A paper "Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems" by Prof. Pascale FUNG and her team (Chien-Sheng WU, Andrea MADOTTO, Ehsan HOSSEINI-ASL, Caiming XIONG, Richard SOCHER) received Outstanding Paper Award in the 57th Annual Meeting of the Association for Computational Linguistics held in Florence, Italy in 28 July - 2 Aug, 2019. Only 5 out of 3,800 submissions were presented this award.
The Awarded Paper
Chien-Sheng Wu, Andrea Madotto, Ehsan Hosseini-Asl, Caiming Xiong, Richard Socher, Pascale Fung. "Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems". Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019). 808-819. Association for Computational Linguistics. Jul 2019.
Over-dependence on domain ontology and lack of sharing knowledge across domains are two practical and yet less studied problems of dialogue state tracking. Existing approaches generally fall short when tracking unknown slot values during inference and often have difficulties in adapting to new domains. In this paper, we propose a Transferable Dialogue State Generator (TRADE) that generates dialogue states from utterances using copy mechanism, facilitating transfer when predicting (domain, slot, value) triplets not encountered during training. Our model is composed of an utterance encoder, a slot gate, and a state generator, which are shared across domains. Empirical results demonstrate that TRADE achieves state-of-the-art 48.62% joint goal accuracy for the five domains of MultiWOZ, a human-human dialogue dataset. In addition, we show the transferring ability by simulating zero-shot and few-shot dialogue state tracking for unseen domains. TRADE achieves 60.58% joint goal accuracy in one of the zero-shot domains, and is able to adapt to few-shot cases without forgetting already trained domains. (Source: https://www.aclweb.org/anthology/P19-1078)
Invited Talk by Prof. Pascale FUNG in ACL 2019
"Loquentes Machinae: Technical Approaches, Applications and Ethical Issues of Conversational Systems"
From HAL in “2001:Space Odyssey” to Samantha in “Her”, conversational systems have always captured the public’s imagination as the ultimate intelligent machine. The famous Turing Test was designed to determine whether a machine “thinks” like human or not, based on natural conversation between human and a machine. With the advent of smart devices, conversational systems are suddenly everywhere, talking and responding to us from our phones, speakers, cars and call centers. Meanwhile, the public is also becoming increasingly concerned about privacy and security issues of these systems.
In the decades since the first DARPA Communicator project, conversational systems come in many different forms. Whereas research systems are predominantly based on deep learning approaches today, most of the commercial systems from the US and Asia are still using template-based and retrieval-based approaches.
Recent advances in such systems include endowing them with the ability to (1) learn to memorize; (2) learn to personalize; and (3) learn to empathize. In all aspects of R&D in this area, we encounter the challenge of a lack of well-balanced and well-labeled data. Hence, multi-task and meta-learning have been proposed as possible solutions.
In this talk, I will give an overview of some of the technical challenges, approaches and applications of conversational systems, and the debates on ethical issues surrounding them. I will also highlight some of the cultural differences in this area and discuss how we can collaborate internationally to build conversational systems that are secure, safe, and fair for all.
The Association for Computational Linguistics (ACL)
"The 58th annual meeting of the Association for Computational Linguistics (ACL) will take place in Seattle, Washington at the Hyatt Regency Seattle in downtown Seattle from July 5th through July 10th, 2020.
ACL is the premier conference of the field of computational linguistics, covering a broad spectrum of diverse research areas that are concerned with computational approaches to natural language."
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