Thema
Speech Recognition Using Machine Learning
Typ Master, Forschungspraxis, IDP
Betreuer Dipl.-Ing. (Univ.) Ludwig Kürzinger
Tel.: +49 (0)89 289-28562
E-Mail: ludwig.kuerzinger@tum.de
oder
Tobias Watzel, M.Sc.
Tel.: +49 (0)89 289-28547
E-Mail: tobias.watzel@tum.de
Sachgebiet Speech Recognition, Machine Learning
Beschreibung Speech Recognition enables a machine to understand human voice and convert it to text. State-of-the-art speech recognition systems are based on a combination of neural networks and hidden markov models. Modern speech recognition systems have already matured, with many methods to reduce error rates and improve the robustness against noise.
However, in the light of recent advances in machine learning, modern methods can be applied to speech recognition, for example, (deep) neural network vector-quantizers, generative adversarial
networks (GANs) or attention-based neural networks.

The main task will be about using neural networks for the acoustic model in speech recognition.
Neural networks will be trained in the kaldi [1] speech recognition framework and Pytorch or Tensorflow.

For more information about the topic, please contact the supervisor.

[1] github.com/kaldi-asr/kaldi
Voraussetzung - Experience with Python and/or C++
- Experience in machine learning
- Independent work style
- Motivation to learn new concepts
Bewerbung If you are interested in this topic, we welcome the applications via the email address above. Please set the email subject to "<Type of application> application for topic 'XYZ'", ex. "Master’s thesis application for topic 'XYZ'", while clearly specifying why are you interested in the topic in the text of the message. Also make sure to attach your most recent CV (if you have one) and grade report.