Publications
Publicaciones
| Molina-Solana, M. (2008), "Composing Music with Multiagent Systems", In 3rd International Conference On Art & Technology. Technarte 2008. Bilbao, Spain. April 24-25 2008. |
BibTeX:
@inproceedings{Molina-Solana2008a,
author = {Miguel Molina-Solana},
title = {Composing Music with Multiagent Systems},
booktitle = {3rd International Conference On Art & Technology. Technarte 2008},
year = {2008},
url = {http://www.technarte.org/}
}
|
| Molina-Solana, M., Arcos, J.L. & Gómez, E. (2008), "Learning Violinist's Expressive Trends ", In Proc. International Workshop on Machine Learning and Music (MML08), Held in conjunction with ICML/COLT/UAI 2008. Helsinki, Finland. July 09 2008., pp. 3-4. |
| Abstract: This paper presents a Trend-based model for identifying professional performers in commercial recordings. Trend-based models characterize performers by learning how melodic patterns are played. Reported results using 23 violinists show the high identification rates achieved with our model. |
BibTeX:
@inproceedings{Molina-Solana2008b,
author = {Miguel Molina-Solana and Josep~Lluis Arcos and Emilia Gómez},
title = {Learning Violinist's Expressive Trends },
booktitle = {Proc. International Workshop on Machine Learning and Music (MML08), Held in conjunction with ICML/COLT/UAI 2008},
year = {2008},
pages = {3-4},
url = {http://www.dtic.upf.edu/~rramirez/MML08/}
}
|
| Molina-Solana, M., Arcos, J.L. & Gómez, E. (2008), "Using Expressive Trends for Identifying Violin Performers", In Proc. 9th International Conference on Music Information Retrieval (ISMIR2008). Philadelphia, USA. September 14-18 2008., pp. 495-500. |
| Abstract: This paper presents a new approach for identifying professional performers in commercial recordings. We propose a Trend-based model that, analyzing the way Narmour's Implication- Realization patterns are played, is able to characterize performers. Concretely, starting from automatically extracted descriptors provided by state-of-the-art extraction tools, the system performs a mapping to a set of qualitative behavior shapes and constructs a collection of frequency distributions for each descriptor. Experiments were conducted in a data-set of violin recordings from 23 different performers. Reported results show that our approach is able to achieve high identification rates. |
BibTeX:
@inproceedings{Molina-Solana2008c,
author = {Miguel Molina-Solana and Josep~Lluis Arcos and Emilia Gómez},
title = {Using Expressive Trends for Identifying Violin Performers},
booktitle = {Proc. 9th International Conference on Music Information Retrieval (ISMIR2008)},
year = {2008},
pages = {495-500},
url = {http://ismir2008.ismir.net/}
}
|
| Berzal, F., Fajardo, W., Jiménez, A. & Molina-Solana, M. (2009), "Mining musical patterns: Identification of transposed motives", LNCS, Foundations of Intelligent Systems: 18th International Symposium, ISMIS 2009. Prague, Czech Republic, September 14-17, 2009. Vol. 5722, pp. 271-280. |
| Abstract: Automatic extraction of frequent repeated patterns in music material is an interesting problem. This paper presents an effective approach of unsupervised frequent pattern discovery method from symbolic music sources. Patterns are discovered even if they are transposed. Experiments on some songs suggest that our approach is promising, specially when dealing with songs that include non-exact repetitions. |
BibTeX:
@article{Berzal2009,
author = {Fernando Berzal and Waldo Fajardo and Aída Jiménez and Miguel Molina-Solana},
title = {Mining musical patterns: Identification of transposed motives},
journal = {LNCS, Foundations of Intelligent Systems: 18th International Symposium, ISMIS 2009},
year = {2009},
volume = {5722},
pages = {271-280},
url = {http://ismis09.vse.cz/},
doi = {http://dx.doi.org/10.1007/978-3-642-04125-9_30}
}
|
| Delgado, M., Fajardo, W. & Molina-Solana, M. (2009), "INMAMUSYS: Intelligent multiagent music system", Expert Systems with Applications. Vol. 36(3), pp. 4574-4580. |
| Abstract: Music generation is a complex task even for human beings. This paper describes a two level competitive/collaborative multiagent approach for autonomous, non-deterministic, computer music composition. Our aim is to build a high modular system that composes music on its own by using Experts Systems technology and rule-based systems principles. To do that, rules issued from musical knowledge are used and emotional inputs from the users are introduced. In fact, users are not allowed to directly control the composition process. Two main goals are sought after: investigating relationships between computers and emotions and how the latter can be represented into the former, and developing a framework for music composition that can be useful for future experiments. The system has been successfully tested by asking several people to match compositions with suggested emotions. |
