Publications obtained in PROSEMUS project
Modeling Violin Performances Using Inductive Logic Programming
Rafael Ramirez, Alfonso Perez, Stefan Kersten, David Rizo, Plácido Román, Jose M. Iñesta.
Intelligent Data Analysis, 2010 (In press)
An approach to predicting bowing control parameter contours in violin performance
Esteban Maestre, Rafael Ramirez.
Intelligent Data Analysis, 2010 (In press)
Genre classification of music by tonal harmony
Pérez-Sancho, C.; Rizo, D.; Iñesta, J.M.; Ponce de León, P.J.; Kersten, S.; Ramirez, R., Intelligent Data Analysis, 2010 (In press)
bibtex
abstract
@article {
author = "Pérez-Sancho, C.;
Rizo, D.; Iñesta, J.M.; Ponce de León, P.J.; Kersten, S.; Ramirez,
R.",
title = "Genre classification of music by tonal harmony",
issn
= "1088-467X",
journal = "Intelligent Data Analysis",
volume = "in
press",
year = "2010 (In press)"
}
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.
A Framework for Performer Identification in Audio Recordings
Ramirez, R., Maestre, E. Proceedings International Workshop on Machine Learning and Music - European Conference on Machine Learning, Bled, Slovenia. 2009
A probabilistic approach to melodic similarity
Bernabeu, J.F., Calera-Rubio, J., Iñesta, J.M., Rizo, D., Proceedings of MML 2009, 48-53, 2009
bibtex
abstract
@inproceedings {
author = "Bernabeu, J.F., Calera-Rubio,
J., Iñesta, J.M., Rizo, D.",
title = "A probabilistic approach to
melodic similarity",
booktitle = "Proceedings of MML 2009",
pages =
"48-53",
year = "2009"
}
Melodic similarity is an
important research topic in music information retrieval.
The representation of symbolic music by means of trees has proven to be
suitable
in melodic similarity computation, because they are able to code rhythm in
their
structure leaving only pitch representations as a degree of freedom for
coding.
In order to compare trees, different edit distances have been previously
used.
In this paper, stochastic k-testable tree-models, formerly used in other
domains
like structured document compression or natural language processing, have
been
used for computing a similarity measure between melody trees as a
probability
and their performance has been compared to a classical tree edit distance.
Cross recurrence quantification for cover song identification
Serrà, J., Serra, X., Andrzejak, R.G. (2009).
New Journal of Physics. 11, 093017.
Ensemble of state-of-the-art methods for polyphonic music comparison
Rizo, D. and Lemström, K. and Iñesta, J.M., Proceedings of the Workshop on Exploring Musical Information
Spaces, ECDL 2009, Rauber, Andreas; Orio, Nicola; Rizo, David, 46--51, 2009
pdf
bibtex
abstract
@inproceedings {
author = "Rizo, D. and Lemström, K. and
Iñesta, J.M.",
title = "Ensemble of state-of-the-art methods for
polyphonic music comparison",
address = "Corfu, Greece",
booktitle =
"Proceedings of the Workshop on Exploring Musical Information Spaces, ECDL
2009",
editor = "Rauber, Andreas; Orio, Nicola; Rizo, David",
isbn =
"978-84-692-6082-1",
month = "October",
pages = "46--51",
year =
"2009",
df = "wemis2009.pdf"
}
Content-based music comparison is a task where no
musical similarity measure can perform well in all possible cases. In this
paper we will show that a careful combination of different similarity
measures in an ensemble measure, will behave more robust than any of the
included individual measures when applied as stand-alone measures. For the
experiments we have used five state-of-the-art polyphonic similarity
measures and three different corpora of polyphonic
music.
Expressive Concatenative Synthesis by (re)Using Samples from Real Performance Recordings
Esteban Maestre, Rafael Ramirez, Xavier Serra.
Computer Music Journal, Vol.33(4), pp. 23-42.
2009
First-Order Logic Classification Models of Musical Genres Based on Harmony
Anglade, A., Ramirez, R., Dixon, S.
Proceedings Sound and Music Computing Conference,
Porto.
2009
Detecting Solo Phrases in Music using Spectral and Pitch-related Descriptors
Fuhrmann, F., Herrera, P., Serra, X.
Journal of New Music Research, Vol. 38(4), pp. 343-356. 2009.
