Speech Signal Enhancement with Integrated Weighted Filtering for PSNR Reduction in Multimedia Applications
DOI:
https://doi.org/10.69996/jcai.2024011Keywords:
Speech Signal, Kalman Filter, Speech Enhancement, Classification, MultimediaAbstract
This paper investigates the effectiveness of the Weighted Kalman Integrated Band Rejection (WKBR) method for enhancing speech signals in multimedia applications. Speech enhancement is crucial for improving the quality and intelligibility of audio in environments with varying noise types and levels. The WKBR method is evaluated across ten different noise scenarios, including white noise, babble noise, street noise, airplane cabin noise, and more. Performance metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), and Short-Time Objective Intelligibility (STOI) are used to quantify the enhancement. The results show significant improvements, with PSNR increasing from an average of 12.8 dB before enhancement to 21.9 dB after enhancement, MSE reducing from an average of 0.0179 to 0.0053, and STOI scores improving from an average of 0.58 to 0.75. These findings highlight the potential of WKBR as a powerful tool for speech signal enhancement, making it a promising solution for real-world multimedia applications where clear and intelligible speech is essential.
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