论文标题
顾问：一种用于开发多模式，多域和社会参与对话代理商的工具包
ADVISER: A Toolkit for Developing Multi-modal, Multi-domain and Socially-engaged Conversational Agents
论文作者
论文摘要
We present ADVISER - an open-source, multi-domain dialog system toolkit that enables the development of multi-modal (incorporating speech, text and vision), socially-engaged (e.g. emotion recognition, engagement level prediction and backchanneling) conversational agents.我们工具包的最终实施是灵活的，易于使用的，并且不仅易于用于技术经验丰富的用户，例如机器学习研究人员，而且对于技术经验不足的用户（例如语言学家或认知科学家），从而为协作研究提供了一个灵活的平台。链接到开源代码：https：//github.com/digitalphonetics/adviser
We present ADVISER - an open-source, multi-domain dialog system toolkit that enables the development of multi-modal (incorporating speech, text and vision), socially-engaged (e.g. emotion recognition, engagement level prediction and backchanneling) conversational agents. The final Python-based implementation of our toolkit is flexible, easy to use, and easy to extend not only for technically experienced users, such as machine learning researchers, but also for less technically experienced users, such as linguists or cognitive scientists, thereby providing a flexible platform for collaborative research. Link to open-source code: https://github.com/DigitalPhonetics/adviser