Genre classification using chords and stochastic language models
Pérez-Sancho, C.; Rizo, D; Iñesta, J.M.,
Connection Science, 145-159, 21, 2009
bibtex
abstract
@article {
author = "Pérez-Sancho, C.; Rizo, D; Iñesta,
J.M.",
title = "Genre classification using chords and stochastic
language models",
issn = "0954-0091",
journal = "Connection
Science",
month = "May",
number = "2 & 3",
pages =
"145-159",
volume = "21",
year = "2009",
rchivarRua =
"1"
}
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.
Genre Classification Using Harmony Rules Induced From Automatic Chord Transcriptions
Anglade, A., Ramirez, R., Dixon, S.
International Society for Music Information Retrieval
Conference, ISMIR 2009. Kobe, Japan. pp. 669-674.
2009
Indexing Music by Mood: Design and Integration of an Automatic
Content-based Annotator
Laurier, C., Meyers, O., Serrà, J., Blech, M., Herrera, P., Serra, X.
(2009). Multimedia Tools and Applications.
metamidi: a tool for automatic metadata extraction from MIDI files
Pérez-García, T.; Iñesta, J.M.; Rizo, D.,
Proceedings of the Workshop on Exploring Musical Information Spaces, ECDL
2009, Rauber, Andrea; Orio, Nicola; Rizo, David, 36--40, 2009
pdf
bibtex
abstract
@inproceedings {
author = "Pérez-García, T.; Iñesta,
J.M.; Rizo, D.",
title = "metamidi: a tool for automatic metadata
extraction from MIDI files",
address = "Corfu, Greece",
booktitle =
"Proceedings of the Workshop on Exploring Musical Information Spaces, ECDL
2009",
editor = "Rauber, Andrea; Orio, Nicola; Rizo, David",
isbn =
"978-84-692-6082-1",
month = "October",
pages = "36--40",
year =
"2009",
df = "metamidi.pdf"
}
The
increasing availability of on-line music has motivated a growing interest
for organizing, commercializing, and delivering this kind of multimedia
content. For it, the use of metadata is of utmost importance. Metadata
permit organization, indexing, and retrieval of music contents. They are,
therefore, a subject of research both from the design and automatic
extraction approaches. The present work focuses on this second issue,
providing an open source tool for metadata extraction from standard MIDI
files. The tool is presented, the utilized metadata are explained, and some
applications and experiments are described as examples of its
capabilities.
Modeling timing expressiveness in singing voice performances
Marinescu, M.C., Ramirez, R.
Proceedings International Workshop on Machine Learning and Music- European Conference on Machine Learning, Bled, Slovenia. 2009.
Statistical analysis of chroma features in western music predicts human judgments of tonality
Serrà, J., Gómez, E., Herrera, P., Serra, X. (2009)
Journal of New Music Research. 37(4), 299-309.
Stochastic Language Models for Music Information Retrieval
Pérez-Sancho, C.
PhD Thesis. Supervisors: Iñesta, J.M., Calera, J.
Universidad de Alicante, Alicante, Spain (2009)
pdf
bibtex
abstract
@phdthesis {
author = "Pérez-Sancho,C.",
title = "Stochastic Language Models for Music Information Retrieval",
address = "Alicante, Spain",
editor = "Iñesta, J.M., Calera, J.",
month = "July",
organization = "Universidad de Alicante",
year = "2009"
}
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.
Supporting Soundscape Design in Virtual Environments with Content-based Audio Retrieval
Janer, J., Finney, N., Roma, G., Kersten, S., Serra, X. (2009).
Journal of Virtual Worlds Research. 2(3),
Tree representation in combined polyphonic music comparison
Rizo, D. and Lemström, K. and Iñesta, J.M., Computer Music Modeling and Retrieval. Genesis of Meaning in Sound and
Music. Lecture Notes in Computer Science, 177--195, 5493, 2009
bibtex
abstract
@article {
author = "Rizo, D. and Lemström, K. and Iñesta, J.M.",
title = "Tree representation in combined polyphonic music comparison",
issn = "978-3-642-02517-4",
journal = "Computer Music Modeling and Retrieval. Genesis of Meaning in Sound and Music. Lecture Notes in Computer Science",
pages = "177--195",
volume = "5493",
year = "2009"
}
Identifying copies or different versions of
a same musical work is a focal problem in maintaining large music databases.
In this paper we introduce novel ideas and methods that are applicable to
metered, symbolically encoded polyphonic music. We show how to represent and
compare polyphonic music using a tree structure. Moreover, we put for trial
various comparison methods and observe whether better comparison results can
be obtained by combining distinct similarity measures. Our experiments show
that the proposed representation is adequate for the task with good quality
results and processing times, and when combined with other methods it
becomes more robust against various types of music.
