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Auswahl der wissenschaftlichen Literatur zum Thema „Music Theory, Key of Affection“
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Zeitschriftenartikel zum Thema "Music Theory, Key of Affection"
Mononen, Sini. „Epäilyksen musiikki ja anteeksiannon montaasi“. Lähikuva – audiovisuaalisen kulttuurin tieteellinen julkaisu 34, Nr. 2-3 (08.09.2021): 42–56. http://dx.doi.org/10.23994/lk.111160.
Der volle Inhalt der QuelleTrevarthen, Colwyn. „Embodied Human Intersubjectivity: Imaginative Agency, To Share Meaning“. Cognitive Semiotics 4, Nr. 1 (01.08.2012): 6–56. http://dx.doi.org/10.1515/cogsem.2012.4.1.6.
Der volle Inhalt der QuelleNærland, Torgeir Uberg. „Rhythm, rhyme and reason: hip hop expressivity as political discourse“. Popular Music 33, Nr. 3 (28.08.2014): 473–91. http://dx.doi.org/10.1017/s0261143014000361.
Der volle Inhalt der QuelleRehding, Alexander. „Three Music-Theory Lessons“. Journal of the Royal Musical Association 141, Nr. 2 (2016): 251–82. http://dx.doi.org/10.1080/02690403.2016.1216025.
Der volle Inhalt der QuelleChoi, Won-seon. „Modal and Major-Minor Key Theory in Seventeenth Century Music“. Yonsei Music Research 6 (31.12.1999): 221–49. http://dx.doi.org/10.16940/ymr.1999.6.221.
Der volle Inhalt der QuelleCOHEN, HARVEY G. „Recent Music History Scholarship: Pleasures and Drawbacks“. Journal of American Studies 49, Nr. 2 (Mai 2015): 405–12. http://dx.doi.org/10.1017/s0021875815000146.
Der volle Inhalt der QuelleSun, Jiayin, Haifeng Li und Lin Ma. „A music key detection method based on pitch class distribution theory“. International Journal of Knowledge-based and Intelligent Engineering Systems 15, Nr. 3 (17.06.2011): 165–75. http://dx.doi.org/10.3233/kes-2011-0219.
Der volle Inhalt der QuelleSwinkin, Jeffrey. „About a Key“. Journal of Musicology 34, Nr. 4 (2017): 515–58. http://dx.doi.org/10.1525/jm.2017.34.4.515.
Der volle Inhalt der QuellePuffett, Derrick. „Webern's Wrong Key-Signature“. Tempo, Nr. 199 (Januar 1997): 21–28. http://dx.doi.org/10.1017/s0040298200005568.
Der volle Inhalt der QuelleTaddie, Daniel. „Solmization, Scale, and Key in Nineteenth-Century Four-Shape Tunebooks: Theory and Practice“. American Music 14, Nr. 1 (1996): 42. http://dx.doi.org/10.2307/3052458.
Der volle Inhalt der QuelleDissertationen zum Thema "Music Theory, Key of Affection"
Hwang, Yeeun. „The Role of the Affect and the Key Characteristics in Chopin's Piano Music“. Kent State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=kent1620169641612711.
Der volle Inhalt der QuelleDousa, Dominic. „Assessing the degree of relatedness between key areas : a quantitative model of key distance and tonal similarity“. Virtual Press, 2003. http://liblink.bsu.edu/uhtbin/catkey/1259312.
Der volle Inhalt der QuelleSchool of Music
Vermeulen, Hendrik Johannes. „Key profile optimisation for the computational modelling of tonal centre“. Thesis, Stellenbosch : Stellenbosch University, 2012. http://hdl.handle.net/10019.1/71852.
Der volle Inhalt der QuelleENGLISH ABSTRACT: Tonality cognition incorporates a number of diverse and multidisciplinary aspects, including music cognition, acoustics, culture, computer-aided modelling, music theory and brain science. Current research shows growing emphasis on the use of computational models implemented on digital computers for music analysis, particularly with reference to the analysis of statistical properties, form and tonal properties. The applications of these analytical techniques are numerous, including the classification of genre and style, Music Information Retrieval (MIR), data mining and algorithmic composition. The research described in this document focuses on three aspects of tonality analysis, namely music cognition, computational modelling and music theory, particularly from the perspectives of statistical analysis and key-finding. Mathematical formulations are presented for a number of computational algorithms for analysing the statistical and tonal properties of music encoded in symbolic format. These include algorithms for determining the distributions of note durations, pitch intervals and pitch classes for statistical analysis and for template-based key-finding for tonal analysis. The implementation and validation of these computational algorithms on the Matlab software platform are subsequently discussed. The software application is used to determine whether a more optimal combination of pitch class weighing model and key profile template for the template-based key-finding algorithm can be derived, using the 24 preludes from Bach’s Well-tempered Clavier Book I, the Courante from Bach's Cello Suite in C major and the Gavotte from Bach's French Suite No. 5 in G major (BWV 816) as test material. Four pitch class weighing models, namely histogram weighing, flat weighing, linear durational weighing and durational accent weighing, are investigated. Two prominent key profile templates proposed in literature are considered, namely a key profile derived from tonality cognition experiments and a key profile based on classical music theory principles. The results show that the key-finding performances of all the combinations of the pitch class weighing models and existing key profile templates depend on the nature of the test material and that none of the combinations perform optimally for all test material. The software application is subsequently used to determine whether a more optimal key profile template can be derived using a pattern search parameter estimation algorithm. This investigation was conducted for diverse sets of search conditions, including unconstrained and constrained key profile coefficients, different pitch class weighing models, various key resolutions and different search algorithm parameters. Using the same sample material as for the key-finding evaluations, the investigation showed that a more optimal key profile, compared to existing profiles, can be derived. In comparing the average key-finding scores for all of the test material, the optimised profiles outperform the existing profiles substantially. The optimised key profiles introduce new pitch class hierarchies where the supertonic and the subdominant rate higher at the expense of the mediant in the major profile to improve the tracking of key modulations.
AFRIKAANSE OPSOMMING: Kognitiewe tonaliteit behels 'n aantal uiteenlopende en multidissiplinêre aspekte, insluitende musiek, akoestiek, kultuur, rekenaargesteunde modelering, musiekteorie en breinwetenskap. Huidige navorsing toon toenemende klem op die gebruik van berekenende modelering wat op digitale rekenaars geimplimenteer is vir musiekanalise, veral met verwysing na die analise van statistiese eienskappe, vorm en tonale eienskappe. Die aanwending van hierdie analitiese tegnieke is veelvoudig, insluitende die klassifikasie van genre of styl, onttrekking van musiekinformasie, dataversameling en algoritmiese komposisie. Die navorsing wat in hierdie dokument beskryf word fokus op drie aspekte van tonaliteit analise, naamlik musiekkognisie, berekenende modelering en musiekteorie, veral vanuit die perspektiewe van statistiese analise and toonsoortsoek. Wiskundige formulerings word aangebied vir 'n aantal berekeningalgoritmes vir die analise van die statistiese en tonale eienskappe van musiek wat in simboliese formaat ge-enkodeer is. Hierdie sluit algoritmes in vir die bepaling van die verspreidings van nootlengtes, toonintervalle en toonklasse vir statistiese analise en vir templaatgebaseerde toonsoortsoek vir tonale analise. Die implementering en validering van hierdie berekeningalgoritmes op die Matlab programmatuur platvorm word vervolgens bespreek. Die programmatuur toepassing word vervolgens gebruik om te bepaal of 'n meer optimale kombinasie van toonklas weegmodel en toonsoortprofiel templaat vir die templaat-gebaseerde toonsoortsoek algoritme afgelei kan word, deur gebruik te maak van Bach se Well-tempered Clavier Book I, die Courante van Bach se Cello Suite in C major en die Gavotte van Bach se French Suite No. 5 in G major (BWV 816) as toetsmateriaal. Vier toonklas weegmodelle, naamlik histogram weging, plat weging, lineêre duurtyd weging en duurtyd aksent weging, word ondersoek. Twee prominente toonsoortprofiel template uit die literatuur word oorweeg, naamlik 'n toonsoortprofiel wat van tonaliteit kognisie eksperimente afgelei is en 'n toonsoortprofiel gebaseer op klassieke musiekteoretiese beginsels. Die resultate wys dat die toonsoortsoek prestasies van al die kombinasies van die toonklas weegmodelle en bestaande toonsoortprofiel template afhang van die aard van die toetsmateriaal en dat geen van die kombinasies optimaal presteer vir alle toetsmateriaal nie. Die programmatuur toepassing word vervolgens aangewend om vas te stel of 'n meer optimale toonsoortprofiel afgelei kan word deur gebruik te maak van 'n patroonsoek parameterestimasie algoritme. Hierdie ondersoek is uitgevoer vir uiteenlopende stelle soektoestande, insluitende onbeperkte en beperkte toonsoortprofiel koëffisiënte, verskillende toonklas weegmodelle, 'n verskeidenheid toonsoort resolusies en verskillende soekalgoritme parameters. Deur gebruik te maak van dieselfde toetsmateriaal as vir die toonsoortsoek evaluerings, toon die ondersoek dat 'n meer optimale toonsoortprofiel, in vergelyking met bestaande profiele, afgegelei kan word. In 'n vergelyking van die gemiddelde toonsoortsoek prestasie vir al die toetsmateriaal, presteer die geoptimeerde profiele aansienlik beter as die bestaande profiele. The ge-optimeerde toonsoortprofiele lei tot nuwe toonklas hiërargiee waar die supertonikum en die subdominant hoër rangposissies beklee ten koste van die mediant in die majeur profiel, ten einde die navolg van toonsoort modulasies te verbeter.
