Beat-Tracking

Using voice suppression algorithms to improve beat tracking in the presence of highly predominant vocals
Jose R. Zapata, Emilia Gómez
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Selective Sampling for Beat Tracking Evaluation
Andre Holzapfel, Matthew EP Davies, Jose R. Zapata, João Lobato Oliveira, Fabien Gouyon
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Assigning a confidence threshold on automatic beat annotation in large datasets
Jose R. Zapata, Matthew EP Davies, Andre Holzapfel, João Lobato Oliveira, Fabien Gouyon
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Improving Beat Tracking in the presence of highly predominant vocals using source separation techniques: Preliminary study
Jose R. Zapata, Emilia Gómez
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SMC Beat tracking Dataset
This beat tracking dataset contains 217 excerpts around 40s each, of which 19 are easy and the remaining 198 are hard. This dataset has been designed for radically new techniques which can contend with challenging beat tracking situations like: quiet accompaniment, expressive timing, changes in time signature, slow tempo, poor sound quality etc. More details in Selective Sampling for Beat Tracking Evaluation
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SMC Beat tracking Dataset
On the automatic identification of difficult examples for beat tracking: towards building new evaluation datasets
Andre Holzapfel, Matthew EP Davies, Jose R. Zapata, João Lobato Oliveira, Fabien Gouyon
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