What/when causal expectation modelling applied to audio signals
Hazan, A., Marxer, R., Brossier, P., Purwins, H., Herrera, P., Serra, X.
(2009). Connection Science. 21(2-3), 119 - 143.
A ground-truth experiment on melody genre recognition in absence of timbre
Iñesta, J.M.; Ponce de León, P.J., Heredia-Agoiz, J.L., Proc. of the 10th International Conference on
Music Perception and Cognition (ICMPC10), 758-761, 2008
bibtex
@inproceedings {
author = "Iñesta, J.M.; Ponce de León,
P.J., Heredia-Agoiz, J.L.",
title = "A ground-truth experiment on
melody genre recognition in absence of timbre",
address = "Sapporo,
Japan",
booktitle = "Proc. of the 10th International Conference on Music
Perception and Cognition (ICMPC10)",
isbn = "978-4-9904208-0-2",
pages = "758-761",
year = "2008"
}
An Evolutionary Computing Approach to Expressive Music Performance
Rafael Ramirez, Amaury Hazan, Esteban
Maestre, Xavier Serra
Computer Music Journal, Vol. 32(1), pp. 38-50
2008
An fMRI Study on Attentive Music Listening
Rafael Ramirez
Títol: An fMRI Study on Attentive Music Listening.
Proceedings of The Neurosciences and Music III, Montreal
2008
Chroma Binary Similarity and Local Alignment Applied to Cover Song Identification
Serrà, J., Gómez, E., Herrera, P., Serra, X. (2008).
IEEE Transactions on Audio, Speech and Language Processing. 16(6), 1138-1151.
Computational Models of Music Perception and Cognition I: The Perceptual and Cognitive Processing Chain
Purwins, H., Herrera, P., Grachten, M., Hazan, A., Marxer, R., Serra, X.
(2008).
Physics of Life Reviews. 5(3), 151-168.
Computational Models of Music Perception and Cognition II: Domain-Specific Music Processing
Purwins, H., Grachten, M., Herrera, P., Hazan, A., Marxer, R., Serra, X.
(2008). Physics of Life Reviews. 5(3), 169-182.
Concatenative Synthesis of Expressive Saxophone Performance
Kersten, S., Maestre, E., Ramirez, R.
Proceedings Sound and Music Conference, Berlin
2008
Expressive Irish Fiddle Performance Model Informed with Bowing
Perez, A., Maestre, E., Ramirez, R., Kersten, S.
Proceedings International Computer Music Conference
2008
Expressive Performance in the Human Tenor Voice
Marinescu, M.C., Ramirez, R.
Proceedings Sound and Music Conference, Berlin
2008
Learning to analyse tonal music
Illescas, P.R., Rizo, D., Iñesta, J.M., Proc. Int. Workshop on Machine Learning and Music, MML 2008, 25-26, 2008
bibtex
@inproceedings {
author = "Illescas,
P.R., Rizo, D., Iñesta, J.M.",
title = "Learning to analyse tonal music",
address = "Helsinki, Finland",
booktitle = "Proc. Int.
Workshop on Machine Learning and Music, MML 2008",
pages = "25-26",
year = "2008"
}
Melody characterization by a fuzzy rule system
Ponce de León, P.J., Rizo, D., Ramírez, R., Proc. Int. Workshop on Machine Learning and Music, MML 2008, 35-36, 2008
bibtex
@inproceedings {
author = "Ponce de
León, P.J., Rizo, D., Ramírez, R.",
title = "Melody characterization
by a fuzzy rule system",
address = "Helsinki, Finland",
booktitle =
"Proc. Int. Workshop on Machine Learning and Music, MML 2008",
pages =
"35-36",
year = "2008"
}
Melody Characterization by a Genetic Fuzzy System
Ponce de León, P.J.; Rizo, D.; Ramirez, R.; Iñesta, J.M., Proceedings of the 5th Sound and Music Computing Conference , Martin
Supper and Stefan Weinzierl, Universitätsverlag der TU Berlin, 15-23,
2008
pdf
bibtex
abstract
@inproceedings {
author = "Ponce de León, P.J.; Rizo, D.;
Ramirez, R.; Iñesta, J.M.",
title = "Melody Characterization by a
Genetic Fuzzy System",
booktitle = "Proceedings of the 5th Sound and
Music Computing Conference ",
editor = "Martin Supper and Stefan
Weinzierl",
month = "July",
pages = "15-23",
publisher =
"Universitätsverlag der TU Berlin",
year = "2008",
df =
"smc-08.pdf"
}
We present preliminary work on automatic
human-readable melody
characterization. In order to obtain such a characterization, we
(1) extract a set of statistical descriptors from the tracks in a dataset of
MIDI files,
(2) apply a rule induction algorithm to obtain a set of (crisp)
classification
rules for melody track identification, and (3) automatically transform the
crisp rules into fuzzy rules by applying a genetic algorithm to generate the
membership
functions for the rule attributes.