Levine, Nathan J. „Exploring Algorithmic Musical Key Recognition“. Scholarship @ Claremont, 2015. http://scholarship.claremont.edu/cmc_theses/1101.
Der volle Inhalt der QuelleAarden, Bret J. „Dynamic melodic expectancy“. The Ohio State University, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=osu1060969388.
Der volle Inhalt der QuelleFaraldo, Pérez Ángel. „Tonality estimation in electronic dance music: a computational and musically informed examination“. Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/463079.
Der volle Inhalt der QuelleAquesta tesi doctoral versa sobre anàlisi computacional de tonalitat en música electrònica de ball. El nostre estudi es concentra en tres operacions fonamentals. Primer, intentem assenyalar possibles equívocs dins de la pròpia tasca, que normalment es desenvolupa sobre un vocabulari tonal extremadament centrat en el llenguatge de la música clàssica europea, reduït a un model binari major-menor que podria no acomodar fàcilment estils de música popular. Seguidament, presentem un estudi de pràctiques tonals en música electrònica de ball, efectuat en paral·lel a la recol·lecció i anàlisi d'un corpus de més de 2.000 fragments de música electrònica, incloent diversos subgèneres i graus de complexitat tonal. Basat en aquest corpus, suggerim la creació d'etiquetes tonals més obertes, que incloguin pràctiques modals així com configuracions tonals ambigües. Finalment, descrivim el nostre sistema d'extracció automàtica de tonalitat, adaptant models existents a les particularitats de la música electrònica de ball, amb la creació de distribucions tonals específiques a partir d'anàlisis estadístiques del recentment creat corpus.
Esta tesis doctoral versa sobre análisis computacional de tonalidad en música electrónica de baile. Nuestro estudio se concentra en tres operaciones fundamentales. Primero, intentamos señalar posibles equívocos dentro de la propia tarea, que normalmente se desarrolla sobre un vocabulario tonal extremadamente centrado en el lenguaje de la música clásica europea, reducido a un modelo binario mayor-menor que podría no acomodar fácilmente estilos de música popular. Seguidamente, presentamos un estudio de prácticas tonales en música electrónica de baile, efectuado en paralelo a la recolección y análisis de un corpus de más de 2.000 fragmentos de música electrónica, incluyendo varios subgéneros y grados de complejidad tonal. Basado en dicho corpus, sugerimos la creación de etiquetas tonales más abiertas, que incluyan prácticas modales así como configuraciones tonales ambiguas. Por último, describimos nuestro sistema de extracción automática de tonalidad, adaptando modelos existentes a las particularidades de la música electrónica de baile, con la creación de distribuciones tonales específicas a partir de análisis estadísticos del recién creado corpus.
Ishiguro, Maho A. „The affective properties of keys in instrumental music from the late nineteenth and early twentieth centuries“. 2010. https://scholarworks.umass.edu/theses/536.
Der volle Inhalt der QuelleMoylan, Andrew L. „Venerable Style, Form, and the Avant-Garde in Mozart’s Minor Key Piano Sonatas K. 310 and K. 457: Topic and Structure“. 2014. https://scholarworks.umass.edu/masters_theses_2/35.
Der volle Inhalt der QuelleBücher zum Thema "Music Theory, Key of Affection"
Stevenson, A. The vocal preceptor, or, Key to sacred music from celebrated authors. Montreal: [s.n.], 1987.
