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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Computing pitch names in tonal music : a comparative analysis of pitch spelling algorithms

Meredith, David January 2007 (has links)
A pitch spelling algorithm predicts the pitch names (e.g., C♯4, B♭5 etc.) of the notes in a passage of tonal music, when given the onset-time, MIDI note number and possibly the duration and voice of each note. A new algorithm, called ps13, was compared with the algorithms of Longuet-Higgins, Cambouropoulos, Temperley and Chew and Chen by running various versions of these algorithms on a ‘clean’, score-derived test corpus, C, containing 195972 notes, equally divided between eight classical and baroque composers. The standard deviation of the accuracies achieved by each algorithm over the eight composers was used to measure style dependence (SD). The best versions of the algorithms were tested for robustness to temporal deviations by running them on a ‘noisy’ version of the test corpus, denoted by C'. A version of ps13 called PS13s1 was the most accurate of the algorithms tested, achieving note accuracies of 99.44% (SD = 0.45) on C and 99.41% (SD = 0.50) on C'. A real-time version of PS13s1 also out-performed the other real-time algorithms tested, achieving note accuracies of 99.19% (SD = 0.51) on C and 99.16% (SD = 0.53) on C'. PS13s1 was also as fast and easy to implement as any of the other algorithms. New, optimised versions of Chew and Chen’s algorithm were the least dependent on style over C. The most accurate of these achieved note accuracies of 99.15% (SD = 0.42) on C and 99.12% (SD = 0.47) on C'. It was proved that replacing the spiral array in Chew and Chen’s algorithm with the line of fifths never changes its output. A new, optimised version of Cambouropoulos’s algorithm made 8% fewer errors over C than the most accurate of the versions described by Cambouropoulos himself. This algorithm achieved note accuracies of 99.15% (SD = 0.47) on C and 99.07% (SD = 0.53) on C'. A new implementation of the most accurate of the versions described by Cambouropoulos achieved note accuracies of 99.07% (SD = 0.46) on C and 99.13% (SD = 0.39) on C', making it the least dependent on style over C'. However, Cambouropoulos’s algorithms were among the slowest of those tested. When Temperley and Sleator’s harmony and meter programs were used for pitch spelling, they were more affected by temporal deviations and tempo changes than any of the other algorithms tested. When enharmonic changes were ignored and the music was at a natural tempo, these programs achieved note accuracies of 99.27% (SD = 1.30) on C and 97.43% (SD = 1.69) on C'. A new implementation, called TPROne, of just the first preference rule in Temperley’s theory achieved note accuracies of 99.06% (SD = 0.63) on C and 99.16% (SD = 0.52) on C'. TPROne’s performance was independent of tempo and less dependent on style than that of the harmony and meter programs. Of the several versions of Longuet-Higgins’s algorithm tested, the best was the original one, implemented in his music.p program. This algorithm achieved note accuracies of 98.21% (SD = 1.79) on C and 98.25% (SD = 1.71) on C', but only when the data was processed a voice at a time. None of the attempts to take voice-leading into account in the algorithms considered in this study resulted in an increase in note accuracy and the most accurate algorithm, PS13s1, ignores voice-leading altogether. The line of fifths is used in most of the algorithms tested, including PS13s1. However, the superior accuracy achieved by PS13s1 suggests that pitch spelling accuracy can be optimised by modelling the local key as a pitch class frequency distribution instead of a point on the line of fifths, and by keeping pitch names close to the local tonic(s) on the line of fifths rather than close on the line of fifths to the pitch names of neighbouring notes.
2

Smartphones och surfplattor i musikundervisningen

Fervenza, Manuel January 2023 (has links)
Dagens mellan- och högstadieelever lever i en digitaliserad värld där smartphones och surfplattor är en självklarhet. Samtidigt har applikationer för musikskapande blivit fler och bättre, och musikundervisning med digitala verktyg finns idag med i det centrala innehållet i kursplanen för ämnet musik i grundskolan. Syftet med uppsatsen var att ta reda på i vilken utsträckning mellan- och högstadieelevers digitala litteracitet med surfplattor och smartphones kan användas som redskap i musikundervisning samt vad de digitala verktygen kan erbjuda elever och deras lust att musicera. Utifrån ett sociokulturellt perspektiv och med fokus på lärande och medierande verktyg undersöktes mellan- och grundskoleelevers tillgång till, erfarenhet av, och lust att musicera med surfplattor och smartphones. Detta gjordes genom en kvantitativ enkätundersökning där 222 elever från fem olika skolor runt om i Sverige agerade respondenter. Resultatet visade att de allra flesta mellan- och högstadieelever har tillgång till en surfplatta eller smartphone och att de också använder redskapet dagligen. Dock var det endast en liten minoritet som hade erfarenhet av att skapa musik och spela virtuella instrument på surfplatta och smartphone. Detta mynnade ut i en diskussion där musiklärarens roll i att presentera surfplattor och smartphones som medierande redskap lyfts som viktig. Läraren bör ge eleverna ett sociokulturellt sammanhang där surfplattor och smartphones är medierande redskap och eleverna hittar meningserbjudanden även för musikskapande i artefakten.

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