Methods for Identification of the Tuning System in Audio Musical Signals
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P. Heydarian, L. Jones, and A. Seago, "Methods for Identification of the Tuning System in Audio Musical Signals," Paper 7515, (2008 October.). doi:
P. Heydarian, L. Jones, and A. Seago, "Methods for Identification of the Tuning System in Audio Musical Signals," Paper 7515, (2008 October.). doi:
Abstract: The tuning system is an important aspect of a piece. It specifies the scale intervals and is an indicator of the emotions of a musical file. There is a direct relationship between musical mode and the tuning of a piece for modal musical traditions. So, the tuning system carries valuable information, which is worth incorporating into metadata of a file.
In this paper different algorithms for automatic identification of the tuning system are presented and compared. In the training process, spectral and chroma average, and pitch histograms, are used to construct reference patterns for each class. The same is done for the testing samples and a similarity measure like the Manhattan distance classifies a piece into different tuning classes.
@article{heydarian2008methods,
author={heydarian, peyman and jones, lewis and seago, allan},
journal={journal of the audio engineering society},
title={methods for identification of the tuning system in audio musical signals},
year={2008},
volume={},
number={},
pages={},
doi={},
month={october},}
@article{heydarian2008methods,
author={heydarian, peyman and jones, lewis and seago, allan},
journal={journal of the audio engineering society},
title={methods for identification of the tuning system in audio musical signals},
year={2008},
volume={},
number={},
pages={},
doi={},
month={october},
abstract={the tuning system is an important aspect of a piece. it specifies the scale intervals and is an indicator of the emotions of a musical file. there is a direct relationship between musical mode and the tuning of a piece for modal musical traditions. so, the tuning system carries valuable information, which is worth incorporating into metadata of a file.
in this paper different algorithms for automatic identification of the tuning system are presented and compared. in the training process, spectral and chroma average, and pitch histograms, are used to construct reference patterns for each class. the same is done for the testing samples and a similarity measure like the manhattan distance classifies a piece into different tuning classes.},}
TY - paper
TI - Methods for Identification of the Tuning System in Audio Musical Signals
SP -
EP -
AU - Heydarian, Peyman
AU - Jones, Lewis
AU - Seago, Allan
PY - 2008
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - October 2008
TY - paper
TI - Methods for Identification of the Tuning System in Audio Musical Signals
SP -
EP -
AU - Heydarian, Peyman
AU - Jones, Lewis
AU - Seago, Allan
PY - 2008
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - October 2008
AB - The tuning system is an important aspect of a piece. It specifies the scale intervals and is an indicator of the emotions of a musical file. There is a direct relationship between musical mode and the tuning of a piece for modal musical traditions. So, the tuning system carries valuable information, which is worth incorporating into metadata of a file.
In this paper different algorithms for automatic identification of the tuning system are presented and compared. In the training process, spectral and chroma average, and pitch histograms, are used to construct reference patterns for each class. The same is done for the testing samples and a similarity measure like the Manhattan distance classifies a piece into different tuning classes.
The tuning system is an important aspect of a piece. It specifies the scale intervals and is an indicator of the emotions of a musical file. There is a direct relationship between musical mode and the tuning of a piece for modal musical traditions. So, the tuning system carries valuable information, which is worth incorporating into metadata of a file.
In this paper different algorithms for automatic identification of the tuning system are presented and compared. In the training process, spectral and chroma average, and pitch histograms, are used to construct reference patterns for each class. The same is done for the testing samples and a similarity measure like the Manhattan distance classifies a piece into different tuning classes.
Authors:
Heydarian, Peyman; Jones, Lewis; Seago, Allan
Affiliation:
London Metropolitan University
AES Convention:
125 (October 2008)
Paper Number:
7515
Publication Date:
October 1, 2008Import into BibTeX
Subject:
Analysis and Synthesis of Sound
Permalink:
http://www.aes.org/e-lib/browse.cfm?elib=14667