EUROSPEECH 2001 Scandinavia
7th European Conference on Speech Communication and Technology

Aalborg, Denmark
September 3-7, 2001


ASR - Articulatory Speech Recognition

Joe Frankel, Simon King

University of Edinburgh, UK

We propose that using a continuous trajectory model to describe an articulatory-based feature set will address some of the shortcomings inherent in the hidden Markov model (HMM) as a model for speech recognition. The articulatory parameters allow us to explicitly model effects such as co-articulation and assimilation. A linear dynamic model (LDM) is used to capture the characteristics of each segment type. These models are well suited to describing smoothly varying, continuous, yet noisy trajectories, such as we find present in speech data. Experimentation has been based on data for a single speaker from the MOCHA corpus. This consists of parallel acoustic and recorded articulatory parameters for 460 TIMIT sentences. We report the results of classification and recognition tasks using both real and recovered articulatory parameters, on their own and in conjunction with acoustic features.

Full Paper

Bibliographic reference.  Frankel, Joe / King, Simon (2001): "ASR - articulatory speech recognition", In EUROSPEECH-2001, 599-602.