2010
Pérez-Sancho, C.; Rizo, D.; Iñesta, J. M.; León, P. J. Ponce; Kersten, S.; Ramírez, R.
Genre classification of music by tonal harmony Journal Article
In: Intelligent Data Analysis, vol. 14, no. 5, pp. 533-545, 2010, ISSN: 1088-467X.
Abstract | BibTeX | Tags: Acc. Int. E-A, DRIMS, PROSEMUS
@article{k232,
title = {Genre classification of music by tonal harmony},
author = {C. Pérez-Sancho and D. Rizo and J. M. Iñesta and P. J. Ponce León and S. Kersten and R. Ramírez},
issn = {1088-467X},
year = {2010},
date = {2010-09-01},
urldate = {2010-09-01},
journal = {Intelligent Data Analysis},
volume = {14},
number = {5},
pages = {533-545},
abstract = {In this paper we present a genre classification framework for audio music based on a symbolic classification system. Audio signals are transformed into a symbolic representation of harmony using a chord transcription algorithm, based on the computation of harmonic pitch class profiles. Then, language models built from a ground truth of chord progressions for each genre are used to perform classification. We show that chord progressions are a suitable feature to represent musical genre, as they capture the harmonic rules relevant in each musical period or style. Finally, results using both pure symbolic information and chords transcribed from audio-from-MIDI are compared, in order to evaluate the effects of the transcription process in this task.},
keywords = {Acc. Int. E-A, DRIMS, PROSEMUS},
pubstate = {published},
tppubtype = {article}
}
In this paper we present a genre classification framework for audio music based on a symbolic classification system. Audio signals are transformed into a symbolic representation of harmony using a chord transcription algorithm, based on the computation of harmonic pitch class profiles. Then, language models built from a ground truth of chord progressions for each genre are used to perform classification. We show that chord progressions are a suitable feature to represent musical genre, as they capture the harmonic rules relevant in each musical period or style. Finally, results using both pure symbolic information and chords transcribed from audio-from-MIDI are compared, in order to evaluate the effects of the transcription process in this task.2009
Pérez-Sancho, C.
Stochastic Language Models for Music Information Retrieval PhD Thesis
2009.
Abstract | Links | BibTeX | Tags: Acc. Int. E-A, PROSEMUS
@phdthesis{k240,
title = {Stochastic Language Models for Music Information Retrieval},
author = {C. Pérez-Sancho},
editor = {Jorge Calera Rubio José M. Iñesta},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/240/phdthesis_cperez.pdf},
year = {2009},
date = {2009-07-01},
address = {Alicante, Spain},
organization = {Universidad de Alicante},
abstract = {Music Information Retrieval (MIR) is an interdisciplinary research area that aims at providing solutions to most problems related to the access to multimedia databases, in particular those with musical content, either in symbolic (MIDI) or audio format. An especially relevant problem is the automatic organization and indexation of data, since carrying out these tasks by hand would require an overwhelming effort for most people and institutions.
One of the most relevant features that can be obtained from a song in order to perform its automatic organization is the musical style, since it is one of the most popular fields used by people when accessing musical databases and catalogs. In this thesis it has been studied to what extent the musical style of a piece can be determined using just the information contained in its score, by applying pattern recognition techniques on melodic and harmonic sequences obtained from musical scores.},
keywords = {Acc. Int. E-A, PROSEMUS},
pubstate = {published},
tppubtype = {phdthesis}
}
Music Information Retrieval (MIR) is an interdisciplinary research area that aims at providing solutions to most problems related to the access to multimedia databases, in particular those with musical content, either in symbolic (MIDI) or audio format. An especially relevant problem is the automatic organization and indexation of data, since carrying out these tasks by hand would require an overwhelming effort for most people and institutions.
One of the most relevant features that can be obtained from a song in order to perform its automatic organization is the musical style, since it is one of the most popular fields used by people when accessing musical databases and catalogs. In this thesis it has been studied to what extent the musical style of a piece can be determined using just the information contained in its score, by applying pattern recognition techniques on melodic and harmonic sequences obtained from musical scores. Pérez-Sancho, C.; Rizo, D.; Iñesta, J. M.
