Report
ADVISER: A Toolkit for Developing Multi-modal, Multi-domain and Socially-engaged Conversational Agents
| العنوان: | ADVISER: A Toolkit for Developing Multi-modal, Multi-domain and Socially-engaged Conversational Agents |
|---|---|
| المؤلفون: | Li, Chia-Yu, Ortega, Daniel, Väth, Dirk, Lux, Florian, Vanderlyn, Lindsey, Schmidt, Maximilian, Neumann, Michael, Völkel, Moritz, Denisov, Pavel, Jenne, Sabrina, Kacarevic, Zorica, Vu, Ngoc Thang |
| سنة النشر: | 2020 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language, Computer Science - Artificial Intelligence |
| الوصف: | 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 Comment: All authors contributed equally. Accepted to be presented at ACL - System demonstrations - 2020 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2005.01777 |
| رقم الانضمام: | edsarx.2005.01777 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |