Automatically Training a Problematic Dialogue Predictor for a Spoken Dialogue System

Details Automatically Training a Problematic Dialogue Predictor for a Spoken Dialogue System Automatically Training a Problematic Dialogue Predictor for a Spoken Dialogue System

2011-06-09

arxiv.org/abs/1106.1817v1

Journal Of Artificial Intelligence Research, Volume 16, pages 293-319, 2002

Computer Science

Artificial Intelligence

Scientific paper

10.1613/jair.971

Spoken dialogue systems promise efficient and natural access to a large variety of information sources and services from any phone. However, current spoken dialogue systems are deficient in their strategies for preventing, identifying and repairing problems that arise in the conversation. This paper reports results on automatically training a Problematic Dialogue Predictor to predict problematic human-computer dialogues using a corpus of 4692 dialogues collected with the 'How May I Help You' (SM) spoken dialogue system. The Problematic Dialogue Predictor can be immediately applied to the system's decision of whether to transfer the call to a human customer care agent, or be used as a cue to the system's dialogue manager to modify its behavior to repair problems, and even perhaps, to prevent them. We show that a Problematic Dialogue Predictor using automatically-obtainable features from the first two exchanges in the dialogue can predict problematic dialogues 13.2% more accurately than the baseline.

Affiliated with

Also associated with

No associations

Rating

Automatically Training a Problematic Dialogue Predictor for a Spoken Dialogue System does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Automatically Training a Problematic Dialogue Predictor for a Spoken Dialogue System, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Automatically Training a Problematic Dialogue Predictor for a Spoken Dialogue System will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-580340