Some results are presented and discussed.
Melody recognition with learned edit distances
Habrard, A.; Iñesta, J.M.; Rizo, D.; Sebban, M., Lecture Notes in Computer Science, 86-96, 5342, 2008
pdf
bibtex
@article {
author = "Habrard, A.; Iñesta, J.M.; Rizo, D.;
Sebban, M.",
title = "Melody recognition with learned edit
distances",
journal = "Lecture Notes in Computer Science",
pages =
"86-96",
volume = "5342",
year = "2008",
df =
"melody-rec.pdf",
rchivarRua = "1"
}
Mining digital music score collections: melody extraction and genre recognition
Ponce de León, P.J.; Iñesta, J.M.; Rizo, D. In: Pattern Recognition, 25, Peng-YengYin, ed. IN-TECH, pp. 559-590. ISBN: 978-3-902613-24-4. 2008
bibtex
abstract
@inbook {
author = "Ponce de León, P.J.; Iñesta, J.M.;
Rizo, D.",
title = "Mining digital music score collections: melody
extraction and genre recognition",
address = "Vienna, Austria",
booktitle = "Pattern Recognition",
chapter = "25",
editor =
"Peng-Yeng Yin",
isbn = "978-3-902613-24-4",
month = "November",
pages = "559-590",
publisher = "IN-TECH",
year =
"2008"
}
In the field of computer music, pattern
recognition algorithms are very
relevant for music information retrieval (MIR) applications. Two challenging
tasks in this area is the automatic recognition of musical genre and melody
extraction, having a
number of applications like indexing and selecting musical databases.
One of the main references for music is its melody. In a practical
environment of digital music score collections the information can be found
in standard MIDI file format. Music is structured as a number of tracks in
this file format, usually one of them containing the melodic line, while
others tracks contain the accompaniment.
Finding that melody track is very useful for a number of applications, like
speeding up melody
matching when searching in MIDI databases, extracting motifs for
musicological analysis, building
music thumbnails or extracting melodic ringtones from MIDI files.
In the first part of this chapter,
musical content information is modeled by computing global statistical
descriptors from track content.
These descriptors are the input to a random forest classifier
that assigns the probability of being a melodic line to each track. The
track with the highest probability is then selected as the one containing
the
melodic line of the MIDI file. The first part of this chapter ends with a
discussion on results obtained from a number of databases of different music
styles.
The second part of the chapter deals with the problem of classifying such
melodies in a collection of music genres. A slightly different approach is
used for this task, first dividing a melody track in segments of fixed
length. Statistical features are extracted for each segment and used to
classify them as one of several genres.
The proposed methodology
is presented, covering the feature extraction, feature selection,
and genre classification stages. Different supervised classification
methods, like Bayesian classifier and nearest neighbors are applied. As a
proof of concept, the performance of such algorithms against different
description models and parameters is analyzed for two particular musical
genres, like jazz and classical music.
MIREX 2008: Audio Music Classification Using A Combination Of Spectral, Timbral, Rhythmic, Temporal And Symbolic Features.
Lidy T., Rauber A., Pertusa A., Ponce de León P.J., Iñesta J. M.
MIREX 2008 - Music Information Retrieval Evaluation eXchange, MIREX Genre Classification Contest, Philadelphia, Pennsylvania, USA, September 14-18, 2008
bibtex
abstract
@inproceedings {
author = "Lidy T., Rauber A., Pertusa A., Ponce de León P.J., Iñesta J. M.",
title = "MIREX 2008: Audio Music Classification Using A Combination Of Spectral, Timbral, Rhythmic, Temporal And Symbolic Features.",
address = "Philadelphia, Pennsylvania, USA",
booktitle = "MIREX 2008 - Music Information Retrieval Evaluation eXchange, MIREX Genre Classification Contest, Philadelphia, Pennsylvania, USA, September 14-18, 2008",
year = "2008",
url = "http://www.music-ir.org/mirex/2008/"
}
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.
