Dialog Methods for Improved Alphanumeric String Capture

摘要

In this paper, we consider advances in automated over-the-phone alphanumeric string capture. For this task, acoustic confusions typically result in significant error rates. Of course, confusions also exist in human-to-human communication. However, humans employ dialog-level strategies with which to disambiguate confusions and correct errors - allowing high-fidelity transmission of alphanumeric strings across all but the noisiest of channels. These human strategies are examined and a subset amenable to automation is identified. The resulting automated error-correction dialog achieves 30% dialog error rate reduction compared to a conventional application in a high-volume commercial deployment. Further, the fact that there are many recognition errors in the context of a structurally simple dialog recommends this task for dialog optimization. We present an example of offline optimization and discuss the potential for online learning.