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Learning, Probability and Logic: Toward a Unified Approach for Content-Based Music Information Retrieval

Helene-Camille Crayencour, Carmine-Emanuele Cella
2019 Frontiers in Digital Humanities  
interrelated musical information is limited with current architectures; models are typically restricted to short-term analysis that does not account for the hierarchical temporal structure of musical  ...  In this perspective paper, we critically look at the problem of automatic chord estimation from audio recordings as a case study of content-based algorithms, and point out several bottlenecks in current  ...  Markov Logic Networks (MLNs) Markov logic networks (MLNs), introduced by Richardson and Domingos (2006) , combine first-order logic and probabilistic graphical models (Markov networks).  ... 
doi:10.3389/fdigh.2019.00006 fatcat:nsphz2frebgy5bhcybvpfcyfey

Artificial Musical Intelligence: A Survey [article]

Elad Liebman, Peter Stone
2020 arXiv   pre-print
Beginning in the late 1990s, the rise of the Internet and large scale platforms for music recommendation and retrieval have made music an increasingly prevalent domain of machine learning and artificial  ...  This article provides a definition of musical intelligence, introduces a taxonomy of its constituent components, and surveys the wide range of AI methods that can be, and have been, brought to bear in  ...  As previously mentioned, Papadopoulos and Tzanetakis applied Markov Logic Networks for modeling chord and key structure [268] .  ... 
arXiv:2006.10553v1 fatcat:2j6i27wrsfawpgcr2unxdgngd4

Social networks and statistical relational learning: a survey

Floriana Esposito, Stefano Ferilli, Teresa M.A. Basile, Nicola Di Mauro
2012 International Journal of Social Network Mining  
Statistical relational learning (SRL) is a very promising approach to SNM, since it combines expressive representation formalisms, able to model complex relational networks, with statistical methods able  ...  One of the most appreciated functionality of computers nowadays is their being a means for communication and information sharing among people.  ...  Markov logic networks This section reports an extension to the logical case of Markov networks model.  ... 
doi:10.1504/ijsnm.2012.051057 fatcat:6i7n2zrrj5geho3eh6nicay5nm

Automatic Melodic Harmonization from Symbolic Melody Using BLSTM Networks

Myrsini Ioannou, Ángel Faraldo, Frederic Font
2020 Zenodo  
(BLSTM) networks from symbolic melodies.  ...  Producing chord progressions from a melody is a challenging task for multiple rea-sons but mainly because harmonic subtleties are diÿcult to describe computation-ally.  ...  Until now, automatic melodic harmonization has been approached from two main separate perspectives [29] , in terms of harmonic analysis.  ... 
doi:10.5281/zenodo.4091500 fatcat:cfin5hxqkvejviya6zhcpwwo5q

Probabilistic Multiagent Reasoning over Annotated Amalgamated F-Logic Ontologies

Markus Schatten
2013 ISRN Artificial Intelligence  
It is shown that frame logic can be annotated and amalgamated by using this approach which gives a foundation for collective ontology development in MAS.  ...  A solution to probabilistic reasoning in such an environment by using a social network of trust is given.  ...  A different approach to a similar problem related to trust management in the Semantic Web is presented in [14] . It provides a profound model based on path algebra and inspired by Markov models.  ... 
doi:10.1155/2013/691707 fatcat:dhzidd3jgbfsvlf3qpfeg2cxzi

AI Methods in Algorithmic Composition: A Comprehensive Survey

J.D. Fernandez, F. Vico
2013 The Journal of Artificial Intelligence Research  
This survey aims to be a comprehensive account of research on algorithmic composition, presenting a thorough view of the field for researchers in Artificial Intelligence.  ...  Since the 1950s, different computational techniques related to Artificial Intelligence have been used for algorithmic composition, including grammatical representations, probabilistic methods, neural networks  ...  This study was partially supported by a grant for the MELOMICS project (IPT-300000-2010-010) from the Spanish Ministerio de Ciencia e Innovación, and a grant for the CAUCE project (TSI-090302-2011-8) from  ... 
doi:10.1613/jair.3908 fatcat:lz7tckzdg5d2zkcwjnblwrojua

Guest Editorial: Special Section on Digital Document Imaging

Robert M. Haralick
1996 Journal of Electronic Imaging (JEI)  
The first paper is on a Markov source model for printed music decoding, by Kopec, Chou, and Maltz.  ...  In the paper, a Markov source model is described for a subset of music notation that was developed as an extended example of the document image decoding (DID) approach to document image analysis.  ... 
doi:10.1117/12.256543 fatcat:avqoprlkdncmdjl3rvgnafuiu4

Reasoning with Deep Learning: an Open Challenge

Marco Lippi
2016 International Conference of the Italian Association for Artificial Intelligence  
neuroscience, psychology, linguistic, and logic.  ...  The recent breakthrough achieved by deep learning methods in a variety of AI-related domains has opened novel research lines attempting to solve this complex and challenging task.  ...  An example is given by ground-specific Markov logic networks [14] , that allow to embed neural networks within the Markov logic framework, by learning the weights of the probabilistic logic clauses.  ... 
dblp:conf/aiia/Lippi16 fatcat:bygkeanwrnhnrp645eqtd5vx3m

