Paper: Using Automatically Transcribed Dialogs to Learn User Models in a Spoken Dialog System

ACL ID P08-2031
Title Using Automatically Transcribed Dialogs to Learn User Models in a Spoken Dialog System
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

We use an EM algorithm to learn user mod- els in a spoken dialog system. Our method requires automatically transcribed (with ASR) dialog corpora, plus a model of transcription errors, but does not otherwise need any man- ual transcription effort. We tested our method on a voice-controlled telephone directory ap- plication, and show that our learned models better replicate the true distribution of user ac- tions than those trained by simpler methods and are very similar to user models estimated from manually transcribed dialogs.