Modeling celtic violin expressive performance
Ramírez, R., Pérez, A.; Kersten, S., Rizo, D., Illescas, P.R., Iñesta, J.M., Proc. Int. Workshop on Machine Learning and
Music, MML 2008, 7-8, 2008
bibtex
@inproceedings {
author = "Ramírez, R., Pérez, A.;
Kersten, S., Rizo, D., Illescas, P.R., Iñesta, J.M.",
title =
"Modeling celtic violin expressive performance",
address = "Helsinki,
Finland",
booktitle = "Proc. Int. Workshop on Machine Learning and
Music, MML 2008",
pages = "7-8",
year =
"2008"
}
Modeling Moods in Violin Performances
Perez, A., Ramirez, R., Kersten, S.
Proceedings Sound and Music Conference, Berlin
2008
Multiple Fundamental Frequency estimation using Gaussian smoothness
Pertusa A., Iñesta J.M., Proc. of the IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP 2008,
105-108, 2008
pdf
bibtex
@inproceedings {
author = "Pertusa A., Iñesta J.M.",
title = "Multiple Fundamental Frequency estimation using Gaussian
smoothness",
address = "Las Vegas, USA",
booktitle = "Proc. of the
IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP
2008",
isbn = "1-4244-1484-9",
pages = "105-108",
year =
"2008",
df = "2974_sent.pdf"
}
Multiple Fundamental Frequency Estimation Using Gaussian Smoothness And Short Context.
Pertusa A., Iñesta J. M.
MIREX 2008 - Music Information Retrieval Evaluation eXchange, MIREX Fundamental Frequency Estimation & Tracking Contest, Philadelphia, Pennsylvania, USA, September 14-18, 2008
bibtex
abstract
@inproceedings {
author = "Pertusa A., Iñesta J. M.",
title = "Multiple Fundamental Frequency Estimation Using Gaussian Smoothness And Short Context.",
address = "Philadelphia, Pennsylvania, USA",
booktitle = "MIREX 2008 - Music Information Retrieval Evaluation eXchange, MIREX Fundamental Frequency Estimation & Tracking Contest, Philadelphia, Pennsylvania, USA, September 14-18, 2008",
year = "2008",
url = "http://www.music-ir.org/mirex/2008/"
}
Performer Identification in Celtic Violin Recordings
Ramirez, R., Perez, A., Kersten, S., Maestre, E.
Proceedings International Society of Music Information
Retrieval Conference, Philadelphia
2008
Rule-based Expressive Performance Model for Jazz Saxophone
Ramirez, R., Hazan, A., Maestre, E., Serra, X.
Computer Music Journal, 32(1), 338-350, 2008.
Stochastic text models for music categorization
Pérez-Sancho, C.; Rizo, D.; Iñesta, J.M., Lecture Notes in Computer Science, 55-64, 5342, 2008
pdf
bibtex
@article {
author = "Pérez-Sancho, C.; Rizo, D.; Iñesta,
J.M.",
title = "Stochastic text models for music categorization",
journal = "Lecture Notes in Computer Science",
pages = "55-64",
volume = "5342",
year = "2008",
df = "music-cat.pdf",
rchivarRua
= "1"
}
Tree structured and combined methods for comparing metered polyphonic music
Rizo, D., Lemström, K., Iñesta, J.M., Proc. Computer Music Modeling and Retrieval 2008 (CMMR'08), 263--278, 2008
bibtex
@inproceedings {
author = "Rizo, D.,
Lemström, K., Iñesta, J.M.",
title = "Tree structured and combined
methods for comparing metered polyphonic music",
address = "Copenhagen,
Denmark",
booktitle = "Proc. Computer Music Modeling and Retrieval 2008
(CMMR'08)",
isbn = "978-87-7606-027-5",
month = "May",
pages =
"263--278",
year = "2008"
}
-->
A cooperative approach to style-oriented music composition
Espí D., Ponce de León P.J., Pérez-Sancho C., Rizo D., Iñesta J.M., Moreno-Seco F., Pertusa A., Proc. of the Int.
Workshop on Artificial Intelligence and Music, MUSIC-AI, 25-36, 2007
pdf
bibtex
@inproceedings {
author = "Espí D., Ponce de León P.J.,
Pérez-Sancho C., Rizo D., Iñesta J.M., Moreno-Seco F., Pertusa A.",
title = "A cooperative approach to style-oriented music composition",
address = "Hyderabad, India",
booktitle = "Proc. of the Int. Workshop on
Artificial Intelligence and Music, MUSIC-AI",
pages = "25-36",
year
= "2007",
df = "wijcai07.pdf"
}
A Framework for Separation of Concerns in Concurrent Programming
Rafael Ramirez, Andrew Santosa
IEEE International Computer Software and Applications
Conference, IEEE Press, Beijing
2007
A Genetic Programming Approach to Feature Selection and Classification of Instantaneous Cognitive States
Rafael Ramirez, Montserrat Puiggros
Lecture Notes in Computer
Science, 4448, pp. 311-319
2007
A Genetic Rule-based Expressive Performance Model for Jazz Saxophone
Rafael Ramirez, Amaury Hazan
IJCAI International Workshop on Artificial Intelligence and
Music, India,
2007
A Machine Learning Approach to Detecting Instantaneous Cognitive States from fMRI Data
Rafael Ramirez, Montserrat Puiggros. Pacific-Asia
Conference on Knowledge Discovery and Data Mining, Lecture Notes in
Computer Science, Springer, 4426, pp. 248-259. Nanjing, 2007.
