Master Thesis Deep Neural Networks for Background Noise Classification

Job Description

Category: Signal Processing and Acoustics

Scope: 2 students completing 30/60 credits (20 weeks/40 weeks) each.

Background

Axis Communications develops products that produce sounds such as loudspeakers and intercoms which are deployed in a wide range of acoustical environments and under varying operating conditions. Background noise classification plays a key role in applications such as speech communication hearing aids surveillance and environmental monitoring. Correctly identifying the type of noise enables systems to adapt processing strategies improving intelligibility performance and context awareness. Traditional methods based on hand-crafted features and classical machine learning perform adequately in controlled settings but often fail in real-world scenarios with non-stationary overlapping and diverse noise sources.

Deep learning offers a powerful alternative by learning feature representations directly from audio signals. Neural network architectures such as convolutional and recurrent models have already shown strong performance in related tasks like speech recognition and acoustic scene analysis. However their reliability and generalizability for background noise classification in complex acoustic environments remain open challenges motivating further investigation.

Goal

• Develop a dataset of background noise recordings representing diverse acoustic environments.
• Design and implement deep learning models for automatic noise classification exploring suitable architectures and feature representations.
• Evaluate and compare performance against traditional approaches to assess robustness and generalizability.
• Analyse strengths and limitations of deep learning methods for real-world background noise classification.

Who are you

For this thesis proposal we target students with a strong interest in audio acoustics and computer science. Most likely you are studying a masters program in a sound related field.

OK I am interested! What do I do now
You are valuable to us how nice that you are interested in one of our proposals! There are a few things for you to keep in mind when applying.

• Applications are accepted in both Swedish and English and you apply via the proposal advert.
• The announced thesis is open only to students affiliated with a Swedish University/College either directly or via an exchange program.
• When the thesis proposal states that it includes two students working together we would like you to apply in these cases send one application each but make sure to clearly state in your application who your co-applicant is. If you have any questions regarding this please do not hesitate to contact us.
• Please attach your CV and University/College grade summary.

Who to contact for any questions regarding the position!
Please contact Vasishta Kanthi

Type of Employment

Posting End Date

Certain roles at Axis require background checks which means applicable verifications will be done in these recruitments. Notice will be provided before we take any action.

About Axis Communications

We enable a smarter safer world by creating innovative solutions for improving security and business performance. As a network technology company and industry leader we offer solutions in video surveillance access control intercom and audio systems enhanced by intelligent analytics applications.

With around 5000 committed employees in over 50 countries we collaborate with partners worldwide. Together we thrive in our friendly open and collaborative culture and inspire each other to think beyond the expected. United by our commitment to inclusion diversity and sustainability we consistently seek to develop our skills and way of working.

Lets create a smarter safer world

For more information about Axis please visit our website .

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