Draft:MusicalDNA (software)
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|  |
| MusicalDNA | |
|---|---|
| Developer(s) | IWPD Management GmbH, Appassio AI Sp. z o.o. |
| Operating system | Web-based |
| Platform | Appassio.com |
| Type | Music Analysis, AI-powered Performance Evaluation |
| License | Proprietary |
| Website | musicaldna.me |
MusicalDNA is an AI-powered music analysis tool designed to assess and compare piano performances based on interpretative characteristics. Developed by IWPD Management GmbH with the data-science team SDSC of ETH Zurich and Kalaidos Music University. It allows pianists, musicologists, and educators to analyze their playing and compare it with the styles of historical grandmasters of classical piano. The platform is integrated into Appassio.com and utilizes advanced machine learning models trained on the representation of interpretative styles of renowned pianists from the late 19th and 20th centuries.
Overview
[edit]MusicalDNA offers pianists an AI-driven analysis of their performance, focusing on interpretative elements — the expressive and stylistic nuances that define how the music is played. By uploading an audio recording, users receive feedback on which grandmasters their playing resembles and how unique their interpretation is in comparison to historical styles.
The tool is designed for:
- Pianists – students, professionals, and competition participants looking to refine their interpretation.
- Educators – teachers and conservatories analyzing student performances.
- Musicologists – scholars researching historical performance practices.
- Music Enthusiasts – listeners interested in stylistic comparison and analysis.
Features
[edit]MusicalDNA offers a variety of functionalities, including:
- Grandmaster Comparison – Matches a user's performance with historically significant pianists such as Vladimir Horowitz, Sviatoslav Richter, Artur Rubinstein, Josef Hofmann, Dinu Lipatti, Ignaz Friedman and many more.
- Interpretation Uniqueness Factor – Determines how distinctive a user's playing is in comparison to classical traditions.
- Visual Performance Analysis – Displays waveform visualizations with detailed percentage breakdowns, indicating the stylistic influence of specific pianists throughout the performance.
- Social Sharing – Users can share their results or keep them private through their Appassio account.
Development
[edit]The development of MusicalDNA was segmented into two critical phases:
1. Phase A – Natural Music Making: Computational and human expert evaluation of what constitutes "natural" musical interpretation.
2. Phase B – Style Recognition: AI refinement to distinguish interpretative styles of grandmasters, ensuring high accuracy in comparisons.
The project combines historical performance research and AI advancements, making it the first AI-driven tool focused on interpretation of piano music.
Press
[edit]MusicalDNA has been featured in Austrian media. The Austrian newspaper Oberösterreichische Nachrichten published an article discussing the project and its potential impact on understanding musical interpretation through AI.[1]
The Italian newspaper Corriere della Sera also covered the development of MusicalDNA, highlighting its innovative approach to analyzing piano interpretation using artificial intelligence.[2]
See Also
[edit]- Music
- Music and artificial intelligence
- Musical performance
- Musical phrasing
- Category:20th-century classical pianists
External links
[edit]References
[edit]- ^ "Wie man die Genetik der Musik entschlüsselt". Oberösterreichische Nachrichten. 21 February 2025. Retrieved 25 February 2025.
- ^ "Ingolf Wunder, il pianista che utilizza l'intelligenza artificiale per scoprire gli impulsi dell'interpretazione di un brano". Corriere della Sera. 13 March 2024. Retrieved 25 February 2025.