945 resultados para Music Recommender Systems


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Listeners experience electroacoustic music as full of significance and meaning, and they experience spatiality as one of the factors contributing to its meaningfulness. If we want to understand spatiality in electroacoustic music, we must understand how the listener’s mental processes give rise to the experience of meaning. In electroacoustic music as in everyday life, these mental processes unite the peripheral auditory system with human spatial cognition. In the discussion that follows we consider a range of the listener’s mental processes relating space and meaning from the perceptual attributes of spatial imagery to the spatial reference frames for places and navigation. When considering multichannel loudspeaker systems in particular, an important part of the discussion is focused on the distinctive and idiomatic ways in which this particular mode of sound production contributes to and situates meaning. These idiosyncrasies include the phenomenon of image dispersion, the important consequences of the precedence effect and the influence of source characteristics on spatial imagery. These are discussed in close relation to the practicalities of artistic practice and to the potential for artistic meaning experienced by the listener.

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Nonlinear interactions take place in most systems that arise in music acoustics, usually as a result of player-instrument coupling. Several time-stepping methods exist for the numerical simulation of such systems. These methods generally involve the discretization of the Newtonian description of the system. However, it is not always possible to prove the stability of the resulting algorithms, especially when dealing with systems where the underlying force is a non-analytic function of the phase space variables. On the other hand, if the discretization is carried out on the Hamiltonian description of the system, it is possible to prove the stability of the derived numerical schemes. This Hamiltonian approach is applied to a series of test models of single or multiple nonlinear collisions and the energetic properties of the derived schemes are discussed. After establishing that the schemes respect the principle of conservation of energy, a nonlinear single-reed model is formulated and coupled to a digital bore, in order to synthesize clarinet-like sounds.

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Tese de doutoramento, Informática (Engenharia Informática), Universidade de Lisboa, Faculdade de Ciências, 2015

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Depuis l’avènement des formats de compression numérique et des services d’échange point à point (Peer-to-Peer) comme Napster, l’industrie du disque est en émoi. Plus fondamentalement, il y a lieu de se questionner sur ce qui apparaît comme une crise d’efficacité du droit d’auteur. Si les copistes semblent avoir pris de court de puissants intérêts, les contre-mesures ne sauraient tarder à venir. L’apparition de protections techniques ­ Trusted Systems ­ présage une ère de contrôle total par les titulaires de droits. L’«hyper efficacité» bouleversera le rapport à l’œuvre, entraînant du même souffle un déséquilibre dans les dimensions privée et publique du droit d’auteur.

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The system described herein represents the first example of a recommender system in digital ecosystems where agents negotiate services on behalf of small companies. The small companies compete not only with price or quality, but with a wider service-by-service composition by subcontracting with other companies. The final result of these offerings depends on negotiations at the scale of millions of small companies. This scale requires new platforms for supporting digital business ecosystems, as well as related services like open-id, trust management, monitors and recommenders. This is done in the Open Negotiation Environment (ONE), which is an open-source platform that allows agents, on behalf of small companies, to negotiate and use the ecosystem services, and enables the development of new agent technologies. The methods and tools of cyber engineering are necessary to build up Open Negotiation Environments that are stable, a basic condition for predictable business and reliable business environments. Aiming to build stable digital business ecosystems by means of improved collective intelligence, we introduce a model of negotiation style dynamics from the point of view of computational ecology. This model inspires an ecosystem monitor as well as a novel negotiation style recommender. The ecosystem monitor provides hints to the negotiation style recommender to achieve greater stability of an open negotiation environment in a digital business ecosystem. The greater stability provides the small companies with higher predictability, and therefore better business results. The negotiation style recommender is implemented with a simulated annealing algorithm at a constant temperature, and its impact is shown by applying it to a real case of an open negotiation environment populated by Italian companies

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La monografía presenta la auto-organización sociopolítica como la mejor manera de lograr patrones organizados en los sistemas sociales humanos, dada su naturaleza compleja y la imposibilidad de las tareas computacionales de los regímenes políticos clásico, debido a que operan con control jerárquico, el cual ha demostrado no ser óptimo en la producción de orden en los sistemas sociales humanos. En la monografía se extrapola la teoría de la auto-organización en los sistemas biológicos a las dinámicas sociopolíticas humanas, buscando maneras óptimas de organizarlas, y se afirma que redes complejas anárquicas son la estructura emergente de la auto-organización sociopolítica.

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Many discussions about the music processing have occurred over the years. It is stated, on one hand, the existence of a single joint for grasping the music or any of its attributes by the Central Nervous System. Furthermore, it is claimed also the existence of multiple and diverse systems to understand each aspect of music. In general, model-independent set, studies focusing on the processing of sound components, specifically the musical tones, can significantly clarify the basic functioning of the auditory system and other higher brain functions. In this sense, one of the most prominent approaches in the study of sensory and perceptual processes of hearing, or changed unharmed, has been Neuroscience, which is interested in the interaction between the brain areas corresponding to different cognitive processes. Thus, the purpose of this study was to review the studies that dealt processing models of the attributes of tonal Western music, based on the conception that neuropsychological neural structures are interdependent sensory pathways.

