Sixth International Conference on Spoken Language Processing
(ICSLP 2000)

Beijing, China
October 16-20, 2000

An Automatic Speech Recognition System Using Neural Networks and Linear Dynamic Models to Recover and Model Articulatory Traces

Joe Frankel, Korin Richmond, Simon King, Paul Taylor

Centre for Speech Technology Research, University of Edinburgh, Edinburgh, UK

We describe a speech recognition system which uses articulatory parameters as basic features and phone-dependent linear dynamic models. The system first estimates articulatory trajectories from the speech signal. Estimations of x and y coordinates of 7 actual articulator positions in the midsagittal plane are produced every 2 milliseconds by a recurrent neural network, trained on real articulatory data. The output of this network is then passed to a set of linear dynamic models, which perform phone recognition.

Full Paper

Bibliographic reference.  Frankel, Joe / Richmond, Korin / King, Simon / Taylor, Paul (2000): "An automatic speech recognition system using neural networks and linear dynamic models to recover and model articulatory traces", In ICSLP-2000, vol.4, 254-257.