A Tempogram-based Probabilistic Dynamic Model of Beat Tracking for Audio Music
نویسنده
چکیده
Automatic beat tracking and tempo estimation are challenging tasks, especially for audio music with timevarying tempo. This paper proposes tempogram-based probabilistic dynamic model to deal with beat tracking with time-varying tempo. In particular, the tempogram is the base to obtain correct beat positions. The probabilistic model to estimate the beat positions include tempogram strength model and relative position model. Combining both model to form the state and transition probabilities. Experimental results demonstrate satisfactory performance for music with significant tempo variations. The beat tracking algorithm could obtain compatible score values for mirex2006 tempo training dataset with 20 excerpts in length of 30 seconds. Index Terms – Tempogram, Time-varying tempo, Dynamic programming, Probabilistic model
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