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Very large scale scheduling and planning tasks cannot be effectively addressed by fully automated schedule optimisation systems, since many key factors which govern 'fitness' in such cases are unformalisable. This raises the question of an interactive (or collaborative) approach, where fitness is assigned by the expert user. Though well-researched in the domains of interactively evolved art and music, this method is as yet rarely used in logistics. This paper concerns a difficulty shared by all interactive evolutionary systems (IESs), but especially those used for logistics or design problems. The difficulty is that objective evaluation of IESs is severely hampered by the need for expert humans in the loop. This makes it effectively impossible to, for example, determine with statistical confidence any ranking among a decent number of configurations for the parameters and strategy choices. We make headway into this difficulty with an Automated Tester (AT) for such systems. The AT replaces the human in experiments, and has parameters controlling its decision-making accuracy (modelling human error) and a built-in notion of a target solution which may typically be at odds with the solution which is optimal in terms of formalisable fitness. Using the AT, plausible evaluations of alternative designs for the IES can be done, allowing for (and examining the effects of) different levels of user error. We describe such an AT for evaluating an IES for very large scale planning.

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Computer music usually sounds mechanical; hence, if musicality and music expression of virtual actors could be enhanced according to the user’s mood, the quality of experience would be amplified. We present a solution that is based on improvisation using cognitive models, case based reasoning (CBR) and fuzzy values acting on close-to-affect-target musical notes as retrieved from CBR per context. It modifies music pieces according to the interpretation of the user’s emotive state as computed by the emotive input acquisition componential of the CALLAS framework. The CALLAS framework incorporates the Pleasure-Arousal-Dominance (PAD) model that reflects emotive state of the user and represents the criteria for the music affectivisation process. Using combinations of positive and negative states for affective dynamics, the octants of temperament space as specified by this model are stored as base reference emotive states in the case repository, each case including a configurable mapping of affectivisation parameters. Suitable previous cases are selected and retrieved by the CBR subsystem to compute solutions for new cases, affect values from which control the music synthesis process allowing for a level of interactivity that makes way for an interesting environment to experiment and learn about expression in music.

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There has been a significant amount of work implementing systems for algorithmic composition with the intention of targeting specific emotional responses in the listener, but a full review of this work is not currently available. This gap creates a shared obstacle to those entering the field. Our aim is thus to give an overview of progress in the area of these affectively driven systems for algorithmic composition. Performative and transformative systems are included and differentiated where appropriate, highlighting the challenges these systems now face if they are to be adapted to, or have already incorporated, some form of affective control. Possible real-time applications for such systems, utilizing affectively driven algorithmic composition and biophysical sensing to monitor and induce affective states in the listener are suggested.

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This thesis describes all process of the development of music visualization, starting with the implementation, followed by realization and then evaluation. The main goal is to have to knowledge of how the audience live performance experience can be enhanced through music visualization. With music visualization is possible to give a better understanding about the music feelings constructing an intensive atmosphere in the live music performance, which enhances the connection between the live music and the audience through visuals. These visuals have to be related to the live music, furthermore has to quickly respond to live music changes and introduce novelty into the visuals. The mapping between music and visuals is the focus of this project, in order to improve the relationship between the live performance and the spectators. The implementation of music visualization is based on the translation of music into graphic visualizations, therefore at the beginning the project was based on the existent works. Later on, it was decided to introduce new ways of conveying music into visuals. Several attempts were made in order to discover the most efficient mapping between music and visualization so people can fully connect with the performance. Throughout this project, those attempts resulted in several music visualizations created for four live music performances, afterwards it was produced an online survey to evaluate those live performances with music visualization. In the end, all conclusions are presented based on the results of the online survey, and also is explained which music elements should be depicted in the visuals, plus how those visuals should respond to the selected music elements.

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Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores which uses only music notation to determine the author. The steps of the proposed system are the following. First of all, the music sheet is preprocessed for obtaining a music score without the staff lines. Afterwards, four different methods for generating texture images from music symbols are applied. Every approach uses a different spatial variation when combining the music symbols to generate the textures. Finally, Gabor filters and Grey-scale Co-ocurrence matrices are used to obtain the features. The classification is performed using a k-NN classifier based on Euclidean distance. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving encouraging identification rates.

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Content providers from the music industry argue that peer-to-peer (P2P) networks such as KaZaA, Morpheus, iMesh, or Audiogalaxy are an enormous threat to their business. They furthermore blame these networks for their recent decline in sales figures. For this reason, an empirical investigation was conducted during a period of 6 weeks on one of the most popular files-sharing systems, in order to determine the quantity and quality of pirated music songs shared. We present empirical evidence as to what extent and in which quality music songs are being shared. A number of hypotheses are outlined and were tested. We studied, among other things, the number of users online and the number of flies accessible on such networks, the free riding problem, and the duration per search request. We further tested to see if there are any differences in the accessibility of songs based on the nationality of the artist, the language of the song, and the corresponding chart position. Finally, we outline the main hurdles users may face when downloading illegal music and the probability of obtaining high quality music tracks on such peer-to-peer networks.

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This paper describes a recommender system for sport videos, transmitted over the Internet and/or broadcast, in the context of large-scale events, which has been tested for the Olympic Games. The recommender is based on audiovisual consumption and does not depend on the number of users, running only on the client side. This avoids the concurrence, computation and privacy problems of central server approaches in scenarios with a large number of users, such as the Olympic Games. The system has been designed to take advantage of the information available in the videos, which is used along with the implicit information of the user and the modeling of his/her audiovisual content consumption. The system is thus transparent to the user, who does not need to take any specific action. Another important characteristic is that the system can produce recommendations for both live and recorded events. Testing has showed advantages compared to previous systems, as will be shown in the results.