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2篇 您的检索式:作者名="BAI Haichuan"
    题名 作者 年代 出处 被引量
1DNN-Based Speech Enhancement Using Soft Audible Noise Masking for Wind Noise Reduction显示文摘This paper presents a deep neural network(DNN)-based speech enhancement algorithm based on the soft audible noise masking for the single-channel wind noise reduction. To reduce the low-frequency residual noise, the psychoacoustic model is adopted to calculate the masking threshold from the estimated clean speech spectrum. The gain for noise suppression is obtained based on soft audible noise masking by comparing the estimated wind noise spectrum with the masking threshold. To deal with the abruptly time-varying noisy signals, two separate DNN models are utilized to estimate the spectra of clean speech and wind noise components. Experimental results on the subjective and objective quality tests show that the proposed algorithm achieves the better performance compared with the conventional DNN-based wind noise reduction method.Haichuan Bai Fengpei Ge Yonghong Yan 2018China Communications2018,15,9:1
2Deep Scattering Spectra with Deep Neural Networks for Acoustic Scene Classification Tasks显示文摘As one of the most commonly used features,Mel-frequency cepstral coefficients(MFCCs)are less discriminative at high frequency.A novel technique,known as Deep scattering spectrum(DSS),addresses this issue and looks to preserve greater details.DSS feature has shown promise both on classification and recognition tasks.In this paper,we extend the use of DSS feature for acoustic scene classification task.Results on Detection and classification of acoustic scenes and events(DCASE)2016 and 2017 show that DSS provided 4.8%and 17.4%relative improvements in accuracy over MFCC features,within a state-of-the-art time delay neural network framework.ZHANG Pengyuan CHEN Hangting BAI Haichuan YUAN Qingsheng 2019Chinese Journal of Electronics2019,28,6:1
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