{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T22:21:31Z","timestamp":1789424491839,"version":"build-2803163510"},"reference-count":46,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,4,15]],"date-time":"2022-04-15T00:00:00Z","timestamp":1649980800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61973059"],"award-info":[{"award-number":["61973059"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Automatic speech recognition (ASR) is an essential technique of human\u2013computer interactions; gain control is a commonly used operation in ASR. However, inappropriate gain control strategies can lead to an increase in the word error rate (WER) of ASR. As there is a current lack of sufficient theoretical analyses and proof of the relationship between gain control and WER, various unconstrained gain control strategies have been adopted on realistic ASR systems, and the optimal gain control with respect to the lowest WER, is rarely achieved. A gain control strategy named maximized original signal transmission (MOST) is proposed in this study to minimize the adverse impact of gain control on ASR systems. First, by modeling the gain control strategy, the quantitative relationship between the gain control strategy and the ASR performance was established using the noise figure index. Second, through an analysis of the quantitative relationship, an optimal MOST gain control strategy with minimal performance degradation was theoretically deduced. Finally, comprehensive comparative experiments on a Mandarin dataset show that the proposed MOST gain control strategy can significantly reduce the WER of the experimental ASR system, with a 10% mean absolute WER reduction at \u22129 dB gain.<\/jats:p>","DOI":"10.3390\/s22083027","type":"journal-article","created":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T02:39:31Z","timestamp":1650335971000},"page":"3027","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Automatic Speech Recognition Performance Improvement for Mandarin Based on Optimizing Gain Control Strategy"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9535-5933","authenticated-orcid":false,"given":"Desheng","family":"Wang","sequence":"first","affiliation":[{"name":"Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, School of Computer Science and Engineering, Northeastern University, Shenyang 110169, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6615-5484","authenticated-orcid":false,"given":"Yangjie","family":"Wei","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, School of Computer Science and Engineering, Northeastern University, Shenyang 110169, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ke","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, School of Computer Science and Engineering, Northeastern University, Shenyang 110169, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1341-5638","authenticated-orcid":false,"given":"Dong","family":"Ji","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, School of Computer Science and Engineering, Northeastern University, Shenyang 110169, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, School of Computer Science and Engineering, Northeastern University, Shenyang 110169, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wang, Z. 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