Beat Tracking by Dynamic Programming
By D. Ellis. 2007
464 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Signal Processing
View Paper: https://www.semanticscholar.org/paper/1c7117cd0af225eed589ce542d94748bfb18086f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Xavier Serra
- D. Ellis
- Colin Raffel
- Justin Salamon
- Dawen Liang
- Brian McFee
- Graham E. Poliner
- Eric Battenberg
In Signal Processing
- Xavier Serra
- D. Ellis
- Justin Salamon
- Colin Raffel
- Eduardo Fonseca
- Brian McFee
- Dmitry Bogdanov
- Dawen Liang
Citations in the corpus
- Identifying `Cover Songs' with Chroma Features and Dynamic Programming Beat Tracking (2007, background): “The description here is brief; for more details please see [6].”
- Essentia: An Audio Analysis Library for Music Information Retrieval (2013, background): “• the beat tracker based on the complex spectral difference feature [16], the multifeature beat tracker [74, 75] (which combines 5 different beat trackers taking into account the maximum mutual agreement between them), and the beat tracker based on the BeatIt algorithm [22]; • an extractor of the lo”
- librosa: Audio and Music Signal Analysis in Python (2015, methodology): “The beat module provides functions to estimate the global tempo and positions of beat events from the onset strength function, using the method of Ellis [Ellis07].”
- Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data (2020, unknown): “• Tempo : the beats of the signals by measuring the onset strength, commonly used in music information retrieval [11].”