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Master theses

Current and past ideas and concepts for Master Theses.

Beamformed Sound Classification

Subject

Sound classification is a hot topic in research, both classical machine learning as deep learning is used to classify sounds. Some researches even developed multi classifiers capable of recognizing multiple sounds at the same time. These classifiers only tell you what sound is present, not where it is coming from. Acoustic beamforming on the other hand is used to find out where sound is coming from. By focusing a microphone array into a specific direction, all sounds coming from that direction are amplified while sounds from other directions are suppressed

Kind of work

The work to be done involves:
1. Literature study
2. Evaluation of the most interesting solutions.
3. Implementation of the most promising solution

Framework of the Thesis

Framework of the Thesis
• M3-AC: A Multi-Mode Multithread SoC FPGA Based Acoustic Camera, https://www.mdpi.com/2079-9292/10/3/317
• SoundCompass: A Distributed MEMS Microphone Array-Based Sensor for Sound Source Localization, https://www.mdpi.com/1424-8220/14/2/1918
• A Multimode SoC FPGA-Based Acoustic Camera for Wireless Sensor Networks, https://ieeexplore.ieee.org/abstract/document/8449381

Number of Students

1

Expected Student Profile

• Interested in acoustics
• Interested in embedded systems and/or hardware accelerators.
• Experience with Python, C/C++ and/or Matlab programming languages.
• Motivated

Promotors

Mr. Abdellah Touhafi

+32 (0)2 629 3774

atouhafi@etrovub.be

more info

Prof. Bruno da Silva Gomes

+32 (0)2 629 3768

bdasilva@etrovub.be

more info

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