Machine rhythm: computer emulation of human rhythm perception
Machine rhythm: computer emulation of human rhythm perception
Artificial Intelligence Review - Special issue on lazy learning
A Review of Automatic Rhythm Description Systems
Computer Music Journal
Template-based estimation of time-varying tempo
EURASIP Journal on Applied Signal Processing
Accurate tempo estimation based on harmonic + noise decomposition
EURASIP Journal on Applied Signal Processing
Context-Dependent Beat Tracking of Musical Audio
IEEE Transactions on Audio, Speech, and Language Processing
Analysis of the meter of acoustic musical signals
IEEE Transactions on Audio, Speech, and Language Processing
An experimental comparison of audio tempo induction algorithms
IEEE Transactions on Audio, Speech, and Language Processing
"Copy and scale" method for doing time-localized M.I.R. estimation:: application to beat-tracking
Proceedings of 3rd international workshop on Machine learning and music
Rhythm pattern representations for tempo detection in music
Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia
Autonomous robot dancing driven by beats and emotions of music
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
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An approach for tempo estimation from musical pieces with near-constant tempo is proposed. The method consists of three main steps: measuring the degree of musical accent as a function of time, periodicity analysis, and tempo estimation. Novel accent features based on the chroma representation are proposed. The periodicity of the accent signal is measured using the generalized autocorrelation function, followed by tempo estimation using k-Nearest Neighbor regression. We propose a resampling step applied to an unknown periodicity vector before finding the nearest neighbors. This step improves the performance of the method significantly. The tempo estimate is computed as a distance-weighted median of the nearest neighbor tempi. Experimental results show that the proposed method provides significantly better tempo estimation accuracies than three reference methods.