Abstract

Prosody is an important cue for identifying dialog acts. In this paper, we show that modeling the sequence of acoustic–prosodic values as n-gram features with a maximum entropy model for dialog act (DA) tagging can perform better than conventional approaches that use coarse representation of the prosodic contour through summative statistics of the prosodic contour. The proposed scheme for exploiting prosody results in an absolute improvement of 8.7% over the use of most other widely used representations of acoustic correlates of prosody. The proposed scheme is discriminative and exploits context in the form of lexical, syntactic and prosodic cues from preceding discourse segments. Such a decoding scheme facilitates online DA tagging and offers robustness in the decoding process, unlike greedy decoding schemes that can potentially propagate errors. Our approach is different from traditional DA systems …

Date

2009

Authors

Vivek Kumar Rangarajan Sridhar, Srinivas Bangalore, Shrikanth Narayanan

Journal

Computer Speech & Language

Volume

23

Issue

4

Pages

407-422

Publisher

Academic Press