Picture of Tobias Watzel

Tobias Watzel, M.Sc.

Technical University of Munich

Chair of Human-Machine Communication (Prof. Rigoll)

Postal address

Postal:
Arcisstr. 21
80333 München

Research Areas

• Deep Learning
• Speech Recognition

Publications

  • Kürzinger L., Watzel T., Li L., Baumgartner R., Rigoll G.: Exploring Hybrid CTC/Attention End-to-End Speech Recognition with Gaussian Processes. Proc. 21st International Conference on Speech and Computer SPECOM 2019, Springer, 2019Lecture Notes in Computer Science, pp. 258-269 more… Full text ( DOI )
  • Watzel T., Li L., Kürzinger L., Rigoll G.: Deep Neural Network Quantizers Outperforming Continuous Speech Recognition Systems. Proc. 21st International Conference on Speech and Computer SPECOM 2019, Springer, 2019Lecture Notes in Computer Science, pp. 530-539 more… Full text ( DOI )
  • Watzel, T.; Rigoll, G.: Performance Comparison of Deep Neural Network Quantizers to Continuous ASR Systems. Fortschritte der Akustik -- DAGA '19, 2019, pp. 947-949 more… Full text (mediaTUM)

Projects

Chinesisch-Deutsches Hochschulkolleg in Shanghai:
- supervision of double-degree program between TUM and Tongji University (since April 2017)

Student projects

For inquiries regarding any student projects please apply using your most recent CV together with your grade report emphasizing your previous experience in this area and your desired starting date.

Open Topics

You can find all open topics here.

Finished Projects

2019
• A Comparative Study of Pre-trained Language Models for Contextual Document Representation (Bachelor's Thesis)
• Sensorfusion und Zustandsschätzung auf Grundlage rauschbehafteter Messdaten (Research Internship)
• Wake-Up Word Recognition with DNNs (Research Internship)
• A comparison of techniques for language model integration in encoder-decoder speech recognition (Scientific Seminar)
• Framework Comparison of Tensorflow and Kaldi Using TDNN and LSTM for Hybrid Speech Recognition (Master's Thesis)
• Deep Reinforcement Learning for Decision Making in Autonomous Driving (Master's Thesis)
• Application of Gaussian Mixture VAE in Natural Language Processing (Research Internship)
• A Comparison of Techniques for Language Model Integration in Encoder-Decoder Speech Recognition (Scientific Seminar)

2018
• Entwicklung einer Sprachsteuerung für das Brettspiel “Professor Pünschge” (IDP)
• Application of MFCC Features in Speech Enhancement Generative Adversarial Network (Research Internship)
• Attacks on Neural Networks for Speech Recognition (Scientific Seminar)
• Improving ASR systems with E-Vectors (Scientific Seminar)
• Improved Training of End-to-End Attention Models for Speech Recognition (Scientific Seminar)
• Development of a Perception System for Autonomous Driving (Research Internship)