An Evolutionary Computation Approach to Cognitive States Classification
Rafael Ramirez, Montserrat Puiggros
IEEE Congress on Evolutionary Computing, IEEE Press,
Singapore
2007
A Pattern Recognition Approach for Music Style Identification Using Shallow Statistical Descriptors
Ponce de León P. J. and Iñesta J. M., IEEE Transactions on Systems Man and Cybernetics C, 248-257, 37, 2007
bibtex
abstract
@article {
author = "Ponce de León P. J. and Iñesta J.
M.",
title = "A Pattern Recognition Approach for Music Style
Identification Using Shallow Statistical Descriptors",
journal = "IEEE
Transactions on Systems Man and Cybernetics C",
number = "2",
pages
= "248-257",
volume = "37",
year =
"2007"
}
In the field of computer music, pattern
recognition algorithms are very
relevant for music information retrieval (MIR) applications. One challenging
task in this area is the automatic recognition of musical style, having a
number of applications like indexing and selecting musical databases. From
melodies symbolically represented as digital scores (standard MIDI files) a
number of melodic, harmonic, and rhythmic statistical descriptors are
computed and their classification capability assessed in order to build
effective description models. A framework for experimenting in this
problem is presented, covering the feature extraction, feature selection,
and classification stages, in such a way that new features and new musical
styles can be easily incorporated and tested. Different classification
methods, like Bayesian classifier, nearest neighbors, and self-organising
maps are applied. The performance of such algorithms against different
description models and parameters is analyzed for two particular musical
styles, like jazz and classical, used as an initial benchmark for our
system.
Automatically Detecting Cognitive States: a Speech and Music Case Study
Rafael Ramirez, Montserrat Puiggros
International Conference on Language and Music as
Cognitive Systems, Cambridge, UK,
2007
Automatic Classification of Instantaneous Auditory Cognitive States
Rafael Ramirez, Montserrat Puiggros
Conference of the Society for Music Perception and
Cognition, Montreal
2007
Comparación de representaciones interválicas hansonianas para recuperación de información musical
J.F. Serrano, J.M. Iñesta, Revista Iberoamericana de Inteligencia Artificial, 7-15, 11, 2007
bibtex
abstract
@article {
author = "J.F. Serrano, J.M.
Iñesta",
title = "Comparación de representaciones interválicas
hansonianas para recuperación de información musical",
journal =
"Revista Iberoamericana de Inteligencia Artificial",
number = "34",
pages = "7-15",
volume = "11",
year =
"2007"
}
En la recuperación de información musical
se utiliza la similitud melódica como elemento principal para la detección
de información relevante. Entre las aplicaciones posibles se encuentran
detección de plagio de ideas ya expuestas por un artista en el pasado, el
pago por derecho de autor por medio de detección de piezas musicales en
transmisiones de radio, la asistencia en la composición, etc. Existen
varias técnicas expuestas en similitud melódica que utilizan diversos
análisis estadísticos y probabilísticos. El objetivo en este trabajo es
establecer un equivalente de la notación musical a palabras de texto
utilizando una representación basada en relaciones interválicas y de
duración, y evaluar tres de las técnicas de recuperación de información
textual aplicadas a esta representación, además de proponer cambios para
mejorar el rendimiento de
sistema.
