The DialPort project this http URL, funded by the National Science
Foundation (NSF), covers a group of tools and services that aim at fulfilling
the needs of the dialog research community. Over the course of six years,
several offerings have been created, including the DialPort Portal and
DialCrowd. This paper describes these contributions, which will be demoed at
SIGDIAL, including implementation, prior studies, corresponding discoveries,
and the locations at which the tools will remain freely available to the
community going forward.

该研究论文介绍了 DialPort 项目，该项目旨在为对话研究社区提供工具和服务，其中包括 DialPort 门户网站和 DialCrowd。这些贡献将在 SIGDIAL 中进行演示，这些工具将继续在社区中免费提供。

DialPort 工具

The DialPort tools

The ultimate goal of dialog research is to develop systems that can be
effectively used in interactive settings by real users. To this end, we
introduced the Interactive Evaluation of Dialog Track at the 9th Dialog System
Technology Challenge. This track consisted of two sub-tasks. The first sub-task
involved building knowledge-grounded response generation models. The second
sub-task aimed to extend dialog models beyond static datasets by assessing them
in an interactive setting with real users. Our track challenges participants to
develop strong response generation models and explore strategies that extend
them to back-and-forth interactions with real users. The progression from
static corpora to interactive evaluation introduces unique challenges and
facilitates a more thorough assessment of open-domain dialog systems. This
paper provides an overview of the track, including the methodology and results.
Furthermore, it provides insights into how to best evaluate open-domain dialog
models

该论文介绍了针对开放领域对话系统的交互式评估方法，为开发基于知识的响应生成模型，探索将其扩展到与真实用户的交互中提供挑战，从而介绍了从静态语料库到交互式评估的进展，以及如何最好评估开放领域对话模型的见解。

DSTC9 中的对话跟踪交互式评估

Interactive Evaluation of Dialog Track at DSTC9

We introduce ParlAI (pronounced "par-lay"), an open-source software platform
for dialog research implemented in Python, available at this http URL Its
goal is to provide a unified framework for sharing, training and testing of
dialog models, integration of Amazon Mechanical Turk for data collection, human
evaluation, and online/reinforcement learning; and a repository of machine
learning models for comparing with others' models, and improving upon existing
architectures. Over 20 tasks are supported in the first release, including
popular datasets such as SQuAD, bAbI tasks, MCTest, WikiQA, QACNN, QADailyMail,
CBT, bAbI Dialog, Ubuntu, OpenSubtitles and VQA. Several models are integrated,
including neural models such as memory networks, seq2seq and attentive LSTMs.

介绍了 ParIAI 平台，一个用于对话研究的开源软件平台，具有统一框架，机器学习模型等特点，它支持多种任务和数据集，包括 Squad、bAbI 任务、MCTest、WikiQA、QACNN、QADailyMail、CBT、bAbI 对话、Ubuntu、OpenSubtitles 和 VQA，并集成了记忆网络，seq2seq 和注意 LSTM 等多个神经网络模型。