2016IEEE Sensors JournalRequires access

Dual-Microphone Noise Reduction in Car Environments With Determinant Analysis of Input Correlation Matrix

Jungpyo Hong, Sangjun Park, Sangbae Jeong, Minsoo Hahn

Open publisher page 10 citations

Abstract

In this paper, a novel noise reduction technique is proposed to improve the speech interface performance in car environments. The proposed noise reduction method with dual microphones is primarily based on the determinant analysis of the input correlation matrix. Through the analysis, a robust feature for speech activity detection and signal-to-noise ratio (SNR) estimation is derived. Using the feature, the SNR of each time-frequency component is estimated, and an enhanced speech signal is obtained through Wiener filtering. To evaluate the proposed noise reduction technique, we constructed a database in a real car environment and comparatively analyzed the performances of noise reduction methods. The results show that meaningful SNR and perceptual speech quality improvements with less signal distortion are achieved compared with the other competing methods.

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What this paper is about

In this paper, a novel noise reduction technique is proposed to improve the speech interface performance in car environments. The proposed noise reduction method with dual microphones is primarily based on the determinant analysis of the input correlation matrix. Through the analysis, a robust feature for speech activity detection and signal-to-noise ratio (SNR) estimation is derived. Using the feature, the SNR of each time-frequency component is estimated, and an enhanced speech signal is obtained through Wiener filtering. To evaluate the proposed noise reduction technique, we constructed a database in a real car environment and comparatively analyzed the performances of noise reduction methods. The results show that meaningful SNR and perceptual speech quality improvements with less signal distortion are achieved compared with the other competing methods.

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Available abstract

In this paper, a novel noise reduction technique is proposed to improve the speech interface performance in car environments. The proposed noise reduction method with dual microphones is primarily based on the determinant analysis of the input correlation matrix. Through the analysis, a robust feature for speech activity detection and signal-to-noise ratio (SNR) estimation is derived. Using the feature, the SNR of each time-frequency component is estimated, and an enhanced speech signal is obtained through Wiener filtering. To evaluate the proposed noise reduction technique, we constructed a database in a real car environment and comparatively analyzed the performances of noise reduction methods. The results show that meaningful SNR and perceptual speech quality improvements with less signal distortion are achieved compared with the other competing methods.

Key concepts: Microphone, Noise reduction, Noise (video), Speech recognition, Computer science, Speech enhancement, Distortion (music), Signal-to-noise ratio (imaging)

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