Towards measuring continuous acoustic feature convergence in unconstrained spoken dialogues

Acoustic/prosodic feature (a/p) convergence has been known to occur both in dialogues between humans, as well as in human-computer interactions. Understanding the form and function of convergence is desirable for developing next generation conversational agents, as this will help increase speech recognition performance and naturalness of synthesized speech. Currently, the underlying mechanisms by which continuous and bi-directional convergence occurs are not well understood. In this study, a direct comparison between time-aligned frames shows significant similarity in acoustic feature variation between the two speakers. The method described (TAMA) constitutes a first step towards a quantitative analysis of a/p convergence.