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Speech Enhancement using Kalman Filter with Preprocessed Digital Expander in Noisy Environment


Affiliations
1 Department of ECE, GMR Institute of Technology, Rajam - 532127, Andhra Pradesh, India
 

Objective: The primary objective of the Speech Enhancement algorithms is to enrich the superiority of speech. The superiority of speech is articulated in two factors, clarity and other is intelligibility. Methods/Statistical Analysis: The method to improve the quality of speech in this paper is proposed based on computationally efficient AR modeled Kalman Filter with digital compressor/expander. This approach is based on reconstruction of noisy speech signal using digital expander and further enhancement with Auto Regressive modeled Kalman filter. Findings: The results of proposed method in terms of SNR and intelligibility are found to be better compared to earlier methods like spectral subtraction; wiener filter and Kalman filter methods. Application/Improvement: This study suggests that improvement in speech signal recovery in noisy environment helping researchers for developing efficient devices in the field of Speech recognition systems, Speech based authentication systems, audio processing devices and so on.

Keywords

Digital Compressor/Expander, Digital Filters, Intelligibility, SNR, Spectral Subtraction, Speech Enhancement, Wiener Filter.
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  • Speech Enhancement using Kalman Filter with Preprocessed Digital Expander in Noisy Environment

Abstract Views: 200  |  PDF Views: 0

Authors

G. Manmadha Rao
Department of ECE, GMR Institute of Technology, Rajam - 532127, Andhra Pradesh, India
U. Santosh Kumar
Department of ECE, GMR Institute of Technology, Rajam - 532127, Andhra Pradesh, India

Abstract


Objective: The primary objective of the Speech Enhancement algorithms is to enrich the superiority of speech. The superiority of speech is articulated in two factors, clarity and other is intelligibility. Methods/Statistical Analysis: The method to improve the quality of speech in this paper is proposed based on computationally efficient AR modeled Kalman Filter with digital compressor/expander. This approach is based on reconstruction of noisy speech signal using digital expander and further enhancement with Auto Regressive modeled Kalman filter. Findings: The results of proposed method in terms of SNR and intelligibility are found to be better compared to earlier methods like spectral subtraction; wiener filter and Kalman filter methods. Application/Improvement: This study suggests that improvement in speech signal recovery in noisy environment helping researchers for developing efficient devices in the field of Speech recognition systems, Speech based authentication systems, audio processing devices and so on.

Keywords


Digital Compressor/Expander, Digital Filters, Intelligibility, SNR, Spectral Subtraction, Speech Enhancement, Wiener Filter.



DOI: https://doi.org/10.17485/ijst%2F2016%2Fv9i39%2F125819