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題名 Streaming audio classification in Smart Home environments
作者 Liao, Wen Hung;Wen, Jing Yao;Kuo, J.-H.
廖文宏;溫景堯
貢獻者 資科系
關鍵詞 Audio classification; Bilateral filters; computational auditory analysis; Local binary patterns; Smart homes; Audition; Automation; Computer vision; Content based retrieval; Intelligent buildings; Audio acoustics
日期 2011
上傳時間 26-十月-2015 15:31:53 (UTC+8)
摘要 In this research, we develop and integrate methods for real-time streaming audio classification based on psychoacoustic models of hearing as well as techniques in pattern recognition. Specifically, a framework for auditory event detection and signal description by means of computer vision approach has been designed to enable real-time processing and classification of audio signals present in home environments. Local binary patterns are employed to describe the extracted sound blobs in the spectrogram. Experimental results show that the proposed approach is quite effective, achieving an overall recognition rate of 80-90% for 8 types of audio input. The performance degrades only slightly in the presence of noise and other interferences. © 2011 IEEE.
關聯 1st Asian Conference on Pattern Recognition, ACPR 2011
資料類型 conference
DOI http://dx.doi.org/10.1109/ACPR.2011.6166676
dc.contributor 資科系
dc.creator (作者) Liao, Wen Hung;Wen, Jing Yao;Kuo, J.-H.
dc.creator (作者) 廖文宏;溫景堯zh_TW
dc.date (日期) 2011
dc.date.accessioned 26-十月-2015 15:31:53 (UTC+8)-
dc.date.available 26-十月-2015 15:31:53 (UTC+8)-
dc.date.issued (上傳時間) 26-十月-2015 15:31:53 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/79042-
dc.description.abstract (摘要) In this research, we develop and integrate methods for real-time streaming audio classification based on psychoacoustic models of hearing as well as techniques in pattern recognition. Specifically, a framework for auditory event detection and signal description by means of computer vision approach has been designed to enable real-time processing and classification of audio signals present in home environments. Local binary patterns are employed to describe the extracted sound blobs in the spectrogram. Experimental results show that the proposed approach is quite effective, achieving an overall recognition rate of 80-90% for 8 types of audio input. The performance degrades only slightly in the presence of noise and other interferences. © 2011 IEEE.
dc.format.extent 176 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) 1st Asian Conference on Pattern Recognition, ACPR 2011
dc.subject (關鍵詞) Audio classification; Bilateral filters; computational auditory analysis; Local binary patterns; Smart homes; Audition; Automation; Computer vision; Content based retrieval; Intelligent buildings; Audio acoustics
dc.title (題名) Streaming audio classification in Smart Home environments
dc.type (資料類型) conferenceen
dc.identifier.doi (DOI) 10.1109/ACPR.2011.6166676
dc.doi.uri (DOI) http://dx.doi.org/10.1109/ACPR.2011.6166676