Title :
Harmonic Change Detection for musical chords segmentation
Author :
Degani, Alessio ; Dalai, Marco ; Leonardi, Riccardo ; Migliorati, Pierangelo
Author_Institution :
Signals & Commun. Lab., Univ. of Brescia, Brescia, Italy
fDate :
June 29 2015-July 3 2015
Abstract :
In this paper, different strategies for the calculation of the Harte´s Harmonic Change Detection Function (HCDF) are discussed. HCDFs can be used for detecting chord boundaries for Automatic Chord Estimation (ACE) tasks, where the chord transitions are identified as peaks in the HCDF. We show that different audio features and different novelty metric have significant impact on the overall accuracy results of a chord segmentation algorithm. Furthermore, we show that certain combination of audio features and novelty measures provide a significant improvement with respect to the current chord segmentation algorithms.
Keywords :
acoustic signal processing; audio signal processing; music; ACE; HCDF; Harte harmonic change detection function; audio features; automatic chord estimation; chord segmentation algorithm; chord transitions; musical chords segmentation; Correlation; Estimation; Euclidean distance; Feature extraction; Frequency estimation; Harmonic analysis; Noise; Audio Chord Estimation; Harmonic; Music; Segmentation;
Conference_Titel :
Multimedia and Expo (ICME), 2015 IEEE International Conference on
Conference_Location :
Turin
DOI :
10.1109/ICME.2015.7177404