Music Mood Player Implementation Applied in Daycare Using Self Organizing Map Method

. Music is an art, entertainment and human activity that involve some organized sounds. Music is closely related to human psychology. A piece of music often associated with certain adjectives such as happy, sad, romantic and many more. The linkage between the music with a certain mood has been widely used in various occasions by people, there for music classification based on relevance to a particular emotion is important. Daycare is one example of an institution that used music as therapy or tools of support in each of its parenting activities. This research concerns in implementation of a music mood player using Self Organizing Map applied at the Daycare. The features that are used on this music mood player are rhythm patterns of the music. The mood parameters that used in this system is based on Robert Thayer\u27s energy-stress model which are exuberance / happy, contentment / relax, anxious and depression. The system is tested using a set of songs with various genres and the classification results are compared with the mood obtained by child psychology expert. The system can be set automatically according to the activities at daycare.

Unsupervised automatic music genre classification

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia InformáticaIn this study we explore automatic music genre recognition and classification of digital music. Music has always been a reflection of culture di erences and an influence in our society. Today’s digital content development triggered the massive use of digital music. Nowadays,digital music is manually labeled without following a universal taxonomy, thus, the labeling process to audio indexing is prone to errors. A human labeling will always be influenced by culture di erences, education, tastes, etc. Nonetheless, this indexing process is primordial to guarantee a correct organization of huge databases that contain thousands of music titles. In this study, our interest is about music genre organization. We propose a learning and classification methodology for automatic genre classification able to group several music samples based on their characteristics (this is achieved by the proposed learning process) as well as classify a new test music into the previously learned created groups(this is achieved by the proposed classification process). The learning method intends to group the music samples into di erent clusters only based on audio features and without any previous knowledge on the genre of the samples, and therefore it follows an unsupervised methodology. In addition a Model-Based approach is followed to generate clusters as we do not provide any information about the number of genres in the dataset. Features are related with rhythm analysis, timbre, melody, among others. In addition, Mahalanobis distance was used so that the classification method can deal with non-spherical clusters. The proposed learning method achieves a clustering accuracy of 55% when the dataset contains 11 di erent music genres: Blues, Classical, Country, Disco, Fado, Hiphop, Jazz, Metal,Pop, Reggae and Rock. The clustering accuracy improves significantly when the number of genres is reduced; with 4 genres (Classical, Fado, Metal and Reggae), we obtain an accuracy of 100%. As for the classification process, 82% of the submitted music samples were correctly classified

Backwards is the way forward: feedback in the cortical hierarchy predicts the expected future

Clark offers a powerful description of the brain as a prediction machine, which offers progress on two distinct levels. First, on an abstract conceptual level, it provides a unifying framework for perception, action, and cognition (including subdivisions such as attention, expectation, and imagination). Second, hierarchical prediction offers progress on a concrete descriptive level for testing and constraining conceptual elements and mechanisms of predictive coding models (estimation of predictions, prediction errors, and internal models)

User-centric Music Information Retrieval

The rapid growth of the Internet and the advancements of the Web technologies have made it possible for users to have access to large amounts of on-line music data, including music acoustic signals, lyrics, style/mood labels, and user-assigned tags. The progress has made music listening more fun, but has raised an issue of how to organize this data, and more generally, how computer programs can assist users in their music experience. An important subject in computer-aided music listening is music retrieval, i.e., the issue of efficiently helping users in locating the music they are looking for. Traditionally, songs were organized in a hierarchical structure such as genre-\u3eartist-\u3ealbum-\u3etrack, to facilitate the users’ navigation. However, the intentions of the users are often hard to be captured in such a simply organized structure. The users may want to listen to music of a particular mood, style or topic; and/or any songs similar to some given music samples. This motivated us to work on user-centric music retrieval system to improve users’ satisfaction with the system. The traditional music information retrieval research was mainly concerned with classification, clustering, identification, and similarity search of acoustic data of music by way of feature extraction algorithms and machine learning techniques. More recently the music information retrieval research has focused on utilizing other types of data, such as lyrics, user access patterns, and user-defined tags, and on targeting non-genre categories for classification, such as mood labels and styles. This dissertation focused on investigating and developing effective data mining techniques for (1) organizing and annotating music data with styles, moods and user-assigned tags; (2) performing effective analysis of music data with features from diverse information sources; and (3) recommending music songs to the users utilizing both content features and user access patterns

