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CDH

Seminar: Automatic building and cataloging audio databases from web

Background

Web scraping methods can nowadays be very helpful to automatically collect data and build large-sized datasets which can be necessary when developing machine learning algorithms. The project aims at implementing a convenient algorithm for the automatic extraction and tagging of audio data by using web scraping, crowd-sourcing and publicly available repositories.

Aim

Apply web scraping-based algorithms to extract and catalogue automatically audio data from publicly available repositories.

Learning objectives

  • Analyze audio data from open source repositories
  • Apply web-scraping methods to collect datasets from publicly available repositories
  • Use crowd-sourcing to catalog the audio data
  • 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 Winter term 2020/21
Presence time Virtual seminar, working from remote
Useful knowledge Python, Machine Learning
Work distribution 100% algorithm development
Med. Eng. designation Advanced Context Recognition (ACR)
StudOn link Please join
First Meeting online-introduction-vorbesprechung-of-winter-term-2020-seminars, on 4th November 2020 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