An Automated Mp3 Tag Editor using Data Scraping, Data Aggregation and Data Mining, to retreive metadata for a given song.
CSE3001 - ETJ Project (Winter Semester 2021-22) Authors: Jonathan Rufus Samuel (20BCT0332), Shivansh Sahai (20BCT0236), Dr. Swarnlatha P
Abstract - The Music space int today’s world is ever evolving and expanding. With great improvements to today’s technology, we have been able to bring out music to the vast majority of today’s ever growing and tech savvy people. In today’s market, the biggest players for Music Streaming include behemoth corporations like Spotify, Gaana, Apple Music, YouTube Music and so on and so forth. This also happens to be quite the shift from how music was once listened to. For songs downloaded out of Old Music Databases, and other distribution sites, they oftentimes come without any known metadata. i.e., Most of the Details with regards to the songs are absent, such as the Artist’s name, the year it was made, Album Art, etc. This piece of software aims to tackle this problem via the principles of data mining and data aggregation via classification-based algorithms.
Proposed Solution: Proposed solution is to deploy an automation software that can data mine (data scrape) required metadata from various sources like google searches, Wikipedia, Spotify Databases, etc. This metadata is then applied to the required songs along with appropriate cover art. The Pert Diagram shown above best describes the thought process behind the given Project.
Demonstration Link: https://youtu.be/coYtrDU7lqY
Projected Release Date: June, 2023 | Copyright: © 2023 |Pages: 310
DOI: 10.4018/978-1-6684-8098-4
DOI URL: https://doi.org/10.4018/978-1-6684-8098-4.ch012
ISBN13: 9781668480984|ISBN10: 1668480980|EISBN13: 9781668481004|ISBN13 Softcover: 9781668480991
- GUI change from Python to React based Electron JS GUI
- Add Power Automate Scraping Vector
- Make Download Site for the same
- Improve Documentation
- Add Code of Conduct for Contributing