Genre classification using chords and stochastic language models Journal Article
In: Connection Science, vol. 21, no. 2, pp. 145-159, 2009, ISSN: 0954-0091.
Abstract | BibTeX | Tags: Acc. Int. E-A, MIPRCV, PROSEMUS
@article{k227,
title = {Genre classification using chords and stochastic language models},
author = {C. Pérez-Sancho and D. Rizo and J. M. Iñesta},
issn = {0954-0091},
year = {2009},
date = {2009-05-01},
urldate = {2009-05-01},
journal = {Connection Science},
volume = {21},
number = {2},
pages = {145-159},
abstract = {Music genre meta-data is of paramount importance for the organisation of music repositories. People use genre in a natural way when entering a music store or looking into music collections. Automatic genre classification has become a popular topic in music information retrieval research both, with digital audio and symbolic data. This work focuses on the symbolic approach, bringing to music cognition some technologies, like the stochastic language models, already successfully applied to text categorisation. The representation chosen here is to model chord progressions as n-grams and strings and then apply perplexity and naiumlve Bayes classifiers, respectively, in order to assess how often those structures are found in the target genres. Some genres and sub-genres among popular, jazz, and academic music have been considered, trying to investigate how far can we reach using harmonic information with these models. The results at different levels of the genre hierarchy for the techniques employed are presented and discussed.},
keywords = {Acc. Int. E-A, MIPRCV, PROSEMUS},
pubstate = {published},
tppubtype = {article}
}
Music genre meta-data is of paramount importance for the organisation of music repositories. People use genre in a natural way when entering a music store or looking into music collections. Automatic genre classification has become a popular topic in music information retrieval research both, with digital audio and symbolic data. This work focuses on the symbolic approach, bringing to music cognition some technologies, like the stochastic language models, already successfully applied to text categorisation. The representation chosen here is to model chord progressions as n-grams and strings and then apply perplexity and naiumlve Bayes classifiers, respectively, in order to assess how often those structures are found in the target genres. Some genres and sub-genres among popular, jazz, and academic music have been considered, trying to investigate how far can we reach using harmonic information with these models. The results at different levels of the genre hierarchy for the techniques employed are presented and discussed. Pertusa, A.; Iñesta, J. M.
Note Onset Detection Using One Semitone Filter-Bank For MIREX 2009 Proceedings Article
In: MIREX 2009 - Music Information Retrieval Evaluation eXchange, MIREX Audio Onset Detection, Kobe, Japan., 2009.
Links | BibTeX | Tags: Acc. Int. E-A, PROSEMUS
@inproceedings{k238,
title = {Note Onset Detection Using One Semitone Filter-Bank For MIREX 2009},
author = {A. Pertusa and J. M. Iñesta},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/238/PI.pdf},
year = {2009},
date = {2009-01-01},
urldate = {2009-01-01},
booktitle = {MIREX 2009 - Music Information Retrieval Evaluation eXchange, MIREX Audio Onset Detection},
address = {Kobe, Japan.},
keywords = {Acc. Int. E-A, PROSEMUS},
pubstate = {published},
tppubtype = {inproceedings}
}
2008
Iñesta, J. M.; Pertusa, A.
Multiple Fundamental Frequency estimation using Gaussian smoothness Proceedings Article
In: Proc. of the IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP 2008, pp. 105-108, Las Vegas, USA, 2008, ISBN: 1-4244-1484-9.
Links | BibTeX | Tags: Acc. Int. E-A, MIPRCV, PROSEMUS
@inproceedings{k202,
title = {Multiple Fundamental Frequency estimation using Gaussian smoothness},
author = {J. M. Iñesta and A. Pertusa},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/202/2974_sent.pdf},
isbn = {1-4244-1484-9},
year = {2008},
date = {2008-01-01},
urldate = {2008-01-01},
booktitle = {Proc. of the IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP 2008},
pages = {105-108},
address = {Las Vegas, USA},
keywords = {Acc. Int. E-A, MIPRCV, PROSEMUS},
pubstate = {published},
tppubtype = {inproceedings}
}
Pérez-Sancho, C.; Rizo, D.; Kersten, S.; Ramírez, R.
