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We study how closely the optimal Bayes error rate can be approximately reached using a classification algorithm that computes a classifier by minimizing a convex upper bound of the classification error function. The measurement of closeness is characterized by the loss function used in the estimation. We show that such a classification scheme can be(More)
While current approaches for audiovisual data segmentation and classification are mostly focused on visual cues, audio signals may actually play a more important role in content parsing for many applications. An approach to automatic segmentation and classification of audiovisual data based on audio content analysis is proposed. The audio signal from movies(More)
A hierarchical system for audio classi cation and retrieval based on audio content analysis is presented in this paper. The system consists of three stages. The rst stage is called the coarse-level audio classi cation and segmentation, where audio recordings are classi ed and segmented into speech, music, several types of environmental sounds, and silence,(More)
An online audio classiication and segmentation system is presented in this research, where audio recordings are classiied and segmented into speech, music, several types of environmental sounds and silence based on audio content analysis. This is the rst step of our continuing work towards a general content-based audio classiication and retrieval system.(More)
ABSTRACT The SNoW (Sparse Network of Winnows) ar hite ture has re ently been su essful applied to a number of natural language pro essing (NLP) problems. In this paper, we propose large margin versions of the Winnow algorithms, whi h we argue an potentially enhan e the performan e of basi Winnows (and hen e the SNoW ar hite ture). We demonstrate that the(More)
A real-time audio segmentation and indexing scheme is presented in this paper. Audio recordings are segmented and classified into basic audio types such as silence, speech, music, song, environmental sound, speech with the music background, environmental sound with the music background, etc. Simple audio features such as the energy function, the average(More)
A hierarchical system for audio classiication and retrieval based on audio content analysis is presented in this paper. The system consists of three stages. The audio recordings are rst classiied and segmented into speech, music, several types of environmental sounds, and silence, based on morphological and statistical analysis of temporal curves of the(More)