Very short utterances in conversation

Abstract

Faced with the difficulties of finding an operationalized definition of backchannels, we have previously proposed an intermediate, auxiliary unit – the very short utterance (VSU) – which is defined operationally and is automatically extractable from recorded or ongoing dialogues. Here, we extend that work in the following ways: (1) we test the extent to which the VSU/NONVSU distinction corresponds to backchannels/non-backchannels in a different data set that is manually annotated for backchannels – the Columbia Games Corpus; (2) we examine to the extent to which VSUS capture other short utterances with a vocabulary similar to backchannels; (3) we propose a VSU method for better managing turn-taking and barge-ins in spoken dialogue systems based on detection of backchannels; and (4) we attempt to detect backchannels with better precision by training a backchannel classifier using durations and inter-speaker relative loudness differences as features. The results show that VSUS indeed capture a large proportion of backchannels – large enough that VSUs can be used to improve spoken dialogue system turntaking; and that building a reliable backchannel classifier working in real time is feasible.