Genre classification of music by tonal harmony Proceedings Article
In: Proc. Int. Workshop on Machine Learning and Music, MML 2008, pp. 21-22, Helsinki, Finland, 2008.
BibTeX | Tags: Acc. Int. E-A, MIPRCV, PROSEMUS
@inproceedings{k209,
title = {Genre classification of music by tonal harmony},
author = {C. Pérez-Sancho and D. Rizo and S. Kersten and R. Ramírez},
year = {2008},
date = {2008-01-01},
booktitle = {Proc. Int. Workshop on Machine Learning and Music, MML 2008},
pages = {21-22},
address = {Helsinki, Finland},
keywords = {Acc. Int. E-A, MIPRCV, PROSEMUS},
pubstate = {published},
tppubtype = {inproceedings}
}
Iñesta, J. M.; Heredia-Agoiz, J. L.; León, P. J. Ponce
A ground-truth experiment on melody genre recognition in absence of timbre Proceedings Article
In: Proc. of the 10th International Conference on Music Perception and Cognition (ICMPC10), pp. 758-761, Sapporo, Japan, 2008, ISBN: 978-4-9904208-0-2.
BibTeX | Tags: Acc. Int. E-A, PROSEMUS
@inproceedings{k215,
title = {A ground-truth experiment on melody genre recognition in absence of timbre},
author = {J. M. Iñesta and J. L. Heredia-Agoiz and P. J. Ponce León},
isbn = {978-4-9904208-0-2},
year = {2008},
date = {2008-01-01},
urldate = {2008-01-01},
booktitle = {Proc. of the 10th International Conference on Music Perception and Cognition (ICMPC10)},
pages = {758-761},
address = {Sapporo, Japan},
keywords = {Acc. Int. E-A, PROSEMUS},
pubstate = {published},
tppubtype = {inproceedings}
}
Pérez-Sancho, C.; Rizo, D.; Iñesta, J. M.
Stochastic text models for music categorization Journal Article
In: Lecture Notes in Computer Science, vol. 5342, pp. 55-64, 2008.
Links | BibTeX | Tags: Acc. Int. E-A, MIPRCV, PROSEMUS
@article{k217,
title = {Stochastic text models for music categorization},
author = {C. Pérez-Sancho and D. Rizo and J. M. Iñesta},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/217/music-cat.pdf},
year = {2008},
date = {2008-01-01},
journal = {Lecture Notes in Computer Science},
volume = {5342},
pages = {55-64},
keywords = {Acc. Int. E-A, MIPRCV, PROSEMUS},
pubstate = {published},
tppubtype = {article}
}
Lidy, T.; Rauber, A.; Pertusa, A.; de León, P. J. Ponce; Iñesta, J. M.
MIREX 2008: Audio Music Classification Using A Combination Of Spectral, Timbral, Rhythmic, Temporal And Symbolic Features. Proceedings Article
In: MIREX 2008 - Music Information Retrieval Evaluation eXchange, MIREX Genre Classification Contest., Philadelphia, Pennsylvania, USA, 2008.
Abstract | Links | BibTeX | Tags: Acc. Int. E-A, PROSEMUS
@inproceedings{k236,
title = {MIREX 2008: Audio Music Classification Using A Combination Of Spectral, Timbral, Rhythmic, Temporal And Symbolic Features.},
author = {T. Lidy and A. Rauber and A. Pertusa and P. J. Ponce de León and J. M. Iñesta},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/236/abstract_mirex08_class.pdf},
year = {2008},
date = {2008-01-01},
urldate = {2008-01-01},
booktitle = {MIREX 2008 - Music Information Retrieval Evaluation eXchange, MIREX Genre Classification Contest.},
address = {Philadelphia, Pennsylvania, USA},
abstract = {The novel approach of combining audio and symbolic features
for music classification from audio enhanced previous
audio-only based results in MIREX 2007. We extended the
approach by including temporal audio features, enhancing
the polyphonic audio to MIDI transcription system and including
an extended set of symbolic features. Recent research
in music genre classification hints at a glass ceiling
being reached using timbral audio features.},
keywords = {Acc. Int. E-A, PROSEMUS},
pubstate = {published},
tppubtype = {inproceedings}
}
The novel approach of combining audio and symbolic features
for music classification from audio enhanced previous
audio-only based results in MIREX 2007. We extended the
approach by including temporal audio features, enhancing
the polyphonic audio to MIDI transcription system and including
an extended set of symbolic features. Recent research
in music genre classification hints at a glass ceiling
being reached using timbral audio features. Pertusa, A.; Iñesta, J. M.
