DocumentCode :
2659760
Title :
Caller Experience: A method for evaluating dialog systems and its automatic prediction
Author :
Evanini, K. ; Hunter, P. ; Liscombe, J. ; Suendermann, D. ; Dayanidhi, K. ; Pieraccini, R.
Author_Institution :
SpeechCycle Inc., New York, NY
fYear :
2008
fDate :
15-19 Dec. 2008
Firstpage :
129
Lastpage :
132
Abstract :
In this paper we introduce a subjective metric for evaluating the performance of spoken dialog systems, caller experience (CE). CE is a useful metric for tracking the overall performance of a system in deployment, as well as for isolating individual problematic calls in which the system underperforms. The proposed CE metric differs from most performance evaluation metrics proposed in the past in that it is a) a subjective, qualitative rating of the call, and b) provided by expert, external listeners, not the callers themselves. The results of an experiment in which a set of human experts listened to the same calls three times are presented. The fact that these results show a high level of agreement among different listeners, despite the subjective nature of the task, demonstrates the validity of using CE as a standard metric. Finally, an automated rating system using objective measures is shown to perform at the same high level as the humans. This is an important advance, since it provides a way to reduce the human labor costs associated with producing a reliable CE.
Keywords :
interactive systems; prediction theory; software performance evaluation; automatic prediction; caller experience; performance evaluation metrics; spoken dialog systems; Business; Costs; Humans; Investments; Performance evaluation; Robustness; Usability; classification; inter-rater agreement; performance evaluation; spoken dialog systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Spoken Language Technology Workshop, 2008. SLT 2008. IEEE
Conference_Location :
Goa
Print_ISBN :
978-1-4244-3471-8
Electronic_ISBN :
978-1-4244-3472-5
Type :
conf
DOI :
10.1109/SLT.2008.4777857
Filename :
4777857
Link To Document :
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