Dialog Systems 2018


Notes:

  • dialog system
  • dialog systems
  • dialogue system
  • dialogue systems

Wikipedia:

See also:

Dialog Systems Meta GuideNatural Language Processors 2018


Augmenting end-to-end dialogue systems with commonsense knowledge
T Young, E Cambria, I Chaturvedi, H Zhou… – Thirty-Second AAAI …, 2018 – aaai.org
Building dialogue systems that can converse naturally with humans is a challenging yet intriguing problem of artificial intelligence. In open-domain human-computer conversation, where the conversational agent is expected to respond to human utterances in an …

Ruber: An unsupervised method for automatic evaluation of open-domain dialog systems
C Tao, L Mou, D Zhao, R Yan – Thirty-Second AAAI Conference on Artificial …, 2018 – aaai.org
Open-domain human-computer conversation has been attracting increasing attention over the past few years. However, there does not exist a standard automatic evaluation metric for open-domain dialog systems; researchers usually resort to human annotation for model …

Mem2seq: Effectively incorporating knowledge bases into end-to-end task-oriented dialog systems
A Madotto, CS Wu, P Fung – arXiv preprint arXiv:1804.08217, 2018 – arxiv.org
End-to-end task-oriented dialog systems usually suffer from the challenge of incorporating knowledge bases. In this paper, we propose a novel yet simple end-to-end differentiable model called memory-to-sequence (Mem2Seq) to address this issue. Mem2Seq is the first …

Bbq-networks: Efficient exploration in deep reinforcement learning for task-oriented dialogue systems
Z Lipton, X Li, J Gao, L Li, F Ahmed, L Deng – Thirty-Second AAAI …, 2018 – aaai.org
We present a new algorithm that significantly improves the efficiency of exploration for deep Q-learning agents in dialogue systems. Our agents explore via Thompson sampling, drawing Monte Carlo samples from a Bayes-by-Backprop neural network. Our algorithm …

Sequicity: Simplifying task-oriented dialogue systems with single sequence-to-sequence architectures
W Lei, X Jin, MY Kan, Z Ren, X He, D Yin – … of the 56th Annual Meeting of …, 2018 – aclweb.org
Existing solutions to task-oriented dialogue systems follow pipeline designs which introduce architectural complexity and fragility. We propose a novel, holistic, extendable framework based on a single sequence-to-sequence (seq2seq) model which can be optimized with …

Dialogue learning with human teaching and feedback in end-to-end trainable task-oriented dialogue systems
B Liu, G Tur, D Hakkani-Tur, P Shah, L Heck – arXiv preprint arXiv …, 2018 – arxiv.org
In this work, we present a hybrid learning method for training task-oriented dialogue systems through online user interactions. Popular methods for learning task-oriented dialogues include applying reinforcement learning with user feedback on supervised pre-training …

Ethical challenges in data-driven dialogue systems
P Henderson, K Sinha, N Angelard-Gontier… – Proceedings of the …, 2018 – dl.acm.org
The use of dialogue systems as a medium for human-machine interaction is an increasingly prevalent paradigm. A growing number of dialogue systems use conversation strategies that are learned from large datasets. There are well documented instances where interactions …

A survey of available corpora for building data-driven dialogue systems: The journal version
IV Serban, R Lowe, P Henderson… – Dialogue & …, 2018 – dad.uni-bielefeld.de
During the past decade, several areas of speech and language understanding have witnessed substantial breakthroughs from the use of data-driven models. In the area of dialogue systems, the trend is less obvious, and most practical systems are still built through …

Personalizing a dialogue system with transfer reinforcement learning
K Mo, Y Zhang, S Li, J Li, Q Yang – Thirty-Second AAAI Conference on …, 2018 – aaai.org
It is difficult to train a personalized task-oriented dialogue system because the data collected from each individual is often insufficient. Personalized dialogue systems trained on a small dataset is likely to overfit and make it difficult to adapt to different user needs. One way to …

Spoken dialogue system for a human-like conversational robot ERICA
T Kawahara – Proc. IWSDS, keynote speech, 2018 – colips.org
This article gives an overview of our symbiotic human-robot interaction project, which aims at an autonomous android who behaves and interacts just like a human. A conversational android ERICA is designed to conduct several social roles focused on spoken dialogue …

Neural user simulation for corpus-based policy optimisation for spoken dialogue systems
F Kreyssig, I Casanueva, P Budzianowski… – arXiv preprint arXiv …, 2018 – arxiv.org
User Simulators are one of the major tools that enable offline training of task-oriented dialogue systems. For this task the Agenda-Based User Simulator (ABUS) is often used. The ABUS is based on hand-crafted rules and its output is in semantic form. Issues arise from …

An end-to-end goal-oriented dialog system with a generative natural language response generation
S Constantin, J Niehues, A Waibel – arXiv preprint arXiv:1803.02279, 2018 – arxiv.org
Recently advancements in deep learning allowed the development of end-to-end trained goal-oriented dialog systems. Although these systems already achieve good performance, some simplifications limit their usage in real-life scenarios. In this work, we address two of …

Knowledge-aware Multimodal Dialogue Systems
L Liao, Y Ma, X He, R Hong, T Chua – 2018 ACM Multimedia Conference …, 2018 – dl.acm.org
By offering a natural way for information seeking, multimodal dialogue systems are attracting increasing attention in several domains such as retail, travel etc. However, most existing dialogue systems are limited to textual modality, which cannot be easily extended to capture …

