SammanfattningZavgorodni, Nikolai (2008). Titel: Rock- och popmusik i undervisningen. En studie om betydelsen av musicerande på gymnasiets estetiska program (Rock and pop music in music education. Investigating the importance of music creation in high school’s aesthetic program).Syfte med denna studie är att undersöka vilken betydelse musicerandet har i elevernas musikaliska utveckling. Studien omfattar musikundervisning i gymnasieskolan. Jag har använt mig av kvantitativ metod i min studie. Den kvantitativa metoden var i form av enkätundersökningen. Resultatet visar att musicerandet har en stor betydelse för musikstuderande och rock- och popmusik har en hög status i undervisningen. Majoriteten av alla studerande anser att det är viktigt att man ska satsa mer på musicerandet än på teori på lektionerna. Det framgick även av enkätstudien att det är mycket viktig med genrebredd i musikundervisningen. Många musikstuderande i studien anser att rock och popmusikgenrer har en stor betydelse i musikundervisningen. En viktig aspekt är att läraren ska engagera sig i elevernas musikaliska utveckling. Sökord: genre, ensemble, musikundervisning, musicerandet. / Abstract Title: Rock and popmusic in education. A study on the importance of rock and popmusic playing in music education. The aim of this study is to find out what music students think about playing in music lesson and their reflections on the importance of genre in music education. The study covers music education in high school. I have used both of quanititative and qualititative methods in my study. The quantitative method vas in the form of queststionnaires and qualitative method in the form of my observations above all in the form of definitions, conceptions and theoretical constructions. The result shows that play the instuments is very important for students and rock and popmusic have a high status in music education. The majority of students prefer more to play the instruments than their have theory in the lesson. The most of music students in high school believ that rock and popmusic is very important things in music education. One importans aspect is that teacher’s commitment to the students musical development. Keywords: genre, ensemble, music education, play the instruments.

Annotation: My graduation work deals with the usage of a traditional song as a genre at primary school. The aim was to bring a traditional song closer to children using genre and find out whether they can also feel and appreciate different kinds of genre work than the media provide them . I also tried to find out what kind of music children like and according to this information I tried to make my own interpretation. As the method of research I chose an observation and an interview which I did in the school club and in the centre for children and youth in Jindřichův Hradec. As a result I found out that children are able to accept different kinds of music than media and they like learning folk songs of various genres during their own participation in a music activity.

SammanfattningNikolai Zavgorodni (2008)Titel: Rock- och popmusik i undervisningen.Syfte med denna studie är att undersöka vilken betydelse har musicerandet i elevernas musikaliska utveckling. Studien omfattar musikundervisningen i gymnasieskolan. Jag har använt mig av både kvantitativ och kvalitativ metoder i min studie. Den kvantitativa metoden var i form av enkätundersökningen och kvalitativa metoden i form av observationer men framförallt i form av definitioner, konceptioner och teoretiska konstruktioner. Resultatet visar att musicerandet har en stor betydelse för musikstuderande och rock- och popmusik har en hög status i undervisningen. Majoriteten av alla studerande anser att det är viktigt att man ska satsa mer på musicerandet än på teori på lektionerna. Det framgick även av enkätstudien att det är mycket viktig med genrebredd i musikundervisningen. Många musikstuderande i studien anser att rock och popmusikgenrer har en stor betydelse i musikundervisningen. En viktig aspekt är att läraren ska engagera sig i elevernas musikaliska utveckling. Sökord: genre, ensemble, musikundervisning, musicerandet. / Abstract Nikolai Zavgorodni (2008)Title: Rock and popmusic in education. A study on the importance of rock and popmusic playing in music education. The aim of this study is to find out what music students think about playing in music lesson and their reflections on the importance of genre in music education. The study covers music education in high school. I have used both of quanititative and qualititative methods in my study. The quantitative method vas in the form of queststionnaires and qualitative method in the form of my observations above all in the form of definitions, conceptions and theoretical constructions. The result shows that play the instuments is very important for students and rock and popmusic have a high status in music education. The majority of students prefer more to play the instruments than their have theory in the lesson. The most of music students in high school believ that rock and popmusic is very important things in music education. One importans aspect is that teacher’s commitment to the students musical development. Keywords: genre, ensemble, music education, play the instruments.

