Master Thesis, Removal of noise from speech
Background of thesis project
The acoustic operator environment is essential for Volvo Construction Equipment machines. Our cabins are known for their low internal noise levels and that operators will experience a productive work shift in this environment. In order to further refine this environment we seek solutions for improved communication with the machine and its operator. This communication solution should ideally work regardless of whether the operator or speaker are located on the inside or outside of the cabin or working remotely.
Our work at Volvo CE is now focused on electrical, remote controlled and autonomous machines. Please see the following link for more information: https://www.dn.se/ekonomi/fjarrstyrda-hjullastare-och-forarlosa-dumprar-uppkopplade-mot-5g-nat-framtiden-for-volvo/
The student/students should have a background in Signal Processing or similar, with good MATLAB programming skills.
Description of thesis work
In this thesis work the target is to develop methods for removing background machine noise from relevant sounds such as speech. The project is split in two parts, depending on whether there are one or two students. It can also be seen as a core part and an optional part, if there is only one student.
There are two approaches that should be tested, but the project could be limited to either one of them, if there is only one student doing the work. The approaches to be implement and evaluate are blind source separation or adaptive noise cancellation.
Thesis Level: Master
Language: Swedish or English
Starting date: 2020-01-13
Number of students:1 or 2
Nicklas Frenne Specialist Sound Quality 016-541 4726
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