Master Thesis Speech Target Extraction Based on Directives
Master Thesis Speech Target Extraction Based on Directives
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Job Description
Targeted speech hearing in a multisource auditory environment is crucial for the latest hearing acoustics applications such as ear buds hearing aids smart watches incar acoustics etc. In the latest hearing devices AIbased 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.
- During your Master thesis you 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 preprocessing stages of audio.
- Furthermore you develop neural networks to extract target speech based on directives.
- In addition you extend the developed method to multisource speech targets.
- Last but not least you will gain experience and collaborate in a crossfunctional 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: an independent 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 7
Andre Guntoro (Functional Department)
49 1
#LIDNI
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
