Speech Recognition Using Machine Learning
|Typ||Master, Forschungspraxis, IDP|
|Betreuer||Dipl.-Ing. (Univ.) Ludwig Kürzinger
Tel.: +49 (0)89 289-28562
Tobias Watzel, M.Sc.
Tel.: +49 (0)89 289-28547
|Sachgebiet||Speech Recognition, Machine Learning|
|Beschreibung||Speech Recognition enables a machine to understand human voice and convert it to text. State-ofthe-
art speech recognition systems are based on pattern recognition methods or end-to-end deep
learning, such as DeepSpeech .
Improving speech recognition, reducing its error rate and increasing its robustness against noise,
remains a challenge. It can be improved by using an appropriate learning algorithm and finding good
The main tasks for this topic will be to get familiar with the a speech recognition framework, to adapt
the framework and training your own model. Intermediate steps may include choosing a different loss
function or data augmentation.
Please contact the thesis supervisor for further details.
 2014, Deep Speech: Scaling up end-to-end speech recognition
|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.|