Multiple Fundamental Frequency Estimation Using Gaussian Smoothness And Short Context. Proceedings Article
In: MIREX 2008 - Music Information Retrieval Evaluation eXchange, MIREX Fundamental Frequency Estimation & Tracking Contest., Philadelphia, Pennsylvania, USA, 2008.
Links | BibTeX | Tags: Acc. Int. E-A, MIPRCV, PROSEMUS
@inproceedings{k237,
title = {Multiple Fundamental Frequency Estimation Using Gaussian Smoothness And Short Context.},
author = {A. Pertusa and J. M. Iñesta},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/237/F0_pertusa.pdf},
year = {2008},
date = {2008-01-01},
urldate = {2008-01-01},
booktitle = {MIREX 2008 - Music Information Retrieval Evaluation eXchange, MIREX Fundamental Frequency Estimation & Tracking Contest.},
address = {Philadelphia, Pennsylvania, USA},
keywords = {Acc. Int. E-A, MIPRCV, PROSEMUS},
pubstate = {published},
tppubtype = {inproceedings}
}
2007
Pertusa, A.; Rauber, A.; Lidy, T.; Iñesta, J. M.
Improving genre classification by combination of audio and symbolic descriptors using a transcription system Proceedings Article
In: Proc. of the 8th Int. Conf. on Music Information Retrieval, ISMIR 2007, pp. 61-66, Vienna, Austria, 2007.
Links | BibTeX | Tags: Acc. Int. E-A, PROSEMUS
@inproceedings{k196,
title = {Improving genre classification by combination of audio and symbolic descriptors using a transcription system},
author = {A. Pertusa and A. Rauber and T. Lidy and J. M. Iñesta},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/196/aptl_ismir07.pdf},
year = {2007},
date = {2007-01-01},
urldate = {2007-01-01},
booktitle = {Proc. of the 8th Int. Conf. on Music Information Retrieval, ISMIR 2007},
pages = {61-66},
address = {Vienna, Austria},
keywords = {Acc. Int. E-A, PROSEMUS},
pubstate = {published},
tppubtype = {inproceedings}
}
2010
Pérez-Sancho, C.; Rizo, D.; Iñesta, J. M.; León, P. J. Ponce; Kersten, S.; Ramírez, R.
Genre classification of music by tonal harmony Journal Article
In: Intelligent Data Analysis, vol. 14, no. 5, pp. 533-545, 2010, ISSN: 1088-467X.
Abstract | BibTeX | Tags: Acc. Int. E-A, DRIMS, PROSEMUS
@article{k232,
title = {Genre classification of music by tonal harmony},
author = {C. Pérez-Sancho and D. Rizo and J. M. Iñesta and P. J. Ponce León and S. Kersten and R. Ramírez},
issn = {1088-467X},
year = {2010},
date = {2010-09-01},
urldate = {2010-09-01},
journal = {Intelligent Data Analysis},
volume = {14},
number = {5},
pages = {533-545},
abstract = {In this paper we present a genre classification framework for audio music based on a symbolic classification system. Audio signals are transformed into a symbolic representation of harmony using a chord transcription algorithm, based on the computation of harmonic pitch class profiles. Then, language models built from a ground truth of chord progressions for each genre are used to perform classification. We show that chord progressions are a suitable feature to represent musical genre, as they capture the harmonic rules relevant in each musical period or style. Finally, results using both pure symbolic information and chords transcribed from audio-from-MIDI are compared, in order to evaluate the effects of the transcription process in this task.},
keywords = {Acc. Int. E-A, DRIMS, PROSEMUS},
pubstate = {published},
tppubtype = {article}
}
2009
Pérez-Sancho, C.
