Annual Report 2010 - Fachgruppe Informatik an der RWTH Aachen ...

Overview
The ‘Lehrstuhl für Informatik 6’ is concerned with research on advanced methods for
statistical pattern recognition. The main application of these methods is in the field of
automatic processing of human language, i.e. the recognition of speech, the translation of
spoken and written language, the understanding of natural language and spoken dialogue
systems, and image and optical character recognition.
The general framework for the research activities is based on statistical decision theory and
problem specific modelling. The prototypical area where this approach has been pushed
forward is speech recognition. Here, the approach is expressed by the equation:
Speech Recognition = Acoustic-Linguistic Modelling + Statistical Decision Theory
The characteristic advantages of the probabilistic framework and statistical decision theory
are:
• The approach is able to model weak dependencies and vague knowledge at all levels of
the system.
• The free parameters of the models can be automatically learned from training data (or
examples), and there exist powerful algorithms for this purpose.
• Using the Bayes decision rule (as derived from statistical decision theory), the final
decision is made by taking all available context into account. For example, in large
vocabulary speech recognition, a sound is always recognized as a part of a word, which
itself is part of a sentence. This allows the optimal feedback from the syntactic-semantic
constraints of the language down to the level of sound recognition.
From speech recognition, we have extended and are still extending this approach to other
areas, in particular the translation of spoken and written language and other tasks in natural
language processing. For language translation, the approach is expressed by the equation:
Language Translation = Linguistic Modelling + Statistical Decision Theory
In addition, it offers a couple of advantages like increased robustness and easy adaptation to a
new task.
In summary, the research activities of the ‘Lehrstuhl für Informatik 6’ cover the following
applications:
• speech recognition
o large vocabulary recognition
o multi-lingual speech recognition
o speaker independent and adaptive speech recognition
o robust speech recognition
• machine translation of spoken and written language
• natural language processing
o document classification
o language understanding
o spoken dialogue systems
• part-of-speech tagging and text annotation
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