Harmonic, melodic, and functional automatic analysis
Plácido R. Illescas, David Rizo, José M. Iñesta, Proceedings of the 2007 International Computer Music Conferrence, 165--168,
2007
pdf
bibtex
abstract
@inproceedings {
author = "Plácido R. Illescas, David
Rizo, José M. Iñesta",
title = "Harmonic, melodic, and functional
automatic analysis",
booktitle = "Proceedings of the 2007 International
Computer Music Conferrence",
pages = "165--168",
year = "2007",
df = "icmc07_tonal_analysis.pdf"
}
This work
is an effort towards the development of a system for the automation of
traditional harmonic analysis of polyphonic scores in symbolic format. A
number of stages have been
designed in this procedure: melodic analysis of harmonic and non-harmonic
tones, vertical harmonic analysis, tonality, and tonal functions. All these
informations are
represented as a weighted directed acyclic graph. The best possible analysis
is
the path that maximizes the sum of weights in the graph, obtained through a
dynamic programming algorithm. The feasibility of this approach has been
tested on six J.S. Bach's harmonized
chorales
Identifying saxophonists from their playing styles
Ramírez R., Maestre E., Pertusa A., Proc. of the 30th Audio Engineering Society (AES) Conference, 2007
bibtex
@inproceedings {
author = "Ramírez R., Maestre E., Pertusa
A.",
title = "Identifying saxophonists from their playing styles",
address = "Saariselkä, Finland",
booktitle = "Proc. of the 30th Audio
Engineering Society (AES) Conference",
year =
"2007"
}
Improving genre classification by combination of audio and symbolic descriptors using a transcription system
Lidy T., Rauber A., Pertusa A., Iñesta J.M., Proc. of the 8th Int. Conf. on Music Information Retrieval, ISMIR 2007, 61-66, 2007
pdf
bibtex
@inproceedings {
author = "Lidy T., Rauber A., Pertusa A.,
Iñesta J.M.",
title = "Improving genre classification by combination
of audio and symbolic descriptors using a transcription system",
address
= "Vienna, Austria",
booktitle = "Proc. of the 8th Int. Conf. on Music
Information Retrieval, ISMIR 2007",
pages = "61-66",
year =
"2007",
df = "aptl_ismir07.pdf"
}
Inducing a Generative Expressive Performance Model using a Sequential-Covering Genetic Algorithm
Rafael Ramirez, Amaury Hazan
Genetic and Evolutionary Computation Conference, ACM,
London
2007
Learning to Decode Instantaneous Cognitive States from Brain Images
Rafael Ramirez, Enric Cecilla
Fontiers in the Converge of Biosicnce and Information
Technologies, IEEE Computer Societe Press, Korea.
2007
MIREX 2007: Combining Audio And Symbolic Descriptors For Music Classification From Audio.
Lidy T., Rauber A., Pertusa A., Iñesta J. M.
MIREX 2007 - Music Information Retrieval Evaluation eXchange, MIREX Genre Classification Contest, Vienna, Austria, September 23-27, 2007
bibtex
abstract
@inproceedings {
author = "Lidy T., Rauber A., Pertusa A., Iñesta J. M.",
title = "MIREX 2007: Combining Audio And Symbolic Descriptors For Music Classification From Audio.",
address = "Vienna, Austria",
booktitle = "MIREX 2007 - Music Information Retrieval Evaluation eXchange, MIREX Genre Classification Contest, Vienna, Austria, September 23-27, 2007",
year = "2007",
url = "http://www.music-ir.org/mirex/2007/"
}
Recent research in music genre classification hints at a
glass ceiling being reached using timbral audio features.
To overcome this, the combination of multiple different
feature sets bearing diverse characteristics is needed. We
propose a new approach to extend the scope of the features:
We transcribe audio data into a symbolic form using
a transcription system, extract symbolic descriptors from
that representation and combine them with audio features.
With this method, we are able to surpass the glass ceiling
and to further improve music genre classification.
Multiple fundamental frequency estimation based on spectral pattern loudness and smoothness
Pertusa, A., Iñesta, J.M., Music Information Retrieval Evaluation eXchange, MIREX Genre Classification Contest, Vienna, Austria, September 23-27, 2007
bibtex
abstract
@inproceedings {
author = "Pertusa, A., Iñesta, J.M.",
title = "Multiple fundamental frequency estimation based on spectral pattern loudness and smoothness",
address = "Vienna, Austria",
booktitle = "MIREX 2007 - Music Information Retrieval Evaluation eXchange, MIREX Fundamental Frequency Estimation & Tracking Contest, Vienna, Austria, September 23-27, 2007",
year = "2007",
url = "http://www.music-ir.org/mirex/2007/"
}
Two multiple fundamental frequency estimation systems
are presented in this work. In the first one (PI1, PI2),
the best fundamental frequency candidates combination is
found in a frame-by-frame analysis by applying a set of
rules, taking into account the spectral smoothness measure
described in this work. The second system (PI3) was
used to extract symbolic features for audio genre classification
in a fast way, so the evaluation of this system can
reveal the potential of another similar approaches to support
these kind of tasks.