The Ephemeral City : Songs for the Ghost Quarters

The towers of the Stockholm skyline twine with radio transmissions, flying out over the city, drifting down through the streets and sinking into the underground telephone system below. Stockholm has buildings that have been there for centuries, but is also full of modern and contemporary architectures, all jostling for their place in parallel collective memory. In taking the city up as a subject, this artistic PhD project in music expands allegories to these architectural instruments into the world of the mechanical and the electrical. By taking up and transforming the materials of the cityscape, this project spins ephemeral cities more subtle than the colossal forces transforming the cityscape. The aim is to empower urban dwellers with another kind of ownership of their city.The materials in the project are drawn around themes of urban memory and transformation, psychogeography and the ghosts of the imagined city. There are three questions the artistic works of this project reflect on and address. The first is about the ability of city-dwellers to regain or create some sense of place, history or belonging through the power of their imaginations. The second reflects on the possibility for imagined alternatives to re-empower a sense of place for the people who encounter them. The third seeks out the points where stories, memories, or alternative futures are collective, at what point are they wholly individual, and how the interplay between them plays out in listening.There is an improvisatory practice in how we relate to urban environments: an ever-transforming inter-play between the animate and inanimate. Each individual draws phantoms of memory and imagination onto the cityscape, and this yields subtle ways people can be empowered in their surroundings. The artistic works of this project are made to illuminate those subtleties, centering around a group of compositions, improvisations, artistic collaborations and sound installations in music and sound, utilizing modular synthesizers, field recordings, pipe organs, multi-channel settings; PureData and SuperCollider programs, string ensembles with hurdy-gurdy and nyckelharpa or violin, and sound installations. This choice of instruments is as an allegory to the architecture of Stockholm. The final result is a collection of music and sound works, made to illuminate the imagined city. Taken as a whole, the works of the project create an imaginary city–The Ephemeral City–in order to argue that this evocation of ephemeral space is a way to empower urban dwellers through force of imagination, immune to the vast forces tearing through the fabric of Stockholm life by virtue of the ghostly, transitory and mercurial, as compelling to the inner eye as brick and mortar to the outer life

Choreographing the extended agent : performance graphics for dance theater

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2005.Includes bibliographical references (v. 2, leaves 448-458).The marriage of dance and interactive image has been a persistent dream over the past decades, but reality has fallen far short of potential for both technical and conceptual reasons. This thesis proposes a new approach to the problem and lays out the theoretical, technical and aesthetic framework for the innovative art form of digitally augmented human movement. I will use as example works a series of installations, digital projections and compositions each of which contains a choreographic component - either through collaboration with a choreographer directly or by the creation of artworks that automatically organize and understand purely virtual movement. These works lead up to two unprecedented collaborations with two of the greatest choreographers working today; new pieces that combine dance and interactive projected light using real-time motion capture live on stage. The existing field of"dance technology" is one with many problems. This is a domain with many practitioners, few techniques and almost no theory; a field that is generating "experimental" productions with every passing week, has literally hundreds of citable pieces and no canonical works; a field that is oddly disconnected from modern dance's history, pulled between the practical realities of the body and those of computer art, and has no influence on the prevailing digital art paradigms that it consumes.(cont.) This thesis will seek to address each of these problems: by providing techniques and a basis for "practical theory"; by building artworks with resources and people that have never previously been brought together, in theaters and in front of audiences previously inaccessible to the field; and by proving through demonstration that a profitable and important dialogue between digital art and the pioneers of modern dance can in fact occur. The methodological perspective of this thesis is that of biologically inspired, agent-based artificial intelligence, taken to a high degree of technical depth. The representations, algorithms and techniques behind such agent architectures are extended and pushed into new territory for both interactive art and artificial intelligence. In particular, this thesis ill focus on the control structures and the rendering of the extended agents' bodies, the tools for creating complex agent-based artworks in intense collaborative situations, and the creation of agent structures that can span live image and interactive sound production. Each of these parts becomes an element of what it means to "choreograph" an extended agent for live performance.Marc Downie.Ph.D