975 resultados para Music analysis


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In recent years qualitative research methods have been adopted within in the field of music education and have received widespread acceptance. However, the theoretical framework provided by ethnomethodology (Garfinkel, 1974, in R. Turner, Ethnomethodology , Penguin, Middlesex, UK) and the tools of conversational analysis (Sacks, 1992, Lectures on Conversation , edited by Gail Jefferson, Blackwell, Oxford, UK) have, to this point, been overlooked by researchers in the field of music education. In this paper I argue that the application of ethnomethodological and conversation analytical approaches in the field of research in music education can provide fresh insights into the work of music teachers and how this work is accomplished in institutional settings. Here I demonstrate how a conversation analytical perspective drawing on an ethnomethodological framework might be used to investigate transcripts of audio-recorded interview talk. This type of analysis can illuminate aspects of members' roles in relation to, and perceptions about music education in school settings that might be overlooked in other types of analysis. A conversation analytical approach to the examination of talk-in-interaction explicates in fine-grained detail how members orient to matters at hand in the context of research settings, as well as revealing features of the cultural world of music teaching. Further application of the approach to research problems in other school settings, I argue, will inform the field of music education in ways yet to be realised.

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A raga is a collective melodic expression consisting of motifs. A raga can be identified using motifs which areunique to it. Motifs can be thought of as signature prosodic phrases. Different ragas may be composed of the same setof notes, or even phrases, but the prosody may be completely different. In this paper, an attempt is made to determinethe characteristic motifs that enable identification of a raga and distinguish between them. To determine this, motifs are first manually marked for a set of five popular raga by a professional musician. The motifs are then normalisedwith respect to the tonic. HMMs are trained for each motif using 80% of the data and about 20% are used for testing. The results do indicate that about 80% of the motifs are identified as belonging to a specific raga accurately.

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For computational studies of makam music, it is essential to gather a list of characteristics that constitute a makam and explore corresponding quantitative features for automaticanalysis. This study is such an attempt where we address the characteristics for makams as defined in theory books and deduce a list of quantitative features. The target here is to evoke discussions on some measurable features other than providing complete analysis on thediscriminative potentials of each proposed feature which could be the subject of a few larger studies.

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On étudie l’application des algorithmes de décomposition matricielles tel que la Factorisation Matricielle Non-négative (FMN), aux représentations fréquentielles de signaux audio musicaux. Ces algorithmes, dirigés par une fonction d’erreur de reconstruction, apprennent un ensemble de fonctions de base et un ensemble de coef- ficients correspondants qui approximent le signal d’entrée. On compare l’utilisation de trois fonctions d’erreur de reconstruction quand la FMN est appliquée à des gammes monophoniques et harmonisées: moindre carré, divergence Kullback-Leibler, et une mesure de divergence dépendente de la phase, introduite récemment. Des nouvelles méthodes pour interpréter les décompositions résultantes sont présentées et sont comparées aux méthodes utilisées précédemment qui nécessitent des connaissances du domaine acoustique. Finalement, on analyse la capacité de généralisation des fonctions de bases apprises par rapport à trois paramètres musicaux: l’amplitude, la durée et le type d’instrument. Pour ce faire, on introduit deux algorithmes d’étiquetage des fonctions de bases qui performent mieux que l’approche précédente dans la majorité de nos tests, la tâche d’instrument avec audio monophonique étant la seule exception importante.

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In a workshop setting, two pieces of recorded music were presented to a group of adult non-specialists; a key feature was to set up structured discussion within which the respondents considered each piece of music as a whole and not in its constituent parts. There were two areas of interest, namely to explore whether the respondents were likely to identify the musical features or to make extra-musical associations and, to establish the extent to which there would be commonality and difference in their approach to formulating the verbal responses. An inductive approach was used in the analysis of data to reveal some of the working theories underpinning the intuitive musicianship of the adult non-specialist listener. Findings have shown that, when unprompted by forced choice responses, the listeners generated responses that could be said to be information-poor in terms of musical features but rich in terms of the level of personal investment they made in formulating their responses. This is evidenced in a number of connections they made between the discursive and the non-discursive, including those which are relational and mediated by their experiences. Implications for music education are considered.

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Weather is frequently used in music to frame events and emotions, yet quantitative analyses are rare. From a collated base set of 759 weather-related songs, 419 were analysed based on listings from a karaoke database. This article analyses the 20 weather types described, frequency of occurrence, genre, keys, mimicry, lyrics and songwriters. Vocals were the principal means of communicating weather: sunshine was the most common, followed by rain, with weather depictions linked to the emotions of the song. Bob Dylan, John Lennon and Paul McCartney wrote the most weather-related songs, partly following their experiences at the time of writing.

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Mode of access: Internet.

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In this paper, we initially present an algorithm for automatic composition of melodies using chaotic dynamical systems. Afterward, we characterize chaotic music in a comprehensive way as comprising three perspectives: musical discrimination, dynamical influence on musical features, and musical perception. With respect to the first perspective, the coherence between generated chaotic melodies (continuous as well as discrete chaotic melodies) and a set of classical reference melodies is characterized by statistical descriptors and melodic measures. The significant differences among the three types of melodies are determined by discriminant analysis. Regarding the second perspective, the influence of dynamical features of chaotic attractors, e.g., Lyapunov exponent, Hurst coefficient, and correlation dimension, on melodic features is determined by canonical correlation analysis. The last perspective is related to perception of originality, complexity, and degree of melodiousness (Euler's gradus suavitatis) of chaotic and classical melodies by nonparametric statistical tests. (c) 2010 American Institute of Physics. [doi: 10.1063/1.3487516]

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Australia struggles to achieve economic competitiveness, prevent expansion of the trade deficit and develop value-added production despite applications of policy strategies from protectionism to trade liberalisation. This article argues that these problems were emerging at the turn of the century, and that an investigation of music technology manufacturing in the first two decades of this century reveals fundamental problems in the conduct of relevant policy analysis. Analysis has focused on the trade or technology gap which is only symptomatic of an underlying knowledge gap. The article calls for a knowledge policy approach which can allow protection without the negative effects of isolation from global markets and without having to resort to unworkable utopian free-trade dogma. A shift of focus from a 'goods traded' view to a knowledge transaction (or diffusion) perspective is advocated.

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Revista Lusófona de Línguas, Culturas e Tradução

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This paper studies musical opus from the point of view of three mathematical tools: entropy, pseudo phase plane (PPP), and multidimensional scaling (MDS). The experiments analyze ten sets of different musical styles. First, for each musical composition, the PPP is produced using the time series lags captured by the average mutual information. Second, to unravel hidden relationships between the musical styles the MDS technique is used. The MDS is calculated based on two alternative metrics obtained from the PPP, namely, the average mutual information and the fractal dimension. The results reveal significant differences in the musical styles, demonstrating the feasibility of the proposed strategy and motivating further developments towards a dynamical analysis of musical sounds.