Performance-based Interpreter Identification in Saxophone Audio Recordings
Ramirez R., Maestre E., Pertusa A., Gómez E., Serra X., IEEE Transactions on Circuits and Systems for Video
Technology , 356-364, 7, 2007
bibtex
@article {
author = "Ramirez R., Maestre E., Pertusa A.,
Gómez E., Serra X.",
title = "Performance-based Interpreter
Identification in Saxophone Audio Recordings",
journal = "IEEE
Transactions on Circuits and Systems for Video Technology ",
number =
"3",
pages = "356-364",
volume = "7",
year =
"2007"
}
Performance Model for Jazz Saxophone
Rafael Ramirez, Amaury Hazan. Int. Workshop on Artificial Intelligence
and Music, MUSIC-AI, IJCAI International Workshop on Artificial Intelligence and Music, Hyderabad, India, 2007.
Performance Model using a Sequential-Covering Genetic Algorithm
Rafael Ramirez, Amaury Hazan. Inducing a Generative Expressive, Genetic
and Evolutionary Computation Conference, ACM, London, 2007.
Towards a human-friendly melody characterization by automatically induced rules
Pedro J. Ponce de León, José M. Iñesta, David Rizo, Proceedings of the 8th Int. Conf. on Music Information
Retrieval, ISMIR 2007, Simon Dixon, David Bainbridge, Rainer Typke, Austrian
Computer Society, 437--440, 2007
pdf
bibtex
abstract
@inproceedings {
author = "Pedro J. Ponce de León, José M. Iñesta, David Rizo",
title = "Towards a human-friendly melody characterization by automatically induced rules",
address = "Vienna",
booktitle = "Proceedings of the 8th Int. Conf. on Music Information
Retrieval, ISMIR 2007",
editor = "Simon Dixon, David Bainbridge, Rainer Typke",
month = "September",
organization = "Austrian Computer Society",
pages = "437--440",
publisher = "Austrian Computer Society",
year = "2007"
}
There is an increasing interest in music information retrieval for
reference, motive, or thumbnail extraction from a piece in order to have a
compact and representative representation of the information to be
retrieved. One of the main references for music is its melody. In a
practical environment of symbolic format collections the information can be
found in standard MIDI file format, structured as a number of tracks,
usually one of them containing the melodic line, while the others contain
the accompaniment. The goal of this work is to analyse how statistical rules
can be used to characterize a melody in such a way that one can understand
the solution of an automatic system for selecting the track containing the
melody in such files.
A Logic-based Language for Modeling and Verifying Musical Processes
Rafael Ramirez.
International Computer Music Conference; New Orleans,
2006
A Pattern Recognition Approach for Melody Track Selection in MIDI Files.
Rizo D., Ponce de León P. J., Pérez-Sancho C., Pertusa A., Iñesta J. M. (2006).
In: Proc. of the 7th Int. Symp. on Music Information Retrieval ISMIR 2006, pp. 61-66, Victoria, Canada.
bibtex
@inproceedings {
author = "Rizo D., Ponce de León P. J., Pérez-Sancho C., Pertusa A., Iñesta J. M.",
title = "A Pattern Recognition Approach for Melody Track Selection in MIDI Files",
address = "Victoria, Canada",
booktitle = "Proc. of the 7th Int. Symp. on Music Information Retrieval ISMIR 2006",
editor = "Dannenberg R., Lemström K., Tindale A.",
isbn = "1-55058-349-2",
pages = "61-66",
year = "2006"
}
A Tool for Generating and Explaining Expressive Music Performances of Monophonic Jazz Melodies
Rafael Ramirez, Amaury Hazan.
International Journal on Artificial Intelligence Tools, 15(4), pp. 673-691,
2006
Evolving performance models by performance similarity: beyond note-to-note transformations
Hazan, A. Grachten, M. Ramirez, R.
Intl. Conference on Music Information Retrieval; Canada,
2006
Modeling Expressive Performance: a Regression Tree Approach Based on Strongly Typed Genetic Programming
Amaury Hazan, Rafael Ramirez, E.
Maestre, A. Perez, A. Pertusa.
Lecture Notes in Computer
Science, 3907, pp. 676-687,
2006
Modeling Expressive Music Performance in Bassoon Audio
R. Ramirez, E. Gomez, V. Vicente, M.
Puiggross, A. Hazan, E. Maestre.
Lecture Notes in Control and Information Sciences, 345, pp. 951-958,
2006
Using concatenative synthesis for expressive performance in jazz saxophone
Maestre, E. Hazan, A. Ramirez, R. Perez, A.
International Computer Music Conference, New Orleans,
2006