780 resultados para Vespers (Music)


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The aim of the study is to examine Luther s theology of music from the standpoint of pleasure. The theological assessment of musical pleasure is related to two further questions: the role of emotions in Christianity and the apprehension of beauty. The medieval discussion of these themes is portrayed in the background chapter. Significant traits were: the suspicion felt towards sensuous gratification in music, music as a mathematical discipline, the medieval theory of emotions informed by Stoic apatheia and Platonic-Aristotelian metriopatheia, the notion of beauty as an attribute of God, medieval aesthetics as the aesthetic of proportion and the aesthetic of light and the emergence of the Aristotelian view of science that is based on experience rather than speculation. The treatment of Luther s theology of music is initiated with the notion of gift. Luther says that music is the excellent (or even the best) gift of God. This has sometimes been understood as a mere music-lover s enthusiasm. Luther is, however, not likely to use the word gift loosely. His theology can be depicted as a theology of gift. The Triune God is categorically giving. The notion of gift also includes reciprocity. When we receive the gifts of God, it evokes praise in us. Praising God is predominantly a musical phenomenon. The particular benefit of music in Luther s thought is that it can move human emotions. This emphasis is connected to the overall affectivity of Luther s theology. In contrast to the medieval discussion, Luther ascribes to saints not just emotions but particularly warm and tender affections. The power of music is related to the auditory and vocal character of the Word. Faith comes through hearing the Word that is at once musical and affective perception. Faith is not a mere opinion but the affective trust of the heart. Music can touch the human heart and persuade with its sweetness, like the good news of the Gospel. Music allows us to perceive Luther s theology as a theology of joy and pleasure. Joy is for Luther a gift of the Holy Spirit that fills the heart and bursts out in voice and gestures. Pleasure appears to be a central aspect to Luther s theology. The problem of the Bondage of the Will is precisely the human inability to feel pleasure in God s will. To be pleased in the visible and tangible creation is not something a Christian should avoid. On the contrary, if one is not pleased with the world that God has created, it is a sign of unbelief and ingratitude. The pleasure of music is aesthetic perception. This in turn necessitates the investigation of Luther s aesthetics. Aesthetic evaluation is not just a part of Luther s thought. Eventually his theology as a whole could be portrayed in aesthetic terms. Luther s extremely positive appreciation of music illutrates his theology as an affective acknowledgement of the goodness of the Creation and faith as an aesthetic contentment.

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This study investigates the affinities between philosophy, aesthetics, and music of Japan and the West. The research is based on the structuralist notion (specifically, on that found in the narratology of Algirdas Julius Greimas), that the universal grammar functions as an abstract principle, underlying all kinds of discourse. The study thus aims to demonstrate how this grammar is manifested in philosophical, aesthetic, and musical texts and how the semiotic homogeneity of these texts can be explained on this basis. Totality and belongingness are the key philosophical concepts presented herein. As distinct from logocentrism manifested as substantializations of the world of ideas , god or mind, which was characteristic of previous Western paradigms, totality was defined as the coexistence of opposites. Thus Heidegger, Merleau-Ponty, Dōgen, and Nishida often illustrated it by identifying fundamental polarities, such as being and nothing, seer and seen, truth and illusion, etc. Accordingly, totality was schematically presented as an all-encompassing middle of the semiotic square. Similar values can be found in aesthetics and arts. Instead of dialectic syntagms, differentiated unity is considered as paradigmatic and the study demonstrates how this is manifested in traditional Japanese and Heideggerian aesthetics, as well as in the aspects of music of Claude Debussy and Tōru Takemitsu.

