scholarly journals Contextualize Knowledge Bases with Transformer for End-to-end Task-Oriented Dialogue Systems

2021 ◽  
Author(s):  
Yanjie Gou ◽  
Yinjie Lei ◽  
Lingqiao Liu ◽  
Yong Dai ◽  
Chunxu Shen
Keyword(s):  
Knowledge Bases ◽  
Dialogue Systems ◽  
End To End ◽  
Task Oriented

scholarly journals End-to-end optimization of goal-driven and visually grounded dialogue systems

2017 ◽  
Author(s):  
Florian Strub ◽  
Harm de Vries ◽  
Jérémie Mary ◽  
Bilal Piot ◽  
Aaron Courville ◽  
...  
Keyword(s):  
Gradient Algorithm ◽  
Planning Problem ◽  
Dialogue Systems ◽  
Generation Task ◽  
Policy Gradient ◽  
Specific Object ◽  
Complex Picture ◽  
History Of ◽  
End To End ◽  
Task Oriented

End-to-end design of dialogue systems has recently become a popular research topic thanks to powerful tools such as encoder-decoder architectures for sequence-to-sequence learning. Yet, most current approaches cast human-machine dialogue management as a supervised learning problem, aiming at predicting the next utterance of a participant given the full history of the dialogue. This vision may fail to correctly render the planning problem inherent to dialogue as well as its contextual and grounded nature. In this paper, we introduce a Deep Reinforcement Learning method to optimize visually grounded task-oriented dialogues, based on the policy gradient algorithm. This approach is tested on the question generation task from the dataset GuessWhat?! containing 120k dialogues and provides encouraging results at solving both the problem of generating natural dialogues and the task of discovering a specific object in a complex picture.

scholarly journals UniMF: A Unified Framework to Incorporate Multimodal Knowledge Bases intoEnd-to-End Task-Oriented Dialogue Systems

2021 ◽  
Author(s):  
Shiquan Yang ◽  
Rui Zhang ◽  
Sarah M. Erfani ◽  
Jey Han Lau
Keyword(s):  
Large Scale ◽  
Knowledge Bases ◽  
Language Models ◽  
Dialogue Systems ◽  
Unified Framework ◽  
Proposed Model ◽  
Multimodal Information ◽  
Task Oriented ◽  
Novel Model ◽  
Single Modality

Knowledge bases (KBs) are usually essential for building practical dialogue systems. Recently we have seen rapidly growing interest in integrating knowledge bases into dialogue systems. However, existing approaches mostly deal with knowledge bases of a single modality, typically textual information. As today's knowledge bases become abundant with multimodal information such as images, audios and videos, the limitation of existing approaches greatly hinders the development of dialogue systems. In this paper, we focus on task-oriented dialogue systems and address this limitation by proposing a novel model that integrates external multimodal KB reasoning with pre-trained language models. We further enhance the model via a novel multi-granularity fusion mechanism to capture multi-grained semantics in the dialogue history. To validate the effectiveness of the proposed model, we collect a new large-scale (14K) dialogue dataset MMDialKB, built upon multimodal KB. Both automatic and human evaluation results on MMDialKB demonstrate the superiority of our proposed framework over strong baselines.

scholarly journals Dialogue Learning with Human Teaching and Feedback in End-to-End Trainable Task-Oriented Dialogue Systems

2018 ◽  
Author(s):  
Bing Liu ◽  
Gokhan Tür ◽  
Dilek Hakkani-Tür ◽  
Pararth Shah ◽  
Larry Heck
Keyword(s):  
Dialogue Systems ◽  
End To End ◽  
Task Oriented

scholarly journals Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems

2020 ◽  
Author(s):  
Andrea Madotto ◽  
Samuel Cahyawijaya ◽  
Genta Indra Winata ◽  
Yan Xu ◽  
Zihan Liu ◽  
...  
Keyword(s):  
Knowledge Bases ◽  
Dialogue Systems ◽  
Task Oriented

Incorporating Specific Knowledge into End-to-End Task-oriented Dialogue Systems

2021 ◽  
Author(s):  
Qingyue Wang ◽  
Yanan Cao ◽  
Junyan Jiang ◽  
Yafang Wang ◽  
Lingling Tong ◽  
...  
Keyword(s):  
Dialogue Systems ◽  
Specific Knowledge ◽  
End To End ◽  
Task Oriented

End-to-End Task-Oriented Dialog System Through Template Slot Value Generation

2020 ◽  
Author(s):  
Teakgyu Hong ◽  
Oh-Woog Kwon ◽  
Young-Kil Kim
Keyword(s):  
Dialog System ◽  
End To End ◽  
Task Oriented
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