Public https://www.openml.org/data/download/1798821/php0mZlkF 2 1 ARFF V17 31 2016-01-17T13:48:27Z BachChoralHarmony 0 2016-01-17T13:48:27Z BachChoralHarmony public active **Author**: -- Creators: Daniele P. Radicioni and Roberto Esposito -- Donor: Daniele P. Radicioni (radicion '@' di.unito.it) and Roberto Esposito (esposito '@' di.unito.it) -- Date: May","2014 **Source**: UCI **Please cite**: D. P. Radicioni and R. Esposito. Advances in Music Information Retrieval, chapter BREVE: an HMPerceptron-Based Chord Recognition System. Studies in Computational Intelligence, Zbigniew W. Ras and Alicja Wieczorkowska (Editors), Springer, 2010. Abstract: The data set is composed of 60 chorales (5665 events) by J.S. Bach (1675-1750). Each event of each chorale is labelled using 1 among 101 chord labels and described through 14 features. Source: -- Creators: Daniele P. Radicioni and Roberto Esposito -- Donor: Daniele P. Radicioni (radicion '@' di.unito.it) and Roberto Esposito (esposito '@' di.unito.it) -- Date: May, 2014 Data Set Information: Pitch classes information has been extracted from MIDI sources downloaded from (JSB Chorales)[[Web Link]]. Meter information has been computed through the Meter program which is part of the Melisma music analyser (Melisma)[[Web Link]]. Chord labels have been manually annotated by a human expert. Attribute Information: 1. Choral ID: corresponding to the file names from (Bach Central)[[Web Link]]. 2. Event number: index (starting from 1) of the event inside the chorale. 3-14. Pitch classes: YES/NO depending on whether a given pitch is present. Pitch classes/attribute correspondence is as follows: C -> 3 C#/Db -> 4 D -> 5 ... B -> 14 15. Bass: Pitch class of the bass note 16. Meter: integers from 1 to 5. Lower numbers denote less accented events, higher numbers denote more accented events. 17. Chord label: Chord resonating during the given event. Relevant Papers: 1. D. P. Radicioni and R. Esposito. Advances in Music Information Retrieval, chapter BREVE: an HMPerceptron-Based Chord Recognition System. Studies in Computational Intelligence, Zbigniew W. Ras and Alicja Wieczorkowska (Editors), Springer, 2010. 2. Esposito, R. and Radicioni, D. P., CarpeDiem: Optimizing the Viterbi Algorithm and Applications to Supervised Sequential Learning, Journal of Machine Learning Research, 10(Aug):1851-1880, 2009. Citation Request: D. P. Radicioni and R. Esposito. Advances in Music Information Retrieval, chapter BREVE: an HMPerceptron-Based Chord Recognition System. Studies in Computational Intelligence, Zbigniew W. Ras and Alicja Wieczorkowska (Editors), Springer, 2010.