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Hip-hopin juuret juontavat 1970-luvulle Yhdysvaltoihin, mutta hip-hop-kulttuuri ja musiikkityyli ovat sen jälkeen levinneet ympäri maailmaa osana globalisaatiokehitystä. Myös monet nuoret muslimit tekevät nykyään hip-hop-musiikkia, ja yhä useampi tuo myös sanoituksiinsa vaikutteita Islamista ja elämästään muslimina. Musiikin asema on islamissa varsin kiistelty, eikä sitä ole selvästi sallittu (halal) tai kielletty (haram) muslimeilta. Muslimien tekemää hip-hoppia on toistaiseksi tutkittu hyvin vähän. Tutkielmassa tarkastellaan diskurssianalyysin keinoin, miten tapaustutkimuksena toimivalla muslimhiphop.com-internetsivustolla argumentoidaan ja konstruoidaan käsityksiä muslimi-identiteetistä. Teoreettisena ja analyyttisenä viitekehyksenä toimii sosiaalikonstruktivistinen näkemys identiteetistä kontekstisidonnaisena sekä puheessa ja teksteissä diskursiivisesti rakentuvana. Tutkielma kyseenalaistaa aiempien tutkimusten oletuksen hip-hopista vaikutuksiltaan yksinomaan positiivisena muslimi-identiteetille sekä muslimeja yhdentävänä tekijänä. Aineisto on kerätty edellä mainitulta sivustolta syksyn 2010 ja kevään 2011 aikana, josta analyysiin on rajattu vain itse sivusto ja sen hip-hoppia käsittelevät osiot. Sivusto ja sen perustaja ovat yhdysvaltalaisia, mutta sivustolla esiteltävien artistien tausta on hyvin monikulttuurinen. Moni on myös maahanmuuttajana nykyisessä kotimaassaan. Aineistossa esiintyviä teemoja ja diskursseja eritellään ja analysoidaan tutkielmassa lainauksien avulla. Sivuston periaatteissa ja artistien esillepääsyn kriteereissä määritellään tarkasti asennoituminen Islamin ja musiikin yhdistämiseen: mikäli sanoitukset ja artistit noudattavat Islamin oppeja, on muslimin sallittua tehdä ja kuunnella tällaista musiikkia. Islam-aiheisen hip-hopin perustellaan olevan ennen kaikkea vaihtoehto valtavirran hip-hopille, jota konstruoidaan aineistossa moraalisesti arveluttavaksi. Hip-hopille sekä muslimeille sallittuja ja kiellettyjä elementtejä erottelevan halal-haram-diskurssin ohella aineistosta nousee esiin opetusdiskurssi. Muslimien tekemän hip-hopin perustellaan edistävän Islamin opettamista erityisesti nuorille muslimeille ja siten vahvistavan positiivista muslimi-identiteettiä. Myös positiivisen muutoksen diskurssia käytetään aineistossa runsaasti liittyen mm. muslimiyhteisöihin sekä muslimeihin kohdistuviin taloudellisiin ja sosiaalipoliittisiin epäkohtiin ja stereotypioihin; musiikin sisältöä ja sen tekemistä perustellaan sen voimalla muuttaa asioita parempaan suuntaan. Monet muslimiartistit kamppailevat yhdistääkseen toisaalta Islamin ja taiteellisen luovuuden ja ilmaisuvapauden, toisaalta menestyäkseen kaupallisesti unohtamatta uskonnollista vakaumustaan. Monilla heistä hip-hop on ollut vahvasti läsnä kasvuympäristössä, mutta sen yhdistäminen Islamin periaatteisiin aiheuttaa kysymyksiä ja kyseenalaistuksia oman musiikillisen ja uskonnollisen identiteetin muodosta ja sisällöstä. Aineiston perusteella monet muslimiartistit ja Islam-aiheista hip-hoppia kuuntelevat muslimit joutuvat jatkuvasti puolustamaan musiikkia siihen kielteisesti suhtautuville muslimeille sekä ei-muslimeille, jotka vierastavat sen uskonnollisuutta. Muslimi-identiteettiä neuvotellaan jatkuvasti, ja se näyttäytyy aineistossa moniulotteisena ja tilanteisesti rakentuvana. Avainsanat: Muslimit, Islam, hip-hop, identiteetti, Internet, diskurssi, diskurssianalyysi

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In the direction of arrival (DOA) estimation problem, we encounter both finite data and insufficient knowledge of array characterization. It is therefore important to study how subspace-based methods perform in such conditions. We analyze the finite data performance of the multiple signal classification (MUSIC) and minimum norm (min. norm) methods in the presence of sensor gain and phase errors, and derive expressions for the mean square error (MSE) in the DOA estimates. These expressions are first derived assuming an arbitrary array and then simplified for the special case of an uniform linear array with isotropic sensors. When they are further simplified for the case of finite data only and sensor errors only, they reduce to the recent results given in [9-12]. Computer simulations are used to verify the closeness between the predicted and simulated values of the MSE.

