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In this talk, I will give a presentation of some recent progress we have made at the Multimedia Processing and Communications Lab of National Taiwan University. Specifically, I will describe the multimedia signal processing techniques we have developed for applications to digital video camera and emotion-based multimedia presentation. The demos to be shown in this talk include 1) programmable aperture...
Content-based retrieval has emerged as a promising approach to information access. In this paper, we propose an approach to music emotion ranking. Specifically, we rank music in terms of arousal and valence and represent each song as a point in the 2D emotion space. Novel ranking-based methods for annotation, learning, and evaluation of music emotion recognition are developed and tested on a moderately...
As one of the most important mid-level features of music, chord contains rich information of harmonic structure that is useful for music information retrieval. In this paper, we present a chord recognition system based on the N-gram model. The system is time-efficient, and its accuracy is comparable to existing systems. We further propose a new method to construct chord features for music emotion...
Content-based retrieval has emerged in the face of content explosion as a promising approach to information access. In this paper, we focus on the challenging issue of recognizing the emotion content of music signals, or music emotion recognition (MER). Specifically, we formulate MER as a regression problem to predict the arousal and valence values (AV values) of each music sample directly. Associated...
Typical music emotion classification (MEC) approaches categorize emotions and apply pattern recognition methods to train a classifier. However, categorized emotions are too ambiguous for efficient music retrieval. In this paper, we model emotions as continuous variables composed of arousal and valence values (AV values), and formulate MEC as a regression problem. The multiple linear regression, support...
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