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ADVISER: A Toolkit for Developing Multi-modal, Multi-domain and Socially-engaged Conversational Agents. (arXiv:2005.01777v1 [cs.CL])

Date:

[Submitted on 4 May 2020]

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Abstract: 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: this https URL

Submission history

From: Ngoc Thang Vu [view email]
[v1]
Mon, 4 May 2020 18:27:58 UTC (1,646 KB)

Source: http://arxiv.org/abs/2005.01777

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