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We analyze the AlApana of a Carnatic music piece without the prior knowledge of the singer or the rAga. AlApana is ameans to communicate to the audience, the flavor or the bhAva of the rAga through the permitted notes and its phrases. The input to our analysis is a recording of the vocal AlApana along with the accompanying instrument. The AdhAra shadja(base note) of the singer for that AlApana is estimated through a stochastic model of note frequencies. Based on the shadja, we identify the notes (swaras) used in the AlApana using a semi-continuous GMM. Using the probabilities of each note interval, we recognize swaras of the AlApana. For sampurNa rAgas, we can identify the possible rAga, based on the swaras. We have been able to achieve correct shadja identification, which is crucial to all further steps, in 88.8% of 55 AlApanas. Among them (48 AlApanas of 7 rAgas), we get 91.5% correct swara identification and 62.13% correct R (rAga) accuracy.

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Compressive Sensing (CS) is a new sensing paradigm which permits sampling of a signal at its intrinsic information rate which could be much lower than Nyquist rate, while guaranteeing good quality reconstruction for signals sparse in a linear transform domain. We explore the application of CS formulation to music signals. Since music signals comprise of both tonal and transient nature, we examine several transforms such as discrete cosine transform (DCT), discrete wavelet transform (DWT), Fourier basis and also non-orthogonal warped transforms to explore the effectiveness of CS theory and the reconstruction algorithms. We show that for a given sparsity level, DCT, overcomplete, and warped Fourier dictionaries result in better reconstruction, and warped Fourier dictionary gives perceptually better reconstruction. “MUSHRA” test results show that a moderate quality reconstruction is possible with about half the Nyquist sampling.

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Music signals comprise of atomic notes drawn from a musical scale. The creation of musical sequences often involves splicing the notes in a constrained way resulting in aesthetically appealing patterns. We develop an approach for music signal representation based on symbolic dynamics by translating the lexicographic rules over a musical scale to constraints on a Markov chain. This source representation is useful for machine based music synthesis, in a way, similar to a musician producing original music. In order to mathematically quantify user listening experience, we study the correlation between the max-entropic rate of a musical scale and the subjective aesthetic component. We present our analysis with examples from the south Indian classical music system.

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We address the problem of multi-instrument recognition in polyphonic music signals. Individual instruments are modeled within a stochastic framework using Student's-t Mixture Models (tMMs). We impose a mixture of these instrument models on the polyphonic signal model. No a priori knowledge is assumed about the number of instruments in the polyphony. The mixture weights are estimated in a latent variable framework from the polyphonic data using an Expectation Maximization (EM) algorithm, derived for the proposed approach. The weights are shown to indicate instrument activity. The output of the algorithm is an Instrument Activity Graph (IAG), using which, it is possible to find out the instruments that are active at a given time. An average F-ratio of 0 : 7 5 is obtained for polyphonies containing 2-5 instruments, on a experimental test set of 8 instruments: clarinet, flute, guitar, harp, mandolin, piano, trombone and violin.

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The tonic is a fundamental concept in Indian art music. It is the base pitch, which an artist chooses in order to construct the melodies during a rg(a) rendition, and all accompanying instruments are tuned using the tonic pitch. Consequently, tonic identification is a fundamental task for most computational analyses of Indian art music, such as intonation analysis, melodic motif analysis and rg recognition. In this paper we review existing approaches for tonic identification in Indian art music and evaluate them on six diverse datasets for a thorough comparison and analysis. We study the performance of each method in different contexts such as the presence/absence of additional metadata, the quality of audio data, the duration of audio data, music tradition (Hindustani/Carnatic) and the gender of the singer (male/female). We show that the approaches that combine multi-pitch analysis with machine learning provide the best performance in most cases (90% identification accuracy on average), and are robust across the aforementioned contexts compared to the approaches based on expert knowledge. In addition, we also show that the performance of the latter can be improved when additional metadata is available to further constrain the problem. Finally, we present a detailed error analysis of each method, providing further insights into the advantages and limitations of the methods.

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We formulate the problem of detecting the constituent instruments in a polyphonic music piece as a joint decoding problem. From monophonic data, parametric Gaussian Mixture Hidden Markov Models (GM-HMM) are obtained for each instrument. We propose a method to use the above models in a factorial framework, termed as Factorial GM-HMM (F-GM-HMM). The states are jointly inferred to explain the evolution of each instrument in the mixture observation sequence. The dependencies are decoupled using variational inference technique. We show that the joint time evolution of all instruments' states can be captured using F-GM-HMM. We compare performance of proposed method with that of Student's-t mixture model (tMM) and GM-HMM in an existing latent variable framework. Experiments on two to five polyphony with 8 instrument models trained on the RWC dataset, tested on RWC and TRIOS datasets show that F-GM-HMM gives an advantage over the other considered models in segments containing co-occurring instruments.