BibTeX:
@article{Delgado2009a,
author = {Miguel Delgado and Waldo Fajardo and Miguel Molina-Solana},
title = {INMAMUSYS: Intelligent multiagent music system},
journal = {Expert Systems with Applications},
year = {2009},
volume = {36},
number = {3},
pages = {4574-4580},
doi = {http://dx.doi.org/10.1016/j.eswa.2008.05.028}
}
|
| Molina-Solana, M. (2009), "A Trend Based Model for Identifying Violinists", In New Trends on Intelligent Systems and Soft Computing. Granada, Spain, February, 2009. Vol. 2, pp. 143-160. Editorial Universidad de Granada. |
| Abstract: One of the most challenging problems for the Sound and Music Computing field is the understanding of the way performers use expressive resources of a given instrument to communicate with the audience. Working directly with commercial recordings is a good opportunity for tackling this implicit knowledge. Nevertheless, the huge amount of information to be analyzed suggests the use of non-supervised techniques. These techniques have to deal with imprecise analysis and to manage the information in a more broader perspective. This work presents a new approach, Trend-based modeling, for identifying professional performers in commercial recordings. Departing from information automatically extracted by state-of-the-art extraction tools, our approach performs a qualitative analysis of the detected trends for a given set of different melodic patterns. We tested our system with a dataset of violin recordings from 23 different professional performers. |
BibTeX:
@incollection{Molina-Solana2009,
author = {Miguel Molina-Solana},
title = {A Trend Based Model for Identifying Violinists},
booktitle = {New Trends on Intelligent Systems and Soft Computing},
publisher = {Editorial Universidad de Granada},
year = {2009},
volume = {2},
pages = {143-160}
}
|
| Delgado, M., Fajardo, W. & Molina-Solana, M. (2010), "Can the Machine Play Classical Music like a Human? A Survey in Computational Music Performance", In Music: Composition, Interpretation and Effects. , pp. 191-203. Nova Science Publishers. |
BibTeX:
@incollection{Delgado2010,
author = {Miguel Delgado and Waldo Fajardo and Miguel Molina-Solana},
title = {Can the Machine Play Classical Music like a Human? A Survey in Computational Music Performance},
booktitle = {Music: Composition, Interpretation and Effects},
publisher = {Nova Science Publishers},
year = {2010},
pages = {191-203},
url = {https://www.novapublishers.com/catalog/product_info.php?products_id=10903}
}
|
| Molina-Solana, M., Arcos, J.L. & Gómez, E. (2010), "Identifying Violin Performers by their Expressive Trends", Intelligent Data Analysis. Vol. 14(5), pp. 555-571. |
| Abstract: Understanding the way performers use expressive resources of a given instrument to communicate with the audience is a challenging problem in the sound and music computing field. Working directly with commercial recordings is a good opportunity for tackling this implicit knowledge and studying well-known performers. The huge amount of information to be analyzed suggests the use of automatic techniques, which have to deal with imprecise analysis and manage the information in a broader perspective. This work presents a new approach, Trend-based modeling, for identifying professional performers in commercial recordings. Concretely, starting from automatically extracted descriptors provided by state-of-the-art tools, our approach performs a qualitative analysis of the detected trends for a given set of melodic patterns. The feasibility of our approach is shown for a dataset of monophonic violin recordings from 23 well-known performers. |
BibTeX:
@article{Molina-Solana2010a,
author = {Miguel Molina-Solana and Josep~Lluis Arcos and Emilia Gómez},
title = {Identifying Violin Performers by their Expressive Trends},
journal = {Intelligent Data Analysis},
year = {2010},
volume = {14},
number = {5},
pages = {555-571},
doi = {http://dx.doi.org/10.3233/IDA-2010-0439}
}
|
| Molina-Solana, M. & Grachten, M. (2010), "Nature vs. Culture in ritardando performances", In Proc. Conference on Interdisciplinary Musicology (CIM10). Sheffield, UK. July 23-24 2010., pp. 55-61. |
| Abstract: We present in this work the two traditional visions for the role of performers in music performance. These two alternatives can be seen as a particular case of the nature versus culture debate. The first vision considers that performances are shaped by the structure of the piece, with the performer being a mere transmitter. The second one claims that performers do have a more active role, with the obligation of shaping the music according to their own will. We offer a brief review of several ideas and works, supporting both sides, about the issue. Besides this discussion, we describe our own experimentation. |
BibTeX:
@inproceedings{Molina-Solana2010b,
