Single-channel speech enhancement method using reconstructive NMF with spectrotemporal speech presence probabilities

详细信息    查看全文

• 作者：Seongjae Lee^a ; David K. Han^b ; Hanseok Ko^a ; ^{hsko@korea.ac.kr}
• 关键词：Acoustic source separation ; Noise reduction ; Speech enhancement
• 刊名：Applied Acoustics
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：117
• 期：part_PB
• 页码：257-262
• 全文大小：3345 K
• 卷排序：117

文摘

In this paper, a novel single microphone channel-based speech enhancement technique is presented. While most of the conventional nonnegative matrix factorization-based approaches focus on generating a basis matrix of speech and noise for enhancement, the proposed algorithm performs an additional process to reconstruct speech from noisy speech when these two elements are highly overlapped in selected spectral bands. This process involves a log-spectral amplitude based estimator, which provides the spectrotemporal speech presence probability to obtain a more accurate reconstruction. Moreover, the proposed algorithm applies an unsupervised learning method to the input noise, so it is adaptable to any type of environmental noise without a pre-trained dictionary. The experimental results demonstrate that the proposed algorithm obtains improved speech enhancement performance compared with conventional single channel-based approaches.