This paper introduces a new approach to morpho-syntactic analysis through Humor 99 (High-speed Unification Mo.rphology), a reversible and unification-based morphological analyzer which has already been integrated with a variety of industrial applications.Humor 99 successfully copes with problems of agglutinative (e.g.Hungarian, Turkish, Estonian) and other (highly) inflectional languages (e.g.Polish, Czech, German) very effectively.The authors conclude the paper by arguing that the approach used in Humor 99 is general enough to be well suitable for a wide range of languages, and can serve as basis for higher-level linguistic operations such as shallow parsing.

This paper describes a multi-modal person verification system using speech and frontal face images. We consider two different speaker verification algorithms, a text-independent method using a second-order statistical measure and a text-dependent method based on hidden Markov modelling, as well as a face verification technique using a robust form of corellation. Fusion of the different recognition modules is performed by a Support Vector Machine classifier. Experimental results obtained on the audio-visual database XM2VTS for individual modalities and their combinations show that multimodal systems yield better performances than individual modules for all cases.