Use of artificial intelligence sn the application for working with musical notes

In the work, existing software solutions and successful IT projects were analyzed and their advantages and disadvantages were identified, which helped determine the requirements for a product that would be competitive and meet the requirements of the modern market. Modeling and designing of the software was carried out, the client-server architecture of the application was described, as well as the interaction of subsystems. The mobile application was developed and tested, and further directions for improvement and development of the application were determined. The application processes a PDF file with a given metronome speed in mp3 and mp4, which gives the user the opportunity to see and listen to the sheet music. The project includes an Android application with a clear and convenient interface, integration with external utilities and libraries. In the work, the processing of files from pdf format to such music and playback files as midi, musicxml, mp3, mp4 is collected in one stream. The process of parsing and playing with full-cycle processing of music files has been improved, by providing the user with all software modules, and the process of processing visual notes and bringing them to easy-to-use files, such as videos that combine notes with sound, has been improved. The work is important because it contributes to the development of digital music processing methods. The introduction of modern technologies for note recognition and visualization of musical elements contributes to technological progress in the field of music development.

Authors

Institutions

Publication Details

Journal
PROBLEMS IN PROGRAMMING
Published
2024-09-01
DOI
https://doi.org/10.15407/pp2024.02-03.384
Primary Topic
Music and Audio Processing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Use of artificial intelligence sn the application for working with musical notes

Victor Fuks, Svitlana Popereshnyak, Viktoriia Zhebka, A.K. Tsurkan
PROBLEMS IN PROGRAMMING
Music and Audio Processing
article

Use of artificial intelligence sn the application for working with musical notes

Victor Fuks, Svitlana Popereshnyak, Viktoriia Zhebka, A.K. Tsurkan
article en

Abstract

In the work, existing software solutions and successful IT projects were analyzed and their advantages and disadvantages were identified, which helped determine the requirements for a product that would be competitive and meet the requirements of the modern market. Modeling and designing of the software was carried out, the client-server architecture of the application was described, as well as the interaction of subsystems. The mobile application was developed and tested, and further directions for improvement and development of the application were determined. The application processes a PDF file with a given metronome speed in mp3 and mp4, which gives the user the opportunity to see and listen to the sheet music. The project includes an Android application with a clear and convenient interface, integration with external utilities and libraries. In the work, the processing of files from pdf format to such music and playback files as midi, musicxml, mp3, mp4 is collected in one stream. The process of parsing and playing with full-cycle processing of music files has been improved, by providing the user with all software modules, and the process of processing visual notes and bringing them to easy-to-use files, such as videos that combine notes with sound, has been improved. The work is important because it contributes to the development of digital music processing methods. The introduction of modern technologies for note recognition and visualization of musical elements contributes to technological progress in the field of music development.

PROBLEMS IN PROGRAMMING(2-3)
National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” (UA)
Openalex Percentile: Top 70%
Music and Audio Processing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.