Papers by Daniel Ortega
ADVISER: A Dialog System Framework for Education & Research (P19-3)
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Daniel Ortega, Dirk Väth, Gianna Weber, Lindsey Vanderlyn, Maximilian Schmidt, Moritz Völkel, Zorica Karacevic, Ngoc Thang Vu
| Challenge: | In this paper, we focus on task-oriented dialog systems, although our framework allows easy integration of non-task dialog systems and their combination. |
| Approach: | They propose an open source dialog system framework for education and research that supports multi-domain task-oriented conversations in two languages. |
| Outcome: | The proposed framework supports multi-domain task-oriented conversations in two languages and is open source for education and research. |
Toward Implicit Reference in Dialog: A Survey of Methods and Data (2022.aacl-main)
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| Challenge: | In natural language, speakers often leave out information that is understood by the other party through the shared context. |
| Approach: | They propose to use omitted entities as implicit references in dialogs to improve language processing. |
| Outcome: | The proposed method is based on a set of experiments which show that the proposed method has a high level of accuracy and is a success. |
ADVISER: A Toolkit for Developing Multi-modal, Multi-domain and Socially-engaged Conversational Agents (2020.acl-demos)
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Chia-Yu Li, Daniel Ortega, Dirk Väth, Florian Lux, Lindsey Vanderlyn, Maximilian Schmidt, Michael Neumann, Moritz Völkel, Pavel Denisov, Sabrina Jenne, Zorica Kacarevic, Ngoc Thang Vu
| Challenge: | Existing toolkits for developing dialog systems are limited to core components and do not support multi-modal processing and social signals. |
| Approach: | They propose to use ADVISER to develop multi-modal dialog agents using multi-text and social signals. |
| Outcome: | The proposed toolkit is flexible, easy to use, and easy to extend for linguists and cognitive scientists, thereby providing a flexible platform for collaborative research. |