Stochastic Language Models for Music Information Retrieval PhD Thesis
2009.
Abstract | Links | BibTeX | Tags: Acc. Int. E-A, PROSEMUS
@phdthesis{k240,
title = {Stochastic Language Models for Music Information Retrieval},
author = {C. Pérez-Sancho},
editor = {Jorge Calera Rubio José M. Iñesta},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/240/phdthesis_cperez.pdf},
year = {2009},
date = {2009-07-01},
address = {Alicante, Spain},
organization = {Universidad de Alicante},
abstract = {Music Information Retrieval (MIR) is an interdisciplinary research area that aims at providing solutions to most problems related to the access to multimedia databases, in particular those with musical content, either in symbolic (MIDI) or audio format. An especially relevant problem is the automatic organization and indexation of data, since carrying out these tasks by hand would require an overwhelming effort for most people and institutions.
One of the most relevant features that can be obtained from a song in order to perform its automatic organization is the musical style, since it is one of the most popular fields used by people when accessing musical databases and catalogs. In this thesis it has been studied to what extent the musical style of a piece can be determined using just the information contained in its score, by applying pattern recognition techniques on melodic and harmonic sequences obtained from musical scores.},
keywords = {Acc. Int. E-A, PROSEMUS},
pubstate = {published},
tppubtype = {phdthesis}
}
One of the most relevant features that can be obtained from a song in order to perform its automatic organization is the musical style, since it is one of the most popular fields used by people when accessing musical databases and catalogs. In this thesis it has been studied to what extent the musical style of a piece can be determined using just the information contained in its score, by applying pattern recognition techniques on melodic and harmonic sequences obtained from musical scores.
Pérez-Sancho, C.; Rizo, D.; Iñesta, J. M.
Genre classification using chords and stochastic language models Journal Article
In: Connection Science, vol. 21, no. 2, pp. 145-159, 2009, ISSN: 0954-0091.
Abstract | BibTeX | Tags: Acc. Int. E-A, MIPRCV, PROSEMUS
@article{k227,
title = {Genre classification using chords and stochastic language models},
author = {C. Pérez-Sancho and D. Rizo and J. M. Iñesta},
issn = {0954-0091},
year = {2009},
date = {2009-05-01},
urldate = {2009-05-01},
journal = {Connection Science},
volume = {21},
number = {2},
pages = {145-159},
abstract = {Music genre meta-data is of paramount importance for the organisation of music repositories. People use genre in a natural way when entering a music store or looking into music collections. Automatic genre classification has become a popular topic in music information retrieval research both, with digital audio and symbolic data. This work focuses on the symbolic approach, bringing to music cognition some technologies, like the stochastic language models, already successfully applied to text categorisation. The representation chosen here is to model chord progressions as n-grams and strings and then apply perplexity and naiumlve Bayes classifiers, respectively, in order to assess how often those structures are found in the target genres. Some genres and sub-genres among popular, jazz, and academic music have been considered, trying to investigate how far can we reach using harmonic information with these models. The results at different levels of the genre hierarchy for the techniques employed are presented and discussed.},
keywords = {Acc. Int. E-A, MIPRCV, PROSEMUS},
pubstate = {published},
tppubtype = {article}
}
Pertusa, A.; Iñesta, J. M.
Note Onset Detection Using One Semitone Filter-Bank For MIREX 2009 Proceedings Article
In: MIREX 2009 - Music Information Retrieval Evaluation eXchange, MIREX Audio Onset Detection, Kobe, Japan., 2009.
