Papers by Lama Nachman
Data Augmentation with Paraphrase Generation and Entity Extraction for Multimodal Dialogue System (2022.lrec-1)
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| Challenge: | Contextually aware intelligent agents are often required to understand the users and their surroundings in real-time. |
| Approach: | They propose to build a multimodal dialogue system for children learning basic math concepts using limited datasets. |
| Outcome: | The proposed system improves the Natural Language Understanding (NLU) module of a task-oriented SDS pipeline with limited dataset resources. |
Cue-bot: A Conversational Agent for Assistive Technology (2022.acl-demo)
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Shachi H Kumar, Hsuan Su, Ramesh Manuvinakurike, Maximilian C. Pinaroc, Sai Prasad, Saurav Sahay, Lama Nachman
| Challenge: | Large-scale pre-training has achieved significant performance gains across many tasks within NLP, including intent prediction and dialogue state tracking. |
| Approach: | They propose to use eye-tracking, mouse controls and an intelligent agent Cue-bot to represent the user in a conversation. |
| Outcome: | The proposed system can be used by people with different levels of disabilities to interact with the world, supported by eye-tracking, mouse controls and an intelligent agent Cue-bot. |