This study examines emotion-specific information (ESI) in the articulatory movements estimated using acoustic-to-articulatory inversion on emotional speech. We study two main aspects: (1) the degree of similarity between the pair of estimated and original articulatory trajectories for the same and different emotions and (2) the amount of ESI present in the estimated trajectory. They are evaluated using mean squared error between the articulatory pair and by automated emotion classification. This study uses parallel acoustic and articulatory data in 5 elicited emotions spoken by 3 native American English speakers. We also test emotion classification performance using articulatory trajectories estimated from different acoustic feature sets and they turn out subject-dependent. Experimental results suggest that the ESI in the estimated trajectory, although smaller than that in the direct articulatory measurements, is found to be complementary to that in the prosodic features and hence, suggesting the usefulness of estimated articulatory data for emotions research. © 2012 APSIPA.