Den vollen Inhalt der Quelle findenGennet, Robbie. The key of ONE: A revealing, notation-free approach that unlocks the music within you. Van Nuys, CA: Alfred Music Pub. Co., 2010.
Den vollen Inhalt der Quelle findenAndrew, Maddocks, und Somerset Music Education Programme, Hrsg. Growing with music: Key stage 1 : teacher's book. Harlow, Essex: Longman, 1992.
Den vollen Inhalt der Quelle findenStocks, Michael. Growing with music: Key stage 2 : teacher's book B. Harlow, Essex: Longman, 1992.
Den vollen Inhalt der Quelle findenAndrew, Maddocks, und Somerset Music Education Programme, Hrsg. Growing with music: Key stage 2 : teacher's book A. Harlow, Essex: Longman, 1992.
Den vollen Inhalt der Quelle findenManus, Morton, Andrew Surmani und Karen Farnum Surmani. Essentials of Music Theory: Teacher's Answer Key Book (Essentials of Music Theory). Alfred Publishing Company, 1998.
Den vollen Inhalt der Quelle findenEssentials of Music Theory Major and Minor: Flash Cards - Key Signature (Essentials of Music Theory). Alfred Publishing Company, 2006.
Den vollen Inhalt der Quelle findenManus, Morton, Karen Surmani und Andrew Surmani. Essentials of Music Theory: Double Bingo Game -- Key Signature: Major and Minor (Essentials of Music Theory). Alfred Publishing Company, 2006.
Den vollen Inhalt der Quelle findenManus, Morton, Andrew Surmani und Karen Farnum Surmani. Essentials of Music Theory: Teacher's Answer Key Book and 2 Ear Training CDs (Essentials of Music Theory). Alfred Publishing Company, 1998.
Den vollen Inhalt der Quelle findenStocks, Michael, und Andrew Maddocks. Growing with Music Key Stage 1 Cassette (Growing with Music). Cambridge University Press, 1999.
Den vollen Inhalt der Quelle findenBuchteile zum Thema "Music Theory, Key of Affection"
Ford, Biranda. „From a Different Place to a Third Space: Rethinking International Student Pedagogy in the Western Conservatoire“. In The Politics of Diversity in Music Education, 177–89. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65617-1_13.
Der volle Inhalt der Quelle„Key Signatures for Major Scales“. In Revisiting Music Theory, 87–91. Second edition. | New York; London: Routledge, 2016. |: Routledge, 2016. http://dx.doi.org/10.4324/9781315689975-20.
Der volle Inhalt der Quelle„Key Signatures for Minor Keys“. In Revisiting Music Theory, 101–6. Second edition. | New York; London: Routledge, 2016. |: Routledge, 2016. http://dx.doi.org/10.4324/9781315689975-23.
Der volle Inhalt der Quelle„folk music“. In Key Concepts in Cultural Theory, 116–27. Routledge, 2005. http://dx.doi.org/10.4324/9780203981849-17.
Der volle Inhalt der QuelleSnodgrass, Jennifer. „The Classroom Environment“. In Teaching Music Theory, 50–90. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190879945.003.0003.
Der volle Inhalt der QuelleSnodgrass, Jennifer. „Pedagogy of Fundamentals and Diatonic Harmony“. In Teaching Music Theory, 125–60. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190879945.003.0005.
Der volle Inhalt der QuelleHickmott, Sarah. „Music, Mousike, Muses (and Sirens)“. In Music, Philosophy and Gender in Nancy, Lacoue-Labarthe, Badiou, 15–49. Edinburgh University Press, 2020. http://dx.doi.org/10.3366/edinburgh/9781474458313.003.0002.
Der volle Inhalt der QuelleManzo, V. J. „Tools for Music Theory Concepts“. In Max/MSP/Jitter for Music. Oxford University Press, 2011. http://dx.doi.org/10.1093/oso/9780199777679.003.0014.
Der volle Inhalt der QuelleBolden, Tony. „Sly Stone and the Gospel of Funk“. In Groove Theory, 85–116. University Press of Mississippi, 2020. http://dx.doi.org/10.14325/mississippi/9781496830524.003.0004.
Der volle Inhalt der QuelleBolden, Tony. „The Kinkiness of Turquoise“. In Groove Theory, 182–223. University Press of Mississippi, 2020. http://dx.doi.org/10.14325/mississippi/9781496830524.003.0007.
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