کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10361545 | 870361 | 2005 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Nonnegative features of spectro-temporal sounds for classification
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
A parts-based representation is a way of understanding object recognition in the brain. The nonnegative matrix factorization (NMF) is an algorithm which is able to learn a parts-based representation by allowing only non-subtractive combinations [Lee, D.D., Seung, H.S., 1999. Learning the parts of objects by non-negative matrix factorization. Nature 401, 788-791]. In this paper we incorporate a parts-based representation of spectro-temporal sounds into the acoustic feature extraction, which leads to nonnegative features. We present a method of inferring encoding variables in the framework of NMF and show that the method produces robust acoustic features in the presence of noise in the task of general sound classification. Experimental results confirm that the proposed feature extraction method improves the classification performance, especially in the presence of noise, compared to independent component analysis (ICA) which produces holistic features.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 26, Issue 9, 1 July 2005, Pages 1327-1336
Journal: Pattern Recognition Letters - Volume 26, Issue 9, 1 July 2005, Pages 1327-1336
نویسندگان
Yong-Choon Cho, Seungjin Choi,