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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.19181524 |
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| _version_ | 1866901401838288896 |
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| author | Yu-Hsin Chang |
| author_facet | Yu-Hsin Chang |
| contents | Polyphonic music presents unique technical and cognitive challenges for performers, especially when it comes to voice independence, finger coordination, and memorization (Sweller et al., 2019). This study proposes an interactive learning model that integrates Max/MSP gesture recognition technology with Ableton Live sequencing to enhance practice strategies for polyphonic repertoires, with a focus on Bach fugues. In the proposed system, distinct hand gestures are mapped to different musical voices and mapped to separate MIDI tracks to facilitate targeted practice of motifs, counter-motifs, and episodes. The design aims to optimize memorization, expand hand-eye span, reduce cognitive load, and support flow in performance. Technical comparisons of various Max/MSP gesture recognition approaches are discussed, alongside a detailed account of the system's architecture. Instead of large-scale quantitative testing, initial consultation and feedback were gathered from piano students and music educators to assess the system's usability and perceived pedagogical value. These expert insights suggest that technology-assisted practice schemas, grounded in embodiment and cognitive load theory, hold substantial promise for supporting the acquisition of polyphonic works and offer new avenues for future research and innovative pedagogy in music education. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19181524 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Practice Strategies for Polyphonic Music: Exploring the Role of Gesture Controllers in Enhancing Technical Stability and Optimizing Mapping Methods Yu-Hsin Chang Polyphonic music presents unique technical and cognitive challenges for performers, especially when it comes to voice independence, finger coordination, and memorization (Sweller et al., 2019). This study proposes an interactive learning model that integrates Max/MSP gesture recognition technology with Ableton Live sequencing to enhance practice strategies for polyphonic repertoires, with a focus on Bach fugues. In the proposed system, distinct hand gestures are mapped to different musical voices and mapped to separate MIDI tracks to facilitate targeted practice of motifs, counter-motifs, and episodes. The design aims to optimize memorization, expand hand-eye span, reduce cognitive load, and support flow in performance. Technical comparisons of various Max/MSP gesture recognition approaches are discussed, alongside a detailed account of the system's architecture. Instead of large-scale quantitative testing, initial consultation and feedback were gathered from piano students and music educators to assess the system's usability and perceived pedagogical value. These expert insights suggest that technology-assisted practice schemas, grounded in embodiment and cognitive load theory, hold substantial promise for supporting the acquisition of polyphonic works and offer new avenues for future research and innovative pedagogy in music education. |
| title | Practice Strategies for Polyphonic Music: Exploring the Role of Gesture Controllers in Enhancing Technical Stability and Optimizing Mapping Methods |
| url | https://doi.org/10.5281/zenodo.19181524 |