This paper analyzes music charts of an online music distributor. In music charts, the digital music provider displays a daily ranking of 1st ~ 100th and a weekly ranking of 1st ~ 1,000th songs on its website. And the ranking of each song is assigned based on streaming volumes and download volumes. This paper studies how the online music distributor should set its ranking policy to maximize the ...

A new integration method is presented to recognize the emotional expressions. We attempted to use both voices and facial expressions. For voices, we use such prosodic parameters as pitch signals, energy, and their derivatives, which are trained by Hidden Markov Model (HMM) for recognition. For facial expressions, we use feature parameters from thermal images in addition to visible images, which...

A hidden Markov model approach to piano music transcription is presented. The main difficulty in applying traditional HMM techniques is the large number of chord hypotheses that must be considered. We address this problem by using a trained likelihood model to generate reasonable hypotheses for each frame and construct the search graph out of these hypotheses. Results are presented using a reco...

We consider two approaches to robust estimation for the Box-Cox power transfonnation "model. one approach maximizes weighted, modified likelihoods. A second approach bounds the self-standardized gross-error sensitivity, a measure of the potential influence of outliers pIoneered by KrasKer and Welsch (JASA, 1982). Among our primary concerns is the performance of these estimators on actual data. ...

This paper describes a methodology for the statistical modeling of music works. Starting from either the representation of the symbolic score or the audio recording of a performance, a hidden Markov model is built to represent the corresponding music work. The model can be used to identify unknown recordings and to align them with the corresponding score. Experimental evaluation using a collect...

Clarke, E. F. (1988). Generative principles in music performance. In J. Sloboda (Ed.), Generative processes in music (pp. 1–27). Oxford, U.K.: Clarendon Press. Graybill, R. (1990). Towards a pedagogy of gestural rhythm. Journal of Music Theory Pedagogy, 4, 1–50. Green, M. D. (1994). Mathis Lussy’s Traité de l’expression musicale as a window into performance practice. Music Theory Spectrum, 16, ...

Generative models of music are in need of performance and gesture additions, i.e. inclusions of subtle temporal and dynamic alterations, and gestures so as to render the music musical. While much of the research regarding music generation is based on music theory, the work presented here is based on the temporal perception, which is divided into three parts, the immediate (subchunk), the short-...

One reason for the universal appeal of music lies in the emotional rewards that music offers to its listeners. But what makes these rewards so special? The authors addressed this question by progressively characterizing music-induced emotions in 4 interrelated studies. Studies 1 and 2 (n=354) were conducted to compile a list of music-relevant emotion terms and to study the frequency of both fel...

Music semantic annotation aims to automatically annotate a music signal with a set of semantic labels (words or tags). Existing methods on music semantic annotation usually take it as a multi-label binary classification problem, and model each semantic label individually while ignoring their relationships. However, there are usually strong correlations between some labels. Intuitively, investig...

In this paper we present a fast implementation of the subspacebased MUltiple SIgnal Classification (MUSIC) estimation criterion for harmonic signals with a known and an unknown model order, respectively. The proposed implementation improves the MUSIC criterion in two ways: First, we introduce a novel and fast implementation for evaluating the cost function of the MUSIC estimator involving only ...