2016
Rizo, D.; Illescas, P. R.; Iñesta, J. M.
Interactive melodic analysis Book Chapter
In: Meredith, D. (Ed.): Computational Music Analysis, Chapter 7, pp. 191-219, Springer, 2016, ISBN: 978-3-319-25931-4.
Abstract | Links | BibTeX | Tags: GRE-12-34, Prometeo 2012, TIMuL
@inbook{k322,
title = {Interactive melodic analysis},
author = {D. Rizo and P. R. Illescas and J. M. Iñesta},
editor = {D. Meredith},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/322/RizoEtAl.pdf},
isbn = {978-3-319-25931-4},
year = {2016},
date = {2016-01-01},
urldate = {2016-01-01},
booktitle = {Computational Music Analysis},
pages = {191-219},
publisher = {Springer},
chapter = {7},
abstract = {Melodic analysis sets the importance and role of each note in a particular harmonic context. Thus, a note is classified as a harmonic tone, when it belongs to the underlying chord, and as a non harmonic tone otherwise, with a number of categories in this latter case. Automatic systems for solving this task are still far from being available, so it must be assumed that in a practical scenario the human expert must correct the system’s output. Interactive systems allow for turning the user into a source of high-quality and high-confidence training data, so on-line ma- chine learning and interactive pattern recognition provide tools that have proven to be very convenient in this context.},
keywords = {GRE-12-34, Prometeo 2012, TIMuL},
pubstate = {published},
tppubtype = {inbook}
}
Melodic analysis sets the importance and role of each note in a particular harmonic context. Thus, a note is classified as a harmonic tone, when it belongs to the underlying chord, and as a non harmonic tone otherwise, with a number of categories in this latter case. Automatic systems for solving this task are still far from being available, so it must be assumed that in a practical scenario the human expert must correct the system’s output. Interactive systems allow for turning the user into a source of high-quality and high-confidence training data, so on-line ma- chine learning and interactive pattern recognition provide tools that have proven to be very convenient in this context.2015
Rizo, D.; Iñesta, J. M.
A grammar for Plaine and Easie Code Proceedings Article
In: Roland, Perry; Kepper, Johannes (Ed.): Proceedings of the Music Encoding Initiative Conferences 2013 and 2014, pp. 54–64, 2015.
BibTeX | Tags: GRE-12-34, Prometeo 2012, TIMuL
@inproceedings{k321,
title = {A grammar for Plaine and Easie Code},
author = {D. Rizo and J. M. Iñesta},
editor = {Perry Roland and Johannes Kepper},
year = {2015},
date = {2015-01-01},
urldate = {2015-01-01},
booktitle = {Proceedings of the Music Encoding Initiative Conferences 2013 and 2014},
pages = {54--64},
keywords = {GRE-12-34, Prometeo 2012, TIMuL},
pubstate = {published},
tppubtype = {inproceedings}
}
2016
Rizo, D.; Illescas, P. R.; Iñesta, J. M.
Interactive melodic analysis Book Chapter
In: Meredith, D. (Ed.): Computational Music Analysis, Chapter 7, pp. 191-219, Springer, 2016, ISBN: 978-3-319-25931-4.
Abstract | Links | BibTeX | Tags: GRE-12-34, Prometeo 2012, TIMuL
@inbook{k322,
title = {Interactive melodic analysis},
author = {D. Rizo and P. R. Illescas and J. M. Iñesta},
editor = {D. Meredith},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/322/RizoEtAl.pdf},
isbn = {978-3-319-25931-4},
year = {2016},
date = {2016-01-01},
urldate = {2016-01-01},
booktitle = {Computational Music Analysis},
pages = {191-219},
publisher = {Springer},
chapter = {7},
abstract = {Melodic analysis sets the importance and role of each note in a particular harmonic context. Thus, a note is classified as a harmonic tone, when it belongs to the underlying chord, and as a non harmonic tone otherwise, with a number of categories in this latter case. Automatic systems for solving this task are still far from being available, so it must be assumed that in a practical scenario the human expert must correct the system’s output. Interactive systems allow for turning the user into a source of high-quality and high-confidence training data, so on-line ma- chine learning and interactive pattern recognition provide tools that have proven to be very convenient in this context.},
keywords = {GRE-12-34, Prometeo 2012, TIMuL},
pubstate = {published},
tppubtype = {inbook}
}
Melodic analysis sets the importance and role of each note in a particular harmonic context. Thus, a note is classified as a harmonic tone, when it belongs to the underlying chord, and as a non harmonic tone otherwise, with a number of categories in this latter case. Automatic systems for solving this task are still far from being available, so it must be assumed that in a practical scenario the human expert must correct the system’s output. Interactive systems allow for turning the user into a source of high-quality and high-confidence training data, so on-line ma- chine learning and interactive pattern recognition provide tools that have proven to be very convenient in this context.
2015
Rizo, D.; Iñesta, J. M.
A grammar for Plaine and Easie Code Proceedings Article
In: Roland, Perry; Kepper, Johannes (Ed.): Proceedings of the Music Encoding Initiative Conferences 2013 and 2014, pp. 54–64, 2015.
BibTeX | Tags: GRE-12-34, Prometeo 2012, TIMuL
@inproceedings{k321,
title = {A grammar for Plaine and Easie Code},
author = {D. Rizo and J. M. Iñesta},
editor = {Perry Roland and Johannes Kepper},
year = {2015},
date = {2015-01-01},
urldate = {2015-01-01},
booktitle = {Proceedings of the Music Encoding Initiative Conferences 2013 and 2014},
pages = {54--64},
keywords = {GRE-12-34, Prometeo 2012, TIMuL},
pubstate = {published},
tppubtype = {inproceedings}
}