Stefan Braun

Position:
PhD Student -- ended Sep 2019
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As a PhD student, I dedicate my research to bringing perceptional capabilities to machines.
I especially focus on automatic speech recognition. This involves research in areas such as deep learning, and developing methods using recurrent neural networks and other state-of-the art methods in this research domain.

My intention is not only to achieve good results on standard artificial benchmarks, but to also develop methods that are robust and fast enough for real world applications (e.g. noisy environments, limited computational power). Event-based sensors such as the event-driven spiking cochlea and their use together with spiking neural networks are key components to achieve these goals.

Supervisor

Shih-Chii Liu

Publications

2019

  • Braun, S. and Liu, S-C. Parameter uncertainty for end-to-end speech recognition, 2019 International Conference on Acoustics, Speech and Signal Processing, 2019
  • Braun, S., Neil, D., Anumula, J.,. Ceolini, E., and Liu, S-C. Attention-driven multi-sensor selection, 2019 IEEE International Joint Conference on Neural Networks (IJCNN), 2019
  • Ceolini, E., Anumula, J.,. Braun, S., and Liu, S-C. Event-driven pipeline for low latency low compute keyword spotting and speaker verification system, 2019 International Conference on Acoustics, Speech and Signal Processing, 2019
  • Gao, C., Braun, S., Kiselev, I., Anumula, J., Delbruck, T., Liu, S-C. Live Demonstration: Real-Time Spoken Digit Recognition Using the DeltaRNN Accelerator, 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019
  • Gao, C., Braun, S., Kiselev, I., Anumula, J., Delbruck, T., Liu, S-C. Real-Time Speech Recognition for IoT Purpose Using a Delta Recurrent Neural Network Accelerator, 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019

2018

2017