Seminar/Thesis: Automatic tagging audio databases
Background
Machine learning methods can nowadays be very helpful to automatically collect data and build large-sized datasets. However, the retrieved datasets need to be cataloged before being further processed. The project aims at implementing a convenient algorithm for the automatic tagging of audio data retrieved from publicly available repositories.
Aim
Apply algorithms to catalog and tag automatically audio data retrieved from publicly available repositories.
Learning objectives
- Analyse audio data from open source repositories
- Apply audio processing methods to segment and tag data stream
- Apply machine learning algorithms to automate the process
Data
| Project type | Seminar (optional: Master thesis) |
| ECTS | 2.5, 5, 7.5, default: 5 |
| Language | English |
| Period | Summer term 2021 |
| Presence time | Virtual seminar, working from remote |
| Useful knowledge | Python, Machine Learning, Audio Processing |
| Work distribution | 100% algorithm development |
| Med. Eng. designation | Advanced Context Recognition (ACR) |
| StudOn link | Please join |
| First Meeting | online-introduction-vorbesprechung-of-summer-term-2021-seminars, on 12th April 2021 at 16:15 |
| Registration | Via StudOn, obligatory after introduction |
Literature
Up-to-date literature recommendations are provided during the lectures.
Examination
Final presentation and final report.
Contact
Annalisa Baronetto
- Job title: Researcher
- Address:
Henkestraße 91, Haus 7, 1. OG
91052 Erlangen
Germany - Phone number: +49 9131 85 23608
- Email: annalisa.baronetto@fau.de