Departmental Papers (CIS)

Date of this Version

December 2007

Document Type

Journal Article

Comments

Copyright 2007 IEEE. Reprinted from IEEE Workshop on Automatic Speech Recognition and Understanding, 2007, ASRU, December 2007, pages 201-206.

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Abstract

In natural speech people use different levels of prominence to signal which parts of an utterance are especially important. Contrastive elements are often produced with stronger than usual prominence and their presence modifies the meaning of the utterance in subtle but important ways. We use a richly annotated corpus of conversational speech to study the acoustic characteristics of contrastive elements and the differences between them and words at other levels of prominence. We report our results for automatic detection of contrastive elements based on acoustic and textual features, finding that a baseline predicting nouns and adjectives as contrastive performs on par with the best combination of features. We achieve a much better performance in a modified task of detecting contrastive elements among words that are predicted to bear pitch accent.

Keywords

contrastive elements, discourse understanding, focus detection

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Date Posted: 16 July 2008

This document has been peer reviewed.