SNR-Progressive Model With Harmonic Compensation for Low-SNR Speech Enhancement

• Published in: IEEE signal processing letters Vol. 32; pp. 476 - 480
• Main Authors: Hou, Zhongshu, Lei, Tong, Hu, Qinwen, Cao, Zhanzhong, Lu, Jing
• Format: Journal Article
• Language: English
• Published: New York IEEE 2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Compensation; Estimation; Filtering; Harmonic analysis; Low-SNR speech enhancement; neural network; Noise measurement; Pitch estimation; Power harmonic filters; Signal quality; Signal to noise ratio; SNR-progressive learning; Spectrogram; Speech enhancement; Speech processing; Training

Despite significant progress made in the last decade, deep neural network (DNN) based speech enhancement (SE) still faces the challenge of notable degradation in the quality of recovered speech under low signal-to-noise ratio (SNR) conditions. In this letter, we propose an SNR-progressive speech enh...