Mr Adrien Ycart
Data Mining (Postgraduate/Undergraduate)
Data that has relevance for decision-making is accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations such as the Internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, and electronic patient records. Data mining is a rapidly growing field that is concerned with developing techniques to assist decision-makers to make intelligent use of these repositories. The field of data mining has evolved from the disciplines of statistics and artificial intelligence. This module will combine practical exploration of data mining techniques with a exploration of algorithms, including their limitations. Students taking this module should have an elementary understanding of probability concepts and some experience of programming.
Machine Learning (Postgraduate)
The aim of the module is to give students an understanding of machine learning methods, including pattern recognition, clustering and neural networks, and to allow them to apply such methods in a range of areas.
Music Analysis and Synthesis (Undergraduate/Postgraduate)
This module is intended to provide students with advanced training in standard and state-of-the-art techniques for music analysis and synthesis. This knowledge is relevant for the music generation, processing, recording, reproduction and distribution industries, with special emphasis on music-oriented on-line services and the development of hardware and software for musicians, musicologists, sound engineers and producers. Background in digital signal processing is essential for the understanding of analysis and synthesis processes on musical signals.
Research Interests:My PhD research topic is : Music Language Models for Audio Analysis
- Symbolic music modelling
- Automatic Music Transcription
- Rhythm transcription
- Neural Networks, Machine Learning
YCART A, BENETOS E (2018). Polyphonic Music Sequence Transduction with Meter-Constrained LSTM Networks. IEEE International Conference on Acoustics, Speech and Signal Processing
Ycart A, Benetos E (2017). A study on LSTM networks for polyphonic music sequence modelling. 18th International Society for Music Information Retrieval Conference (ISMIR 2017)
YCART A, BENETOS E (2017). Neural Music Language Models: investigating the training process. International Conference of Students of Systematic Musicology
YCART A, Benetos E (2016). Towards a Music Language Model for Audio Analysis. DMRN+11: Digital Music Research Network One-day Workshop 2016
Ycart A, Jacquemard F, Bresson J et al. (2016). A supervised approach for rhythm transcription based on tree series enumeration. nameOfConference