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This diploma work deals with music genre recognition using the techniques of Music Information Retrieval. It contains a brief description of the principle of this research area and its subfield called Music Genre Recognition. The following chapter includes selection of the most suitable parameters for describing music genres. This work further characterizes machine learning methods used in this field of research. The next chapter deals with the descriptions of music datasets created for genre classification studies. Subsequently, there is a draft and evaluation of the system for music genre recognition. The last part of this work describes the results of partial parameter analysis, dependence of genre classification accuracy on the amount of parameters and contains a discussion on the causes of classification accurancy for the individual genres.

Syftet med studien är att undersöka hur pedagoger som undervisar i akustisk, nylonsträngad gitarr inom musik-och kulturskolan förhåller sig till musikgenrer i undervisningsinnehållet. Detta har studerats med avseende på hur repertoaren väljs genremässigt och vad som har inverkan på detta. Datainsamlingen har gjorts med utgångspunkt från kvalitativa intervjuer med tre gitarrpedagoger. Resultaten visar att genrebredd präglar undervisningen. En viktig aspekt av detta ur pedagogens perspektiv är att visa på gitarrens bredd och möjligheter. Ur ett elevperspektiv ges möjligheter till inflytande över undervisningsinnehållet. Studien visar att förutsättningarna för gitarrundervisning har förändrats över tid i takt med IT-utvecklingen och elevernas allt större musikaliska medvetenhet. Studien pekar på att pedagogerna måste förhålla sig till såväl tradition, samtid som elevinflytande i valet av undervisningsinnehåll med avseende på genrer.

This thesis explores the ideas of feature learning and sparse coding for Music Information Retrieval (MIR). Sparse coding is an algorithm which aims to learn new feature representations from data automatically. In contrast to previous work which uses sparse coding in an MIR context the concept of supervised sparse coding is also investigated, which makes use of the ground-truth labels explicitly during the learning process. Here sparse coding and supervised coding are applied to two MIR problems: classification of musical genre and recognition of the emotional content of music. A variation of Label Consistent K-SVD is used to add supervision during the dictionary learning process. In the case of Music Genre Recognition (MGR) an additional discriminative term is added to encourage tracks from the same genre to have similar sparse codes. For Music Emotion Recognition (MER) a linear regression term is added to learn an optimal classifier and dictionary pair. These results indicate that while sparse coding performs well for MGR, the additional supervision fails to improve the performance. In the case of MER, supervised coding significantly outperforms both standard sparse coding and commonly used designed features, namely MFCC and pitch chroma.

