

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Correspondence to T. R. Vijaya Lakshmi.

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Vijaya Lakshmi, T.R., Krishna Reddy, C.V. Modeling and simulation of bacterial foraging variants: acoustic feature selection and classification. SIViP 18, 607–613 (2024). https://doi.org/10.1007/s11760-023-02783-w

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  • DOI: https://doi.org/10.1007/s11760-023-02783-w

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