Master-Thesis (m/f/d) – Adaptive Soundscape Editing Based on Classified Acoustic Events

Master-Thesis (m / f / d) Adaptive Soundscape Editing Based on Classified Acoustic Events at Fraunhofer-Institut für Integrierte Schaltungen IIS softgarden

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Master-Thesis (m / f / d) Adaptive Soundscape Editing Based on Classified Acoustic Events

Part Time

Hybrid

Am Wolfsmantel 33, Erlangen

Without Professional Experience

11 / 23 / 24

The Fraunhofer-Gesellschaft ( www.fraunhofer.com ) currently operates 76 institutes and research institutions throughout Germany and is the world’s leading applied research organization.

Around 30 800 employees work with an annual research budget of 3 billion euros.

You are interested in combining research and practices and would like to write a Master-Thesis about the above topic?

Then have a look at our offer!

What you will do

Abstract :

This topic aims at the removal of classified acoustic events from a given recorded signal. In it's simplest form this could be an ambience suppression algorithm, but perhaps more interestingly it could be used as an accessibility feature to aid people who suffer from misophonia / hyperacusis / phonophobia, by suppressing certain unwanted sounds.

While datasets curated for such an accessibility feature are perhaps limited, an initial starting point might be to investigate a proof-of-concept making use of the DCASE dataset 1 for suppression of pre-annotated acoustic events.

An alternative side-track for this project could be to consider a lower complexity classification of acoustic events, in this case it might be that the sound-labels used in DCASE need to be simplified.

If a lightweight real-time solution is possible, it's not infeasible that this could be used within a transparency / ANC pipeline on hearables like True-Wireless earbuds.

1 https : / / dcase.community / challenge2023 / task-sound-event-localization-and-detection-evaluated-in-real-spatial-sound-scenes

What you bring to the table

• You are currently studying Computer science, Electrical engineering or similar
• Confident in python programming, optimally some experience in the domain of signal processing
• Knowledgeable in the field of machine learning, and experience working with TensorFlow or PyTorch

What you can expect

• Flexible working hours
• Open and friendly team work
• Networking with scientists
• Active contribution in applied research
• Interesting an innovative projects

Your start date and weekly working hours will be determined individually with you. After your studies, there are attractive opportunities to join the institute on a full time or part time basis.

We would be happy to offer you the opportunity to write a master's thesis in cooperation with us in the above-mentioned subject area.

The thesis will be assigned and carried out in accordance with the rules of your university. For this reason, please discuss the thesis with a professor who can advise you over the course of the project.

We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity.

Interested?

Apply online now (PDF : cover letter, CV, transcripts).

We look forward to getting to know you!

Fraunhofer-Institute for Integrated Circuits IIS

www.iis.fraunhofer.de / en

Apply Online

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