{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T20:17:50Z","timestamp":1778185070989,"version":"3.51.4"},"reference-count":42,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T00:00:00Z","timestamp":1750723200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62161040"],"award-info":[{"award-number":["62161040"]}]},{"name":"National Natural Science Foundation of China","award":["NJYT22056"],"award-info":[{"award-number":["NJYT22056"]}]},{"name":"National Natural Science Foundation of China","award":["2023YFSW0006"],"award-info":[{"award-number":["2023YFSW0006"]}]},{"name":"National Natural Science Foundation of China","award":["2023RCTD029"],"award-info":[{"award-number":["2023RCTD029"]}]},{"name":"Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region","award":["62161040"],"award-info":[{"award-number":["62161040"]}]},{"name":"Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region","award":["NJYT22056"],"award-info":[{"award-number":["NJYT22056"]}]},{"name":"Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region","award":["2023YFSW0006"],"award-info":[{"award-number":["2023YFSW0006"]}]},{"name":"Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region","award":["2023RCTD029"],"award-info":[{"award-number":["2023RCTD029"]}]},{"name":"Science and Technology Project of Inner Mongolia Autonomous Region","award":["62161040"],"award-info":[{"award-number":["62161040"]}]},{"name":"Science and Technology Project of Inner Mongolia Autonomous Region","award":["NJYT22056"],"award-info":[{"award-number":["NJYT22056"]}]},{"name":"Science and Technology Project of Inner Mongolia Autonomous Region","award":["2023YFSW0006"],"award-info":[{"award-number":["2023YFSW0006"]}]},{"name":"Science and Technology Project of Inner Mongolia Autonomous Region","award":["2023RCTD029"],"award-info":[{"award-number":["2023RCTD029"]}]},{"name":"Fundamental Research Funds for Inner Mongolia University of Science and Technology","award":["62161040"],"award-info":[{"award-number":["62161040"]}]},{"name":"Fundamental Research Funds for Inner Mongolia University of Science and Technology","award":["NJYT22056"],"award-info":[{"award-number":["NJYT22056"]}]},{"name":"Fundamental Research Funds for Inner Mongolia University of Science and Technology","award":["2023YFSW0006"],"award-info":[{"award-number":["2023YFSW0006"]}]},{"name":"Fundamental Research Funds for Inner Mongolia University of Science and Technology","award":["2023RCTD029"],"award-info":[{"award-number":["2023RCTD029"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Acoustic scene classification aims to recognize the scenes corresponding to sound signals in the environment, but audio differences from different cities and devices can affect the model\u2019s accuracy. In this paper, a time\u2013frequency\u2013wavelet fusion network is proposed to improve model performance by focusing on three dimensions: the time dimension of the spectrogram, the frequency dimension, and the high- and low-frequency information extracted by a wavelet transform through a time\u2013frequency\u2013wavelet module. Multidimensional information was fused through the gated temporal\u2013spatial attention unit, and the visual state space module was introduced to enhance the contextual modeling capability of audio sequences. In addition, Kolmogorov\u2013Arnold network layers were used in place of multilayer perceptrons in the classifier part. The experimental results show that the proposed method achieves a 56.16% average accuracy on the TAU Urban Acoustic Scenes 2022 mobile development dataset, which is an improvement of 6.53% compared to the official baseline system. This performance improvement demonstrates the effectiveness of the model in complex scenarios. In addition, the accuracy of the proposed method on the UrbanSound8K dataset reached 97.60%, which is significantly better than the existing methods, further verifying the generalization ability of the proposed model in the acoustic scene classification task.<\/jats:p>","DOI":"10.3390\/s25133930","type":"journal-article","created":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T08:50:57Z","timestamp":1750755057000},"page":"3930","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Research on Acoustic Scene Classification Based on Time\u2013Frequency\u2013Wavelet Fusion Network"],"prefix":"10.3390","volume":"25","author":[{"given":"Fengzheng","family":"Bi","sequence":"first","affiliation":[{"name":"School of Digital and Intelligent Industry, Inner Mongolia University of Science and Technology, Baotou 014010, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5587-3744","authenticated-orcid":false,"given":"Lidong","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Digital and Intelligent Industry, Inner Mongolia University of Science and Technology, Baotou 014010, China"},{"name":"Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, Baotou 014010, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"104062","DOI":"10.1016\/j.dsp.2023.104062","article-title":"Acoustic scene classification using deep fisher network","volume":"139","author":"Venkatesh","year":"2023","journal-title":"Digit. 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