Computational Creativity and Music Generation Systems: An Introduction to the State of the Art

Filippo Carnovalini, Antonio Rodà
2020 Frontiers in Artificial Intelligence  
Computational Creativity is a multidisciplinary field that tries to obtain creative behaviors from computers.  ...  With this survey, we try to give a complete introduction to those who wish to explore Computational Creativity and Music Generation.  ...  Nonetheless, there is also room for standard feed-forward networks: Lewis (1991) trained a network with musical patterns ranging from random to wellconstructed, to learn a measure of "musicality" that  ... 
doi:10.3389/frai.2020.00014 pmid:33733133 pmcid:PMC7861321 fatcat:yiolnpw4cndinfj54cj4zqpq5q

Generation of Two-Voice Imitative Counterpoint from Statistical Models

Victor Padilla, Darrell Conklin
2018 International Journal of Interactive Multimedia and Artificial Intelligence  
by Conklin [2] - [5] , from the horizontal and vertical perspective.  ...  Markov Model For constructing the Markov model, two voices are selected and cut into slices (see Fig. 6 ).  ... 
doi:10.9781/ijimai.2018.10.002 fatcat:zy6zli6xw5cv7ibklff42m2xxa

Using Machine Learning Algorithm to Describe the Connection between the Types and Characteristics of Music Signal

Bo Sun, Wei Wang
2021 Complexity  
Experiments were designed for these two models to verify the applicability of the model for music classification.  ...  In order to improve the accuracy of music classification, a music classification model based on multifeature fusion and machine learning algorithm is proposed.  ...  model for hidden Markov models.  ... 
doi:10.1155/2021/5577486 fatcat:qx3gkgcznjegfmnuzyd6lnkooy

Statistical Generation Of Two-Voice Florid Counterpoint

Víctor Padilla Martin-Caro, Darrell Conklin
2016 Proceedings of the SMC Conferences  
Acknowledgments This research is supported by the project Lrn2Cre8 which is funded by the Future and Emerging Technologies (FET) programme within the Seventh Framework Programme for Research of the European  ...  APPLYING THE MODEL TO THE TEMPLATE This section explains a method for generating new music based on a piece from the corpus.  ...  Markov model For constructing the Markov model, two voices are selected and cut into slices (see Figure 5 ).  ... 
doi:10.5281/zenodo.851286 fatcat:5rc6nshu7zff5lwsmt3xpsgtzm

Algorithmic interactive music generation in videogames

Alvaro E. Lopez Duarte
2020 SoundEffects  
Starting with music generation, I examine conceptual implementations and technical challenges of algorithmic composition studies that use Markov models, a-life/evolutionary music, generative grammars,  ...  For each model, I evaluate rule-based strategies for interactive music transformation using parameters provided by contextual gameplay situations.  ...  The recurrent model (RNN) learns from sequential patterns through time, which makes it a good fit for music.  ... 
doi:10.7146/se.v9i1.118245 fatcat:yoqonmlm5ncvdgxb2obg7iejwm

Music and Mathematics in Latin America: Major Developments in the Last 25 Years

Gabriel Pareyon, Carlos Almada, Carlos Mathias, Cecília Saraiva, Daniel Moreira, Hugo Carvalho, Liduino Pitombeira, Pauxy Gentil-Nunes, Bruno Mesz, Pablo Amster, Pablo Riera
2022 MusMat: Brazilian Journal of Music and Mathematics  
This text is an overview for Latin America across the field of music and musicology intersecting mathematics, including the advances from perspectives of experimentation, creation, analysis and pedagogy  ...  Our main goal is to spread worldwide the richness and variety of research on music and mathematics in Latin America as well as stimulate further investigation in this fascinating intersection.  ...  Cabezas-Hernández [190] , is also a distinguished Salvadorean scholar making part of a new generation of Central American specialists interested on topics connecting music, mathematics and computer science  ... 
doi:10.46926/musmat.2022v6n1.12-47 fatcat:4fb7zvw7hjhm3dana4wolkoxmq

On Improvised Music, Computational Creativity and Human-Becoming

Arto Artinian, Adam James Wilson
2017 Leonardo Music Journal  
Escaping musical systems of historical memory, calibrating new musical materials for congruity with the present-an act of human-becoming-can nonetheless be achieved by integrating computational creativity  ...  In other words, the formation of the self is not a "natural" condition, an outcome of evolution, or some hard-wired, rational kernel that propels the development of a person from the helplessness of infant  ...  There are many tools for this, including hidden Markov models, probabilistic automata and neural networks [33] .  ... 
doi:10.1162/lmj_a_01006 fatcat:skxw3zapbbhxrmcyayveusel4u
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