author = {Miguel Molina-Solana and Maarten Grachten},
title = {Nature vs. Culture in ritardando performances},
booktitle = {Proc. Conference on Interdisciplinary Musicology (CIM10)},
year = {2010},
pages = {55-61},
url = {http://www.sheffield.ac.uk/cim10/}
}
|
| Molina-Solana, M., Grachten, M. & Widmer, G. (2010), "Evidence for pianist-specific rubato style in Chopin Nocturnes", In Proc. 11th International Society for Music Information Retrieval Conference (ISMIR2010). Utrecht, Netherlands. August 9-13 2010., pp. 225-230. |
| Abstract: The performance of music usually involves a great deal of interpretation by the musician. In classical music, the final ritardando is a good example of the expressive aspect of music performance. Even though expressive timing data is expected to have a strong component that is determined by the piece itself, in this paper we investigate to what degree individual performance style has an effect on the timing of final ritardandi. The particular approach taken here uses Friberg and Sundberg's kinematic rubato model in order to characterize performed ritardandi. Using a machine-learning classifier, we carry out a pianist identification task to assess the suitability of the data for characterizing the individual playing style of pianists. The results indicate that in spite of an extremely reduced data representation, when cancelling the piece-specific aspects, pianists can often be identified with accuracy above baseline. This fact suggests the existence of a performer-specific style of playing ritardandi. |
BibTeX:
@inproceedings{Molina-Solana2010c,
author = {Miguel Molina-Solana and Maarten Grachten and Gerhard Widmer},
title = {Evidence for pianist-specific rubato style in Chopin Nocturnes},
booktitle = {Proc. 11th International Society for Music Information Retrieval Conference (ISMIR2010)},
year = {2010},
pages = {225-230},
url = {http://ismir2010.ismir.net/}
}
|
| Delgado, M., Fajardo, W. & Molina-Solana, M. (2011), "A state of the art on computational music performance", Expert Systems with Applications. Vol. 38(1), pp. 155-160. |
| Abstract: Musical expressivity can be defined as the deviation from a musical standard when a score is performed by a musician. This deviation is made in terms of intrinsic note attributes like pitch, timbre, timing and dynamics. The advances in computational power capabilities and digital sound synthesis have allowed real-time control of synthesized sounds. Expressive control becomes then an area of great interest in the sound and music computing field. Musical expressivity can be approached from different perspectives. One approach is the musicological analysis of music and the study of the different stylistic schools. This approach provides a valuable understanding about musical expressivity. Another perspective is the computational modelling of music performance by means of automatic analysis of recordings. It is known that music performance is a complex activity that involves complementary aspects from other disciplines such as psychology and acoustics. It requires creativity and eventually, some manual abilities, being a hard task even for humans. Therefore, using machines appears as a very interesting and fascinating issue. In this paper, we present an overall view of the works many researchers have done so far in the field of expressive music performance, with special attention to the computational approach. |
BibTeX:
@article{Delgado2011,
author = {Miguel Delgado and Waldo Fajardo and Miguel Molina-Solana},
title = {A state of the art on computational music performance},
journal = {Expert Systems with Applications},
year = {2011},
volume = {38},
pages = {155-160},
number = {1},
doi = {http://dx.doi.org/10.1016/j.eswa.2010.06.033}
}
|
| Jiménez, A., Molina-Solana, M., Berzal, F. & Fajardo, W. (2011), "Mining transposed motifs in music", Journal of Intelligent Information Systems. Vol. 36(1), pp. 99-115. |
| Abstract: The discovery of frequent musical patterns (motifs) is a relevant problem in musicology. This paper introduces an unsupervised algorithm to address this problem in symbolically-represented musical melodies. Our algorithm is able to identify transposed patterns including exact matchings, i.e., null transpositions. We have tested our algorithm on a corpus of songs and the results suggest that our approach is promising, specially when dealing with songs that include non-exact repetitions. |
BibTeX:
@article{Jimenez2011,
author = {Aída Jiménez and Miguel Molina-Solana and Fernando Berzal and Waldo Fajardo},
title = {Mining transposed motifs in music},
journal = {Journal of Intelligent Information Systems},
year = {2011},
volume = {36},
number = {1},
pages = {99-115},
doi = {http://dx.doi.org/10.1007/s10844-010-0122-7}
}
|
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