Abstract not found

We present a novel approach for the automatic translation of written text into sign language. A new corpus focussing on the weather report domain for the language pair German and German Sign Language is introduced. We apply phrase-based statistical machine translation, enhanced by pre- and post-processing steps based on the morpho-syntactical analysis of German. Detailed results are given based on automatic and manual evaluation. 1

In this work, the recent additions to the RWTH-Phoenix corpus, a data collection of interpreted news announcement, are analysed. The corpus features videos, gloss annotation of German Sign Language and transcriptions of spoken German. The annotation procedure is reported, and the corpus statistics are discussed. We present automatic machine translation results for both directions, and discuss syntactically motivated enhancements. 1.

This diploma thesis investigates appearance-based features for the person-independent vision-based recognition of continuous sign language. A large variety of methods which have been successfully used for automatic speech recognition is applied to this task. Appearance-based approaches do not rely on a segmentation of the images or on predefined models of the image content and use the image itself as the feature. A novel tracking algorithm is introduced and applied to hand and head tracking. The tracked body parts are used in order to calculate additional features to improve recognition performance. The presented automatic sign language recognition system is evaluated on a set of sentences in American Sign Language.

Sieh es mir nach, wenn ich weine. Acknowledgements I would like to express my deep gratitude towards Professor Hermann Ney, who granted me the possibility to, in his own words, build machines instead of pressing knobs and turning wheels. His proficiency in matters of science, his relentless search for the next step and his professionality in human interaction has been and will continue to be most inspiring. I would also like to sincerely thank co-supervisor Professor Andy Way for his kind hosting and general guidance during my stay in Dublin, as well as for his extensive feedback. I admit that he caught me a bit by surprise when he found my work truly interesting. Many thanks to Prof. Jarke, Prof. Lakemeyer and PD Unger, who in one way or the other were always there during my whole academic career and did not hesitate to support me for the viva. With profound admiration I would like to thank Davi(i)d “m-hm ” Vilar for being the best Yoda I have ever had. His contribution to my structural