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Development of vanilla LSTM based stuttered speech recognition system using bald eagle search algorithm

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Abstract

Stuttering or stammering is considered as the most important parameter in the speech recognition algorithm. For the conversion of stuttered speech into readable text, first it is vital to detect the stuttered speech. In many existing models, the exactness of the recognition system is degraded because of the additional noise present in the speech signals. Therefore, proposed a bald eagle search algorithm based vanilla long-short term memory (BES-vanilla LSTM), a system for identifying the stuttered speech among the number of speech signals. Initially, the dataset collected from the TORGO database undergoes preprocessing phase for the elimination of unwanted noise signals present in the input speech signals using the spectral subtraction method. Further, the preprocessed signals are passed to the feature extraction phase. In this phase, the pitch frequencies are extracted from the input signals. Then the extracted pitch frequencies are passed to the input layer of the Vanilla LSTM for stuttered speech recognition. Using the fitness value of the BES algorithm, the LSTM recognizes the stuttered speech and is given at the output layer. The proposed system is implemented in the python tool. The comparison of the suggested system's performance is made with the other existing system by metrics such as f1-score, recall, accuracy and precision, and the overall efficiency of the designed system is studied.

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Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, K S R Institute for Engineering and Technology, Tiruchengode, Tamil Nadu, 637215, India

    S. Premalatha

  2. Department of Computer Science and Engineering, Galgotias College of Engineering and Technology, Greater Noida, Uttar Pradesh, 201310, India

    Vinit Kumar

  3. Department of Computer Science and Engineering, Vardhaman College of Engineering, Hyderabad, Telangana, 501218, India

    Naga Padmaja Jagini

  4. Department of Electronics and Communication Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana, 500090, India

    Gade Venkata Subba Reddy

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  1. S. Premalatha
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Authors S.P., V.K., N.P.J., and G.V.S.R. have contributed equally to the work.

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Correspondence to S. Premalatha.

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Premalatha, S., Kumar, V., Jagini, N.P. et al. Development of vanilla LSTM based stuttered speech recognition system using bald eagle search algorithm. SIViP 17, 4077–4086 (2023). https://doi.org/10.1007/s11760-023-02639-3

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  • DOI: https://doi.org/10.1007/s11760-023-02639-3

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