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Deep Learning for Dialogue Systems

Yun-Nung Chen, Asli Celikyilmaz, Dilek Hakkani-Tür
2017 Proceedings of ACL 2017, Tutorial Abstracts  
Hence, this tutorial is designed to focus on an overview of the dialogue system development while describing most recent research for building dialogue systems and summarizing the challenges, in order  ...  The classic dialogue systems have rather complex and/or modular pipelines. The advance of deep learning technologies has recently risen the applications of neural models to dialogue modeling.  ...  management (DM) -Dialogue state tracking (DST) -Neural belief tracker -Multichannel trackerDialogue management (DM) -Policy optimization -Dialogue RL signal -Deep Q-network for learning policy  ... 
doi:10.18653/v1/p17-5004 dblp:conf/acl/ChenCH17 fatcat:eyltpy5guna6bfsczav3vji7x4

Speech-gesture driven multimodal interfaces for crisis management

R. Sharma, M. Yeasin, N. Krahntoever, I. Rauschert, Guoray Cai, I. Brewer, A.M. Maceachren, K. Sengupta
2003 Proceedings of the IEEE  
for CM.  ...  Dialogue-enabled devices, based on natural, multimodal interfaces have the potential of making a variety of information technology tools accessible during crisis management.  ...  Multi-user collaboration: New multimodal systems are expected to function more robustly and adaptively, and with support for collaborative multi-person use.  ... 
doi:10.1109/jproc.2003.817145 fatcat:flbaisvreresla7wufztzpnvfq

A Survey on Dialogue Systems: Recent Advances and New Frontiers [article]

Hongshen Chen, Xiaorui Liu, Dawei Yin, Jiliang Tang
2018 arXiv   pre-print
Dialogue systems have attracted more and more attention.  ...  For dialogue systems, deep learning can leverage a massive amount of data to learn meaningful feature representations and response generation strategies, while requiring a minimum amount of hand-crafting  ...  [59] proposed a neural belief tracker (NBT) to detect the slot-value pairs.  ... 
arXiv:1711.01731v3 fatcat:6wuovcynqbhlzmuorchn4mn6ma

An Overview of Natural Language State Representation for Reinforcement Learning [article]

Brielen Madureira, David Schlangen
2020 arXiv   pre-print
We appeal for more linguistically interpretable and grounded representations, careful justification of design decisions and evaluation of the effectiveness of different approaches.  ...  Acknowledgments We thank the two anonymous reviewers for their feedback and suggestions.  ...  Dhingra et al. (2017) compared a handcrafted and a neural belief tracker that uses a GRU over turns. The belief state was sometimes combined with other representations.  ... 
arXiv:2007.09774v1 fatcat:rlcplc3u5ncljacugblczaidpa

Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey [article]

Jinjie Ni, Tom Young, Vlad Pandelea, Fuzhao Xue, Erik Cambria
2022 arXiv   pre-print
Furthermore, we comprehensively review the evaluation methods and datasets for dialogue systems to pave the way for future research.  ...  We speculate that this work is a good starting point for academics who are new to the dialogue systems or those who want to quickly grasp up-to-date techniques in this area.  ...  Domain Transfer for DST Domain adaptability is also a significant topic for dialogue state trackers.  ... 
arXiv:2105.04387v5 fatcat:yd3gqg45rjgzxbiwfdlcvf3pye

2021 Index IEEE/ACM Transactions on Audio, Speech, and Language Processing Vol. 29

2021 IEEE/ACM Transactions on Audio Speech and Language Processing  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, TASLP 2021 782-791 Domain-Aware Dialogue State Tracker for Multi-Domain Dialogue Systems.  ...  ., +, TASLP 2021 3617-3630 Ontologies (artificial intelligence) Domain-Aware Dialogue State Tracker for Multi-Domain Dialogue Systems.  ... 
doi:10.1109/taslp.2022.3147096 fatcat:7nl52k7sjfalbhpxtum3y5nmje

Modelling Multimodal Dialogues for Social Robots Using Communicative Acts

Enrique Fernández-Rodicio, Álvaro Castro-González, Fernando Alonso-Martín, Marcos Maroto-Gómez, Miguel Á. Salichs
2020 Sensors  
Consequently, dialogue design is a key factor in creating an engaging multimodal interaction.  ...  This system has been integrated in Mini, a social robot that has been created to assist older adults with cognitive impairment.  ...  Instead of explicitly modelling dialogues through belief and user intent trackers, they use learned neural representations for implicit modelling of dialogue state.  ... 
doi:10.3390/s20123440 pmid:32570807 pmcid:PMC7348960 fatcat:7svhfs4vw5bdtoebpbwod3ucvy

Multimodal Dialogue State Tracking [article]

Hung Le, Nancy F. Chen, Steven C.H. Hoi
2022 arXiv   pre-print
Designed for tracking user goals in dialogues, a dialogue state tracker is an essential component in a dialogue system.  ...  Together with comprehensive ablation and qualitative analysis, we discovered interesting insights towards building more capable multimodal dialogue systems.  ...  Another variant of the model is enhanced with a vanilla dot-product attention at each decoding step; • We adapted and experimented with strong unimodal DST baselines, including: TRADE , UniConv (Le et  ... 
arXiv:2206.07898v1 fatcat:dauljflkovb77dm54zvlgtujqa

