OPERA: Harmonizing Task-Oriented Dialogs and Information Seeking Experience
Existing studies in conversational AI mostly treat task-oriented dialog (TOD) and question answering (QA) as separate tasks. Towards the goal of constructing a conversational agent that can complete user tasks and support information seeking, it is important to build a system that handles both TOD and QA with access to various external knowledge. In this work, we propose a new task, Open-Book TOD (OB-TOD), which combines TOD with QA task and expand external knowledge sources to include both explicit knowledge sources (e.g., the Web) and implicit knowledge sources (e.g., pre-trained language models). We create a new dataset OB-MultiWOZ, where we enrich TOD sessions with QA-like information seeking experience grounded on external knowledge. We propose a unified model OPERA (Open-book End-to-end Task-oriented Dialog) which can appropriately access explicit and implicit external knowledge to tackle the defined task. Experimental results demonstrate OPERA's superior performance compared to closed-book baselines and illustrate the value of both knowledge types.
Code (1)
Tasks
Question AnsweringSimilar Papers 제목 키워드 기반
Variational Hierarchical Dialog Autoencoder for Dialog State Tracking Data Augmentation
Recent works have shown that generative data augmentation, where synthetic samples generated from deep generative models complement the training dataset, benefit NLP tasks. In this work, we extend this approach to the ta…
Data Augmentationdialog state trackingDialogue State TrackingResponse Generation+2DialogStitch: Synthetic Deeper and Multi-Context Task-Oriented Dialogs
Real-world conversational agents must effectively handle long conversations that span multiple contexts. Such context can be interspersed with chitchat (dialog turns not directly related to the task at hand), and potenti…
CookDial: A dataset for task-oriented dialogs grounded in procedural documents
This work presents a new dialog dataset, CookDial, that facilitates research on task-oriented dialog systems with procedural knowledge understanding. The corpus contains 260 human-to-human task-oriented dialogs in which …
Decision MakingResponse GenerationContext-Aware Dialog Re-Ranking for Task-Oriented Dialog Systems
Dialog response ranking is used to rank response candidates by considering their relation to the dialog history. Although researchers have addressed this concept for open-domain dialogs, little attention has been focused…
Re-Rankingspeech-recognitionSpeech RecognitionEnd-to-End Learning of Flowchart Grounded Task-Oriented Dialogs
We propose a novel problem within end-to-end learning of task-oriented dialogs (TOD), in which the dialog system mimics a troubleshooting agent who helps a user by diagnosing their problem (e.g., car not starting). Such …
Flowchart Grounded Dialog Response GenerationRetrievalRetrieval-augmented GenerationZero-Shot Flowchart Grounded Dialog Response Generation