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To address this, our study develops robust, deep neural network (DNN)-based speech enhancement methods. We reproduce several DNN-based monaural speech enhancement methods and outline a strategy for constructing datasets. This strategy, validated through experimental reproductions, has effectively enhanced the denoising efficiency and robustness of the models. Then, we propose a causal speech enhancement system named Supervised Attention Multi-Scale Temporal Convolutional Network (SA-MSTCN). SA-MSTCN extracts the complex compressed spectrum (CCS) for input encoding and employs complex ratio masking (CRM) for output decoding. The supervised attention module, a lightweight addition to SA-MSTCN, guides feature extraction. Experiment results show that the supervised attention module effectively improves noise reduction performance with a minor increase in computational cost. The multi-scale temporal convolutional network refines the perceptual field and better reconstructs the speech signal. Overall, SA-MSTCN not only achieves state-of-the-art speech quality and intelligibility compared to other methods but also maintains stable denoising performance across various environments.<\/jats:p>","DOI":"10.1186\/s13636-024-00341-x","type":"journal-article","created":{"date-parts":[[2024,4,11]],"date-time":"2024-04-11T04:01:37Z","timestamp":1712808097000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Supervised Attention Multi-Scale Temporal Convolutional Network for monaural speech enhancement"],"prefix":"10.1186","volume":"2024","author":[{"given":"Zehua","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuyi","family":"Zhuang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yukun","family":"Qian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingjiang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,4,11]]},"reference":[{"issue":"8","key":"341_CR1","first-page":"1182","volume":"6","author":"R Martin","year":"1994","unstructured":"R. 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