Slot Self-Attentive Dialogue State Tracking

Fanghua Ye, Jarana Manotumruksa, Qiang Zhang, Shenghui Li, Emine Yilmaz
2021 Proceedings of the Web Conference 2021  
Neural Belief Tracker: Data-Driven Dialogue State Tracking. [57] Puhai Yang, Heyan Huang, and Xian-Ling Mao. 2020.  ...  An end-to-end dialogue state tracking system Guided Multi-Domain Dialogue State Tracking with Graph Attention Neural with machine reading comprehension and wide & deep classification  ... 
doi:10.1145/3442381.3449939 fatcat:rv2fqzystrblfjmjfs56xul2ry

Real-time decision making in multimodal face-to-face communication

Kristinn R. Thórisson
1998 Proceedings of the second international conference on Autonomous agents - AGENTS '98  
Gandalf can engage in taskoriented dialogue with a person and has been shown capable of fluid turn-taking and multimodal interaction [40] .  ...  It is part of a broad computational model of psychosocial dialogue skills called Ymir . The architecture has been tested with a prototype humanoid, Gandalf [34] [35] .  ...  The principles of these architectures are very useful for real-time multimodal communication systems. Working on a piece of the multimodal puzzle, Cassell et al.  ... 
doi:10.1145/280765.280769 dblp:conf/agents/Thorisson98 fatcat:tzpyifqsvnf3vlb2u2kyras37i

Neural Approaches to Conversational AI [article]

Jianfeng Gao, Michel Galley, Lihong Li
2019 arXiv   pre-print
We group conversational systems into three categories: (1) question answering agents, (2) task-oriented dialogue agents, and (3) chatbots.  ...  For each category, we present a review of state-of-the-art neural approaches, draw the connection between them and traditional approaches, and discuss the progress that has been made and challenges still  ...  Figure 4 . 4 4: A bLSTM model for joint optimization in NLU. Picture credit: Hakkani-Tür et al. (2016). Figure 4 . 5 : 45 Neural Belief Tracker.  ... 
arXiv:1809.08267v3 fatcat:j57xlm4ogferdnrpfs4f2jporq

A Survey of Available Corpora for Building Data-Driven Dialogue Systems [article]

Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, Joelle Pineau
2017 arXiv   pre-print
To facilitate research in this area, we have carried out a wide survey of publicly available datasets suitable for data-driven learning of dialogue systems.  ...  In the area of dialogue systems, the trend is less obvious, and most practical systems are still built through significant engineering and expert knowledge.  ...  The authors also thank Nissan Pow, Michael Noseworthy, Chia-Wei Liu, Gabriel Forgues, Alessandro Sordoni, Yoshua Bengio and Aaron Courville for helpful discussions.  ... 
arXiv:1512.05742v3 fatcat:lh34cnbvefcfxp2qwxfyiuuwhm

How Can High-Frequency Sensors Capture Collaboration? A Review of the Empirical Links between Multimodal Metrics and Collaborative Constructs

Bertrand Schneider, Gahyun Sung, Edwin Chng, Stephanie Yang
2021 Sensors  
Based on our review, we highlight gaps in the literature and discuss opportunities for the field of MMCA, concluding with future work for this project.  ...  For the scope of this paper, we focus on: (1) the sensor-based metrics computed from multimodal data sources (e.g., speech, gaze, face, body, physiological, log data); (2) outcome measures, or operationalizations  ...  Among these ten papers, four were empirical studies of joint visual attention using multiple eye-trackers [84,127–129]; two papers were reviews (of the use of multimodal data  ... 
doi:10.3390/s21248185 pmid:34960278 pmcid:PMC8706197 fatcat:puclqibmhvew7aadu3xwgse2ly

A Review on Automatic Facial Expression Recognition Systems Assisted by Multimodal Sensor Data

Samadiani, Huang, Cai, Luo, Chi, Xiang, He
2019 Sensors  
Also, we discuss the methods of fusing different inputs obtained from multimodal sensors in an emotion system.  ...  With the emerging advanced technologies in hardware and sensors, FER systems have been developed to support real-world application scenes, instead of laboratory environments.  ...  Also, they have used Deep belief network (DBN) as a classifier to perform faster than a common deep neural network (DNN). However, it is not suitable for running in a general system without a GPU.  ... 
doi:10.3390/s19081863 fatcat:bqsx53jtwvf23cs6ykpfi7qqga

DR 4.4: Natural Multimodal Interaction Final Pro- totype

Bernd Kiefer, Ivana Kruijff-Korbayova, Anna Welker, Rifca Peters, Sarah McLeod
2019 Zenodo  
The dialogue policies and the linguistic resources have been adapted accordingly.  ...  Furthermore, support for an experiment with different interaction styles, using modulated gestures, has been added, and the VOnDA compiler and run-time system has been heavily improved.  ...  Acknowledgements The research described in this paper has been funded by the Horizon 2020 Framework Programme of the European Union within the project PAL (Personal Assistant for healthy Lifestyle) under  ... 
doi:10.5281/zenodo.3443669 fatcat:ez7jk76vmncshlzoivgqftx4ji
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