Where do thewords come from? Learning models for word choice and ordering from spoken dialog corpora
Amanda J. Stent, Srinivas Bangalore, Giuseppe Di Fabbrizio · IEEE International Conference on Acoustics Speech and Signal Processing · 2008
Most existing generation systems for spoken dialog require the system engineer to specify by hand the words to be used in system prompts. However, the existence of corpora of spoken dialog makes it possible to acquire the words and structure of system prompts automatically. In this paper, we construct statistical models for generating system prompts, both for word choice and for word ordering. We evaluate these models using a human-computer dialog multicorpus and a human-human dialog corpus. Our results show that statistical models for word choice can work well, while more work is needed on statistical models for word ordering.