DialPort: Connecting the Spoken Dialog Research Community to Real User Data
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 13 Oct 2026). First posted on arXiv 8 Jun 2016.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 0; 2024: 1.
5 papers.
- 2024OmAgent: A Multi-modal Agent Framework for Complex Video Understanding with Task Divide-and-Conquercited by 34
- 2022Interactive Evaluation of Dialog Track at DSTC9cited by 9
- 2021A Unified Pre-training Framework for Conversational AIcited by 2
- 2021WeChat AI & ICT's Submission for DSTC9 Interactive Dialogue Evaluation Trackcited by 0
- 2022The DialPort toolscited by 0
- 2024OmAgent: A Multi-modal Agent Framework for Complex Video Understanding with Task Divide-and-Conquer24 Jun 2024
- 2022The DialPort tools18 Aug 2022
- 2022Interactive Evaluation of Dialog Track at DSTC928 Jul 2022
- 2021A Unified Pre-training Framework for Conversational AI6 May 2021
- 2021WeChat AI & ICT's Submission for DSTC9 Interactive Dialogue Evaluation Track20 Jan 2021