In this paper we demonstrate the feasibility and usefulness of articul
ation-based approaches in two major areas of speech technology: speech
recognition and speech synthesis. Our articulatory recognition model
estimates probabilities of categories of manner and place of articulat
ion, which establish the articulatory feature vector. The transformati
on from the articulatory level to the symbolic level is performed by h
idden Markov models or multi-layer perceptrons. Evaluations show that
the articulatory approach is a good basis for speaker-independent and
speaker-adaptive speech recognition. We are now working on a more real
istic articulatory model for speech recognition. An algorithm based on
an analysis by synthesis model maps the acoustic signal to 10 articul
atory parameters which describe the position of the articulators. EMA
(electro-magnetic articulograph) measurements recorded at the Universi
ty of Munich provide good initial estimates of tongue coordinates. In
order to improve articulatory speech synthesis we investigated an accu
rate physical model for the generation of the glottal source with the
aid of a numerical simulation. This model takes into account nonlinear
vortical flow and its interaction with soundwaves. The simulation res
ults can be used to improve the articulatory synthesis model developed
by Ishizaka and Flanagan (1972).