Bachelor Thesis

Recently, I have finished my bachelor thesis on the topic Machine Learning for Gesture Recognition. The paper is about principles of machine learning using decision trees, rulesets, functions or lazy algorithms, which are already implemented for the machine learning tool WEKA. For this usecase, I’ve developed a paint tool, where a user can record training data in form of geometrical symbols. This symbols can be found in the computer game “Black & White”, where the user can interact by drawing figures with the mouse. Also Opera has such a feature implemented. I used these figures (also complexer too), calculate attributes and evaluated various machine learning strategies, such as a RandomForest or a Multilayer Perceptron. This paper may be used as basics to implement gesture recognition for mobile phones with acceleration sensors.

You will find the paper online in a few days, so if you are interested in it, have a look and tell me what you think about.

Speech Processing

The last few days, I’ve worked on some speech processing stuff. Because I also wrote some examples, I will add some Matlab programs to do a spectrum and pitch analysis. Another tool provides functionality to recognize and differentiate female and male voices. These tools should provide a fundamental overview about speech processing and also machine learning strategies to do speech re