# DialPort: Connecting the Spoken Dialog Research Community to Real User Data

arXiv: https://arxiv.org/abs/1606.02562 · HTML: https://mlsanity.com/paper/1606.02562/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Jun 2016.

## Built on by (most cited first, 5 of 5)

- [OmAgent: A Multi-modal Agent Framework for Complex Video Understanding with Task Divide-and-Conquer](https://mlsanity.com/paper/2406.16620/) (2024)
- [Interactive Evaluation of Dialog Track at DSTC9](https://mlsanity.com/paper/2207.14403/) (2022)
- [A Unified Pre-training Framework for Conversational AI](https://mlsanity.com/paper/2105.02482/) (2021)
- [WeChat AI & ICT's Submission for DSTC9 Interactive Dialogue Evaluation Track](https://mlsanity.com/paper/2101.07947/) (2021)
- [The DialPort tools](https://mlsanity.com/paper/2208.10918/) (2022)

## 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.