Nowadays, outlier detection has attracted growing interest. Unlike typical outlier detection problems, relational outlier detection focuses on detecting abnormal patterns in datasets that contain relational implications within each data point. Furthermore, different from the traditional outlier detection that focuses on only numerical data, modern outlier detection models must be able to handle data in various types and structures. Detecting relational outliers should consider (1) Dependencies among different data types, (2) Data types that are not continuous or do not have ordinal characteristics, such as binary, categorical or multi-label, and (3) Special structures in the data. This thesis focuses on the development of relational outlier detection methods and real-world applications in datasets that contain non-numerical, mixed-type, and special structure data in three tasks, namely (1) outlier detection in mixed-type data, (2) categorical outlier detection in music genre data, and (3) outlier detection in categorized time series data. For the first task, existing solutions for mixed-type data mostly focus on computational efficiency, and their strategies are mostly heuristic driven, lacking a statistical foundation. The proposed contributions of our work include: (1) Constructing a novel unsupervised framework based on a robust generalized linear model (GLM), (2) Developing a model that is capable of capturing large variances of outliers and dependencies among mixed-type observations, and designing an approach for approximating the analytically intractable Bayesian inference, and (3) Conducting extensive experiments to validate effectiveness and efficiency. For the second task, we extended and applied the modeling strategy to a real-world problem. The existing solutions to the specific task are mostly supervised, and the traditional outlier detection methods only focus on detecting outliers by the data distributions, ignoring the input-output relation between the genres and the extracted features. The proposed contributions of our work for this task include: (1) Proposing an unsupervised outlier detection framework for music genre data, (2) Extending the GLM based model in the first task to handle categorical responses and developing an approach to approximate the analytically intractable Bayesian inference, and (3) Conducting experiments to demonstrate that the proposed method outperforms the benchmark methods. For the third task, we focused on improving the outlier detection performance in the second task by proposing a novel framework and expanded the research scope to general categorized time-series data. Existing studies have suggested a large number of methods for automatic time series classification. However, there is a lack of research focusing on detecting outliers from manually categorized time series. The proposed contributions of our work for this task include: (1) Proposing a novel semi-supervised robust outlier detection framework for categorized time-series datasets, (2) Further extending the new framework to an active learning system that takes user insights into account, and (3) Conducting a comprehensive set of experiments to demonstrate the performance of the proposed method in real-world applications. / Doctor of Philosophy / In recent years, outlier detection has been one of the most important topics in the data mining and machine learning research domain. Unlike typical outlier detection problems, relational outlier detection focuses on detecting abnormal patterns in datasets that contain relational implications within each data point. Detecting relational outliers should consider (1) Dependencies among different data types, (2) Data types that are not continuous or do not have ordinal characteristics, such as binary, categorical or multi-label, and (3) Special structures in the data. This thesis focuses on the development of relational outlier detection methods and real-world applications in datasets that contain non-numerical, mixed-type, and special structure data in three tasks, namely (1) outlier detection in mixed-type data, (2) categorical outlier detection in music genre data, and (3) outlier detection in categorized time series data. The first task aims on constructing a novel unsupervised framework, developing a model that is capable of capturing the normal pattern and the effects, and designing an approach for model fitting. In the second task, we further extended and applied the modeling strategy to a real-world problem in the music technology domain. For the third task, we expanded the research scope from the previous task to general categorized time-series data, and focused on improving the outlier detection performance by proposing a novel semi-supervised framework.

