TY - GEN
T1 - Predicting agreement and disagreement in the perception of tempo
AU - Peeters, Geoffroy
AU - Marchand, Ugo
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2014.
PY - 2014/1/1
Y1 - 2014/1/1
N2 - In the absence of a music score, tempo can only be defined by its perception by users. Thus recent studies have focused on the estimation of perceptual tempo defined by listening experiments. So far, algorithms have only been proposed to estimate the tempo when people agree on it. In this paper, we study the case when people disagree on the perception of tempo and propose an algorithm to predict this disagreement. For this, we hypothesize that the perception of tempo is correlated to a set of variations of various viewpoints on the audio content: energy, harmony, spectral-balance variations and short-term-similarity-rate. We suppose that when those variations are coherent, a shared perception of tempo is favoured and when they are not, people may perceive different tempi.We then propose several statistical models to predict the agreement or disagreement in the perception of tempo from these audio features. Finally, we evaluate the models using a test-set resulting from the perceptual experiment performed at Last-FM in 2011.
AB - In the absence of a music score, tempo can only be defined by its perception by users. Thus recent studies have focused on the estimation of perceptual tempo defined by listening experiments. So far, algorithms have only been proposed to estimate the tempo when people agree on it. In this paper, we study the case when people disagree on the perception of tempo and propose an algorithm to predict this disagreement. For this, we hypothesize that the perception of tempo is correlated to a set of variations of various viewpoints on the audio content: energy, harmony, spectral-balance variations and short-term-similarity-rate. We suppose that when those variations are coherent, a shared perception of tempo is favoured and when they are not, people may perceive different tempi.We then propose several statistical models to predict the agreement or disagreement in the perception of tempo from these audio features. Finally, we evaluate the models using a test-set resulting from the perceptual experiment performed at Last-FM in 2011.
KW - Perceptual tempo
KW - Tempo agreement
KW - Tempo disagreement
KW - Tempo estimation
UR - https://www.scopus.com/pages/publications/84918502557
U2 - 10.1007/978-3-319-12976-1_20
DO - 10.1007/978-3-319-12976-1_20
M3 - Conference contribution
AN - SCOPUS:84918502557
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 313
EP - 329
BT - Sound, Music, and Motion - 10th International Symposium, CMMR 2013, Revised Selected Papers
A2 - Aramaki, Mitsuko
A2 - Aramaki, Mitsuko
A2 - Derrien, Olivier
A2 - Kronland-Martinet, Richard
A2 - Ystad, Sølvi
PB - Springer Verlag
T2 - 10th International Symposium on Computer Music Multidisciplinary Research, CMMR 2013
Y2 - 15 October 2013 through 18 October 2013
ER -