Links | BibTeX | Tags: Acc. Int. E-A, PROSEMUS
@inproceedings{k238,
title = {Note Onset Detection Using One Semitone Filter-Bank For MIREX 2009},
author = {A. Pertusa and J. M. Iñesta},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/238/PI.pdf},
year = {2009},
date = {2009-01-01},
urldate = {2009-01-01},
booktitle = {MIREX 2009 - Music Information Retrieval Evaluation eXchange, MIREX Audio Onset Detection},
address = {Kobe, Japan.},
keywords = {Acc. Int. E-A, PROSEMUS},
pubstate = {published},
tppubtype = {inproceedings}
}
2008
Iñesta, J. M.; Pertusa, A.
Multiple Fundamental Frequency estimation using Gaussian smoothness Proceedings Article
In: Proc. of the IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP 2008, pp. 105-108, Las Vegas, USA, 2008, ISBN: 1-4244-1484-9.
Links | BibTeX | Tags: Acc. Int. E-A, MIPRCV, PROSEMUS
@inproceedings{k202,
title = {Multiple Fundamental Frequency estimation using Gaussian smoothness},
author = {J. M. Iñesta and A. Pertusa},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/202/2974_sent.pdf},
isbn = {1-4244-1484-9},
year = {2008},
date = {2008-01-01},
urldate = {2008-01-01},
booktitle = {Proc. of the IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP 2008},
pages = {105-108},
address = {Las Vegas, USA},
keywords = {Acc. Int. E-A, MIPRCV, PROSEMUS},
pubstate = {published},
tppubtype = {inproceedings}
}
Pérez-Sancho, C.; Rizo, D.; Kersten, S.; Ramírez, R.
Genre classification of music by tonal harmony Proceedings Article
In: Proc. Int. Workshop on Machine Learning and Music, MML 2008, pp. 21-22, Helsinki, Finland, 2008.
BibTeX | Tags: Acc. Int. E-A, MIPRCV, PROSEMUS
@inproceedings{k209,
title = {Genre classification of music by tonal harmony},
author = {C. Pérez-Sancho and D. Rizo and S. Kersten and R. Ramírez},
year = {2008},
date = {2008-01-01},
booktitle = {Proc. Int. Workshop on Machine Learning and Music, MML 2008},
pages = {21-22},
address = {Helsinki, Finland},
keywords = {Acc. Int. E-A, MIPRCV, PROSEMUS},
pubstate = {published},
tppubtype = {inproceedings}
}
Iñesta, J. M.; Heredia-Agoiz, J. L.; León, P. J. Ponce
A ground-truth experiment on melody genre recognition in absence of timbre Proceedings Article
In: Proc. of the 10th International Conference on Music Perception and Cognition (ICMPC10), pp. 758-761, Sapporo, Japan, 2008, ISBN: 978-4-9904208-0-2.
BibTeX | Tags: Acc. Int. E-A, PROSEMUS
@inproceedings{k215,
title = {A ground-truth experiment on melody genre recognition in absence of timbre},
author = {J. M. Iñesta and J. L. Heredia-Agoiz and P. J. Ponce León},
isbn = {978-4-9904208-0-2},
year = {2008},
date = {2008-01-01},
urldate = {2008-01-01},
booktitle = {Proc. of the 10th International Conference on Music Perception and Cognition (ICMPC10)},
pages = {758-761},
address = {Sapporo, Japan},
keywords = {Acc. Int. E-A, PROSEMUS},
pubstate = {published},
tppubtype = {inproceedings}
}
Pérez-Sancho, C.; Rizo, D.; Iñesta, J. M.
Stochastic text models for music categorization Journal Article
In: Lecture Notes in Computer Science, vol. 5342, pp. 55-64, 2008.
Links | BibTeX | Tags: Acc. Int. E-A, MIPRCV, PROSEMUS
@article{k217,
title = {Stochastic text models for music categorization},
author = {C. Pérez-Sancho and D. Rizo and J. M. Iñesta},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/217/music-cat.pdf},
year = {2008},
date = {2008-01-01},
journal = {Lecture Notes in Computer Science},
volume = {5342},
pages = {55-64},
keywords = {Acc. Int. E-A, MIPRCV, PROSEMUS},
pubstate = {published},
tppubtype = {article}
}
Lidy, T.; Rauber, A.; Pertusa, A.; de León, P. J. Ponce; Iñesta, J. M.
