research

I am currently working as a consultant for TIDO and as Post-Doc at City, University of London. Have a look on the right for my recent publications. My research interests include the following topics within music information retrieval and bioacoustics:

  • computational (ethno)musicology
  • digital humanities
  • biometrics, ecg and ppg signals
  • raspberry pi, arduiono and the internet of things
  • automatic score following
  • big data technologies on large music datasets
  • social tagging and folksonomies
  • human computation
  • automatic animal sound detection

Have a look at my Google Scholar site for my publications.

The Digital Music Lab

An AHRC Digital Transformations Project

In collaboration with City University, UCL, QMUL, British Library

During my post-doctoral research at City University I worked on the DML and ASyMMus projects. Both part of the Big Data call of the Digital Transformations in the Arts and Humanities Theme we created a methodology and infrastructure including a web interface and API for remote extraction and access of analysis results from datasets provided by the British Library, I Like Music and the CHARM project.

Spot The Odd Song Out

Similarity Model Adaptation and Analysis using Relative Human Ratings

Finished PhD Studies at City University download thesis

I have recently finished my PhD thesis within the Music Informatics Research Group at City University London. You can read more about the thesis here. A major factor which allowed this project to be successful was our game Spot The Odd Song Out. With Music Technology Group at Universitat Pompeu Fabra, we have developed a flamenco version! You can try the game here. Spot The Odd Song Out

Detecting Bird Sounds via Periodic Structures

A Robust Pattern Recognition Approach to Unsupervised Animal Monitoring

Diploma Thesis; Bonn University 2008 download

My diploma thesis evolved during a collaborative project of the Multimedia Signal Processing Group of Bonn University and the Animal Sound Archive in Berlin. (Long term) monitoring recordings have been performed in a nature conservation area at Parstein Lake, Brandenburg, Germany. Besides a general description of the Project, the thesis focuses on general signal processing algorithms for bird songs featuring periodic structures. These are currently used to identify the Savi’s Warbler calls within such recordings. Furthermore, techniques are provided for the analysis of more complex rhythmic structures. The design of the algorithms heavily orients towards robust recognition of the repetitive song, as the undirected recordings are subject to varying grades of (weather-induced) noise. Key technologies include: FFT, Novelty Curves, Autocorrelation, Hidden Markov Models.

Wuner

A basic windows guitar tuner

Software, Win32 download

This Software may contain errors or malfunction, use with care!