MemoVision: a tool for feature selection and visualization of performance data

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU149848" target="_blank" >RIV/00216305:26220/23:PU149848 - isvavai.cz</a>

Result on the web

<a href="https://ismir2023program.ismir.net/lbd_322.html" target="_blank" >https://ismir2023program.ismir.net/lbd_322.html</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

MemoVision: a tool for feature selection and visualization of performance data

Original language description

Music performance analysis has traditionally been a peripheral topic in the music information retrieval community. However, it is sometimes included in the goals of music information retrieval studies—from low- and high-level parameter detection and synchronization methods to feature selection and measure transfer. In this contribution, we introduce the MemoVision software, which utilizes retrieval and feature selection methods for comparative music analysis. It is built with JavaScript and Python languages, combining the accessibility of a web-based interface and state-of-the-art feature extraction possibilities. Its features can be used separately or as a visualization tool for music performance case studies.

Czech name

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Czech description

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Type

O - Miscellaneous

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/TL05000527" target="_blank" >TL05000527: Memories of Sound: The Evolution of the Interpretative Tradition Based on the Works of Antonin Dvorak and Bedrich Smetana</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů