2016Indian Journal of Science and TechnologyOpen access

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

G. Manmadha Rao, Utkarsh Kumar

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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

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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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Available 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

Key concepts: Intelligibility (philosophy), Speech enhancement, Computer science, Speech recognition, Wiener filter, Kalman filter, Speech processing, Digital filter

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Speech Enhancement using Kalman Filter with Preprocessed Digital Expander in Noisy Environment — Research Paper | ScholarLens