Master-thesis (M/F/d) - Lightweight Environment
vor 3 Monaten
**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**:
Adaptive transparence/noise cancellation is an emerging feature that is becoming available on hearables (such as the AirPods in iOS 17). While one could solve this problem via a soundscape adaptation approach, a more computationally simple method might be to classify the current environment and then based on the classification define whether ANC/Transparency/Or neither should be active - this could even be user defined.
The main part of this task would be based on the low-complexity acoustic scene classification problem presented at DCASE [1, where a mínimal footprint ML approach would be defined for environment classification. The study could then consider the creation of a decision tree based on user preference tests (or user defined protocol) for when ANC/Transparency/Neither should be active.
**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.
**Interested?**
**We look forward to getting to know you**
Fraunhofer-Institute for Integrated Circuits IIS
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