DialPort: Connecting the Spoken Dialog Research Community to Real User Data
Tiancheng Zhao Kyusong Lee Maxine Eskenazi Thanks: Both authors equally contributed to this work Affiliation: Language Technologies Institute, Carnegie Mellon University Affiliation: Language Technologies Institute, Carnegie Mellon University Affiliation: Pohang University of Science and Technology Affiliation:
Abstract
This paper describes a new spoken dialog portal that connects systems produced by the spoken dialog academic research community and gives them access to real users. We introduce a distributed, multi-modal, multi-agent prototype dialog framework that affords easy integration with various remote resources, ranging from end-to-end dialog systems to external knowledge APIs. To date, the DialPort portal has successfully connected to the multi-domain spoken dialog system at Cambridge University, the NOAA (National Oceanic and Atmospheric Administration) weather API and the Yelp API.
原文 arXiv:1606.02562;中英对照 + 大白话阅读 https://aha.fim.ai/paper/1606.02562v1