Hybrid Threshold Speech Enhancement Scheme Using TEO And Wavelet Coefficients

• Published in: 2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT) pp. 01 - 05
• Main Authors: R, Latha, A R, Suhas, Pradeep Kumar, B P, Ibrahim, M.Mohammed, V, Sathiyapriya
• Format: Conference Proceeding
• Language: English
• Published: IEEE 05.04.2023
• Subjects: Additive White Gaussian Noise (AWGN); AWGN; Noise reduction; Signal denoising; Speech enhancement; Speech Enhancement (SE); Teager Energy Operator (TEO); Wavelet analysis; Wavelet domain; Wavelet packets; Wavelet Transform (WT)
• DOI: 10.1109/ICEEICT56924.2023.10156921

Speech Enhancement (SE) aims to improve the quality of degraded speech while maintaining its intelligibility. The Wavelet Transform (WT) has become a powerful tool of signal analysis thereby widely used in signal detection and signal denoising. In this paper, we propose an effective means of SE by a hybrid threshold scheme using WT. The proposed methodology looks into both falling the noise and preserving edges of the speech signal unlike the conventional Hybrid Threshold (HT) and Soft Threshold (ST) in the wavelet domain. The threshold value in the wavelet domain is maintained constant for all sub-bands of the signal which reduces denoising efficiency. A novel speech augmentation technique built on the wavelet onsets and time adaption of introduced by calculating wavelet coefficients of the Teager Energy. Performance analysis of speech enhancement techniques using Wavelet coefficients and Teager Energy Operator (TEO) with hybrid threshold method is done. The experiment is carried out for speech data with various values of SNR vacillating from -10 to +10 db with Additive White Gaussian Noise (AWGN).