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Master theses

Current and past ideas and concepts for Master Theses.

Evaluation and Implementation of Machine Learning techniques for Sound Recognition using a Microphone Array

Subject

Machine learning techniques can be used to recognize particular sounds. A MEMS microphone arrays and an SoC FPGA built in our lab to determine the sound’s direction of arrival. Moreover, such devices have the potential to also identify acoustic patterns while determining the direction of arrival. The student has to explore existing machine learning techniques for sound recognition and to implement the most promising one on the FPGA-based embedded system.

Kind of work

- Literature study of the most interesting AI candidates for sound recognition.

- Software evaluation of the AI candidate.

- Implementation of the AI candidate in our SoC platform.

Framework of the Thesis

This thesis is related to the research track at the RapptorLab (INDI department) in collaboration with ETRO.

Number of Students

1

Expected Student Profile

- Basic knowledge of/ experience in Machine Learning.
- Good programming skills (C/C++, Python or Matlab).

Promotor

Mr. Abdellah Touhafi

+32 (0)2 629 3774

atouhafi@etrovub.be

more info

Supervisor

Mr. Bruno da Silva Gomes

+32 (0)2 629 3768

bdasilva@etrovub.be

more info

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