{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T21:02:41Z","timestamp":1757451761032},"reference-count":3,"publisher":"Hindawi Limited","license":[{"start":{"date-parts":[[2012,1,1]],"date-time":"2012-01-01T00:00:00Z","timestamp":1325376000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Computational Intelligence and Soft Computing"],"published-print":{"date-parts":[[2012]]},"abstract":"<jats:p>Environmental sound recognition is an important function of robots and intelligent computer systems. In this research, we use a multistage perceptron neural network system for environmental sound recognition. The input data is a combination of time-variance pattern of instantaneous powers and frequency-variance pattern with instantaneous spectrum at the power peak, referred to as a time-frequency intersection pattern. Spectra of many environmental sounds change more slowly than those of speech or voice, so the intersectional time-frequency pattern will preserve the major features of environmental sounds but with drastically reduced data requirements. Two experiments were conducted using an original database and an open database created by the RWCP project. The recognition rate for 20 kinds of environmental sounds was 92%. The recognition rate of the new method was about 12% higher than methods using only an instantaneous spectrum. The results are also comparable with HMM-based methods, although those methods need to treat the time variance of an input vector series with more complicated computations.<\/jats:p>","DOI":"10.1155\/2012\/650818","type":"journal-article","created":{"date-parts":[[2012,5,10]],"date-time":"2012-05-10T21:03:24Z","timestamp":1336683804000},"page":"1-6","source":"Crossref","is-referenced-by-count":8,"title":["Environmental Sound Recognition Using Time-Frequency Intersection Patterns"],"prefix":"10.1155","volume":"2012","author":[{"given":"Xuan","family":"Guo","sequence":"first","affiliation":[{"name":"Graduate Department of Computer and Information Systems, Graduate School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu 965-8580, Japan"}]},{"given":"Yoshiyuki","family":"Toyoda","sequence":"additional","affiliation":[{"name":"Graduate Department of Computer and Information Systems, Graduate School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu 965-8580, Japan"}]},{"given":"Huankang","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Shanghai Jiaotong University, 200240 Shanghai, China"}]},{"given":"Jie","family":"Huang","sequence":"additional","affiliation":[{"name":"Graduate Department of Computer and Information Systems, Graduate School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu 965-8580, Japan"}]},{"given":"Shuxue","family":"Ding","sequence":"additional","affiliation":[{"name":"Graduate Department of Computer and Information Systems, Graduate School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu 965-8580, Japan"}]},{"given":"Yong","family":"Liu","sequence":"additional","affiliation":[{"name":"Graduate Department of Computer and Information Systems, Graduate School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu 965-8580, Japan"}]}],"member":"98","reference":[{"issue":"4","key":"1","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1007\/BF02471133","volume":"1","year":"1997","journal-title":"Artificial Life and Robotics"},{"issue":"3","key":"2","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1250\/ast.20.225","volume":"20","year":"1999","journal-title":"Journal of the Acoustical Society of Japan"},{"key":"4","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/0893-6080(90)90044-L","volume":"3","year":"1990","journal-title":"Neural Networks"}],"container-title":["Applied Computational Intelligence and Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/acisc\/2012\/650818.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/acisc\/2012\/650818.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/acisc\/2012\/650818.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,20]],"date-time":"2017-06-20T18:35:13Z","timestamp":1497983713000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.hindawi.com\/journals\/acisc\/2012\/650818\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012]]},"references-count":3,"alternative-id":["650818","650818"],"URL":"https:\/\/doi.org\/10.1155\/2012\/650818","relation":{},"ISSN":["1687-9724","1687-9732"],"issn-type":[{"value":"1687-9724","type":"print"},{"value":"1687-9732","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012]]}}}