Cette thèse de sociologie porte sur les salles de musique dite « vivante », en s’appuyant sur une comparaison entre Paris et Berlin. L’étude des salles de musique rend compte de la production des définitions et des hiérarchies sociales des territoires musicaux, urbains et professionnels. À la diversité des genres musicaux qui y sont programmés répond la variété des manières de les entendre : publics assis ou debout, configurations intimistes ou stades, etc. L’articulation entre approche ethnographique et analyse statistique témoigne du lien entre esthétiques et usages sociaux de la musique. Ces territoires musicaux, constitués par les cadres d’écoute et les esthétiques, sont inégalement reconnus par les politiques culturelles et ne recoupent pas strictement les frontières des genres. Par ailleurs, les sous-champs musicaux dans les deux villes sont structurés par des logiques spatiales, ce qu’éclaire la cartographie des lieux de musique. Et, si la localisation des salles influe sur leur qualification musicale, à l’inverse, le fait musical participe aux transformations des représentations des territoires urbains. Outre l’ancrage géographique, cette thèse s’intéresse de près à la construction d’une offre musicale à travers la sélection des artistes par les programmateurs et programmatrices des salles berlinoises et parisiennes. Ainsi, elle donne à voir la délimitation de la fonction de programmation comme territoire professionnel, en interrogeant sa variabilité selon l’histoire du sous-champ musical et les contraintes liées à la concentration économique du secteur de la musique live. Une série d’entretiens avec les programmateurs et programmatrices a permis la comparaison des pratiques et des trajectoires de ces intermédiaires. Celle-ci atteste d’un développement professionnel inégal à Paris et Berlin et d’usages distincts du désintéressement dans une activité de programmation internationalisée. Les intermédiaires, comme les politiques culturelles, participent aux oppositions au sein du sous-champ des salles de musique, qui reflètent les centres et les périphéries du champ musical transnational. En effet, selon leur position dans le sous-champ et leurs ressources, les salles ne programment pas les mêmes catégories d’artistes. Ainsi, la retraduction locale de la valeur musicale contribue ainsi au positionnement de Paris et de Berlin comme capitales culturelles. / This thesis in sociology offers a comparison of music venues in Paris and Berlin. Studying music venues sheds light on the definitions and hierarchisation of musical, urban and professional territories. Diverse music genres are listened to in these venues, and ethnographic observation shows that events happen in many different configurations – audiences are sometimes seated or standing, in large arenas or intimate atmospheres, etc. Statistical methods enable the study of the connection between music styles and the way they are socially appropriated. These musical territories, unequally supported by cultural policies, distinguish themselves from the strict definition of musical genres. The musical subfield is also structured by spatial forces, revealed by the cartography of the music venues in both cities. Their localisation affects the way venues are perceived and defined but, conversely, the music scene also participates in the transformation of representations about the urban territories. Beyond the urban analysis of music, this thesis examines music production through the role of bookers, who select the artists in the venues. In Paris and Berlin, the definition of booking as a territory of competence depends on the musical subfield’s history and is influenced by pressure linked to the increasing economic concentration within the live music market. Interviews with bookers offer material for comparing the cultural intermediaries’ work practices and social trajectories. They illustrate different forms of professional development and uses of disinterestedness in the internationalised activity of booking. Cultural intermediaries and policies participate in the dual structure of the subfields, which reflects the centres and peripheries of the transnational musical field. Indeed, depending on their resources and position in these subfields, venues do not book the same type of artists. Thus, they tend to the local translation of musical value, all the while taking part in Paris’ and Berlin’s positioning as cultural capitals. / Die Dissertation behandelt in vergleichender Perspektive „lebendige” Musik in Berlin und Paris. Musik wird hierbei als kulturelle Praxis in Form von Konzerten definiert, stellt die Orte an denen Musik stattfindet ins Zentrum und schließt daher das bloße Musikhören aus. Die Studie bezieht in diesem Rahmen beruflich-professionelle Aspekte, das Konzert als eine sinnliche Wahrnehmung und einen sozialen Tatbestand („fait social“) sowie das anwesende Publikum mit ein. Musik wird somit nicht musikwissenschaftlich sondern soziologisch analysiert. Das Konzert wird als künstlerische Ausdrucksform in seinem sozialen Rahmen betrachtet: das soziale Treiben während des Konzerts, die Besonderheiten des Veranstaltungsorts und ähnliche Aspekte sind in diesem Sinne integrale Bestandteile dieser auf Städteebene angesiedelten Forschungsarbeit.

A classificação automática de gênero musical tem como finalidade o conforto de ouvintes de músicas auxiliando no gerenciamento das coleções de músicas digitais. Existem sistemas que se baseiam em cabeçalhos de metadados (tais como nome de artista, gênero cadastrado, etc.) e também os que extraem parâmetros dos arquivos de música para a realização da tarefa. Enquanto a maioria dos trabalhos do segundo tipo utilizam-se do conteúdo rítmico e tímbrico, este utiliza-se apenas de conceitos da teoria da informação e da geometria de fractais. Entropia, lacunaridade e dimensão do fractal são os parâmetros que treinam os classificadores. Os testes foram realizados com duas coleções criadas para este trabalho e os resultados foram proeminentes / The goal of automatic music genre classification is givingmusic listeners ease and confort when managing digital music databases. Some systems are based on tags of metadata (such as artist name, genre labeled, etc.), while others explore characteristics from the music files to complete the task. While the majority of works of the second type analyse rhytmic, timbric and pitch content, this one explores only information theoretic and fractal geometry concepts. Entropy, fractal dimension and lacunarity are the parameters adopted to train the classifiers. Tests were carried out on two databases assembled by the author. Results were prominent