Master Thesis Speech Target Extraction Based on Directives

Company Description

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference.

The Robert Bosch GmbH is looking forward to your application!

Job Description

Targeted speech understanding in a multi-source auditory environment is crucial for the latest hearing acoustics applications such as ear buds, hearing aids, smart watches, in-car acoustics, etc. In the latest hearing devices, AI-based systems such as recurrent neural networks, LSTMs, beamformer networks are deployed to perform noise cancellation, speaker enhancement, etc. With the introduction of directives, target speaker identification is possible without the need for clean target samples.

• In your Master thesis, you will investigate target speech extraction with different background noises and develop a target extraction method based on directives. You will evaluate speech extraction methods for hearing aids.
• You will perform data augmentation on toy datasets and implement pre-processing stages of audio.
• Furthermore, you will develop neural networks to extract target speech based on directives.
• In addition, you will extend the developed method to multi-source speech targets.
• Last but not least, you will gain experience and collaborate in a cross-functional team spanning algorithms, deployment and hardware.

Qualifications

• Education: Master studies in the field of Electrical Engineering, Computer Science or comparable
• Experience and Knowledge in Python and C++; background in Neural Networks; knowledge of PyTorch is an advantage
• Personality and Working Practice: anindependent, structured and highly motivated person
• Enthusiasm: keen interest in future technologies and trends with a passion for innovation
• Languages: fluent in English, German is an advantage

Additional Information

Start: according to prior agreement
Duration: 6 months

Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.

Need further information about the job?
Shreya Kshirasagar (Functional Department)
+49 152 061 48397
Andre Guntoro (Functional Department)
+49 1525 881 3129

#LI-DNI

Summary

• Type: Full-time
• Function: Engineering