MIREX 2008: Audio Music Classification Using A Combination Of Spectral, Timbral, Rhythmic, Temporal And Symbolic Features. Proceedings Article
In: MIREX 2008 - Music Information Retrieval Evaluation eXchange, MIREX Genre Classification Contest., Philadelphia, Pennsylvania, USA, 2008.
Abstract | Links | BibTeX | Tags: Acc. Int. E-A, PROSEMUS
@inproceedings{k236,
title = {MIREX 2008: Audio Music Classification Using A Combination Of Spectral, Timbral, Rhythmic, Temporal And Symbolic Features.},
author = {T. Lidy and A. Rauber and A. Pertusa and P. J. Ponce de León and J. M. Iñesta},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/236/abstract_mirex08_class.pdf},
year = {2008},
date = {2008-01-01},
urldate = {2008-01-01},
booktitle = {MIREX 2008 - Music Information Retrieval Evaluation eXchange, MIREX Genre Classification Contest.},
address = {Philadelphia, Pennsylvania, USA},
abstract = {The novel approach of combining audio and symbolic features
for music classification from audio enhanced previous
audio-only based results in MIREX 2007. We extended the
approach by including temporal audio features, enhancing
the polyphonic audio to MIDI transcription system and including
an extended set of symbolic features. Recent research
in music genre classification hints at a glass ceiling
being reached using timbral audio features.},
keywords = {Acc. Int. E-A, PROSEMUS},
pubstate = {published},
tppubtype = {inproceedings}
}
for music classification from audio enhanced previous
audio-only based results in MIREX 2007. We extended the
approach by including temporal audio features, enhancing
the polyphonic audio to MIDI transcription system and including
an extended set of symbolic features. Recent research
in music genre classification hints at a glass ceiling
being reached using timbral audio features.
Pertusa, A.; Iñesta, J. M.
Multiple Fundamental Frequency Estimation Using Gaussian Smoothness And Short Context. Proceedings Article
In: MIREX 2008 - Music Information Retrieval Evaluation eXchange, MIREX Fundamental Frequency Estimation & Tracking Contest., Philadelphia, Pennsylvania, USA, 2008.
Links | BibTeX | Tags: Acc. Int. E-A, MIPRCV, PROSEMUS
@inproceedings{k237,
title = {Multiple Fundamental Frequency Estimation Using Gaussian Smoothness And Short Context.},
author = {A. Pertusa and J. M. Iñesta},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/237/F0_pertusa.pdf},
year = {2008},
date = {2008-01-01},
urldate = {2008-01-01},
booktitle = {MIREX 2008 - Music Information Retrieval Evaluation eXchange, MIREX Fundamental Frequency Estimation & Tracking Contest.},
address = {Philadelphia, Pennsylvania, USA},
keywords = {Acc. Int. E-A, MIPRCV, PROSEMUS},
pubstate = {published},
tppubtype = {inproceedings}
}
2007
Pertusa, A.; Rauber, A.; Lidy, T.; Iñesta, J. M.
Improving genre classification by combination of audio and symbolic descriptors using a transcription system Proceedings Article
In: Proc. of the 8th Int. Conf. on Music Information Retrieval, ISMIR 2007, pp. 61-66, Vienna, Austria, 2007.
Links | BibTeX | Tags: Acc. Int. E-A, PROSEMUS
@inproceedings{k196,
title = {Improving genre classification by combination of audio and symbolic descriptors using a transcription system},
author = {A. Pertusa and A. Rauber and T. Lidy and J. M. Iñesta},
url = {https://grfia.dlsi.ua.es/repositori/grfia/pubs/196/aptl_ismir07.pdf},
year = {2007},
date = {2007-01-01},
urldate = {2007-01-01},
booktitle = {Proc. of the 8th Int. Conf. on Music Information Retrieval, ISMIR 2007},
pages = {61-66},
address = {Vienna, Austria},
keywords = {Acc. Int. E-A, PROSEMUS},
pubstate = {published},
tppubtype = {inproceedings}
}