Utilizing argument mining techniques for argumentative dialogue systems
N Rach, S Langhammer, W Minker, S Ultes – … Spoken Dialogue Systems  …, 2018 – colips.org
This work presents a pilot study for the application of argument mining techniques in the context of argumentative Dialogue Systems. We extract the argument structure of an online debate and show how it can be utilized to generate artificial persuasive dialogues in an …

Scoutbot: A dialogue system for collaborative navigation
SM Lukin, F Gervits, CJ Hayes, A Leuski… – arXiv preprint arXiv …, 2018 – arxiv.org
ScoutBot is a dialogue interface to physical and simulated robots that supports collaborative exploration of environments. The demonstration will allow users to issue unconstrained spoken language commands to ScoutBot. ScoutBot will prompt for clarification if the user’s …

SlugNERDS: A Named Entity Recognition Tool for Open Domain Dialogue Systems
KK Bowden, J Wu, S Oraby, A Misra… – arXiv preprint arXiv …, 2018 – arxiv.org
In dialogue systems, the tasks of named entity recognition (NER) and named entity linking (NEL) are vital preprocessing steps for understanding user intent, especially in open domain interaction where we cannot rely on domain-specific inference. UCSC’s effort as one of the …

Sample efficient deep reinforcement learning for dialogue systems with large action spaces
G Weisz, P Budzianowski, PH Su, M Gasic – IEEE/ACM Transactions on …, 2018 – dl.acm.org
In spoken dialogue systems, we aim to deploy artificial intelligence to build automated dialogue agents that can converse with humans. A part of this effort is the policy optimization task, which attempts to find a policy describing how to respond to humans, in the form of a …

Task-oriented dialogue system for automatic diagnosis
Z Wei, Q Liu, B Peng, H Tou, T Chen, X Huang… – Proceedings of the 56th …, 2018 – aclweb.org
In this paper, we make a move to build a dialogue system for automatic diagnosis. We first build a dataset collected from an online medical forum by extracting symptoms from both patients’ self-reports and conversational data between patients and doctors. Then we …

Sentiment adaptive end-to-end dialog systems
W Shi, Z Yu – arXiv preprint arXiv:1804.10731, 2018 – arxiv.org
End-to-end learning framework is useful for building dialog systems for its simplicity in training and efficiency in model updating. However, current end-to-end approaches only consider user semantic inputs in learning and under-utilize other user information …

Variational cross-domain natural language generation for spoken dialogue systems
BH Tseng, F Kreyssig, P Budzianowski… – arXiv preprint arXiv …, 2018 – arxiv.org
Cross-domain natural language generation (NLG) is still a difficult task within spoken dialogue modelling. Given a semantic representation provided by the dialogue manager, the language generator should generate sentences that convey desired information. Traditional …

An Empirical Study of Self-Disclosure in Spoken Dialogue Systems
A Ravichander, AW Black – Proceedings of the 19th Annual SIGdial …, 2018 – aclweb.org
Self-disclosure is a key social strategy employed in conversation to build relations and increase conversational depth. It has been heavily studied in psychology and linguistic literature, particularly for its ability to induce self-disclosure from the recipient, a phenomena …

Conversational semantic search: Looking beyond web search, q&a and dialog systems
PA Crook, A Marin, V Agarwal, S Anderson… – Proceedings of the …, 2018 – dl.acm.org
User expectations of web search are changing. They are expecting search engines to answer questions, to be more conversational, and to offer means to complete tasks on their behalf. At the same time, to increase the breadth of tasks that personal digital assistants …

An ontology-based dialogue management system for banking and finance dialogue systems
D Altinok – arXiv preprint arXiv:1804.04838, 2018 – arxiv.org
Keeping the dialogue state in dialogue systems is a notoriously difficult task. We introduce an ontology-based dialogue manage (OntoDM), a dialogue manager that keeps the state of the conversation, provides a basis for anaphora resolution and drives the conversation via …

Speech recognition in a dialog system: from conventional to deep processing
A Becerra, JI de la Rosa, E González – Multimedia Tools and Applications, 2018 – Springer
The aim of this paper is to illustrate an overview of the automatic speech recognition (ASR) module in a spoken dialog system and how it has evolved from the conventional GMM-HMM (Gaussian mixture model-hidden Markov model) architecture toward the recent nonlinear …

A methodology for turn-taking capabilities enhancement in Spoken Dialogue Systems using Reinforcement Learning
H Khouzaimi, R Laroche, F Lefèvre – Computer Speech & Language, 2018 – Elsevier
This article introduces a new methodology to enhance an existing traditional Spoken Dialogue System (SDS) with optimal turn-taking capabilities in order to increase dialogue efficiency. A new approach for transforming the traditional dialogue architecture into an …

Empathetic Dialog Systems
P Fung, D Bertero, P Xu, JH Park, CS Wu… – The International …, 2018 – lrec-conf.org
In this paper, we outline an approach of end-to-end interactive systems with emotional embeddings, which are transfered from a large corpus. We show how to apply emotional embeddings trained from Twitter databases with hashtags and emojis as labels in a …

DeepPavlov: Open-Source Library for Dialogue Systems
M Burtsev, A Seliverstov, R Airapetyan… – Proceedings of ACL …, 2018 – aclweb.org
Adoption of messaging communication and voice assistants has grown rapidly in the last years. This creates a demand for tools that speed up prototyping of featurerich dialogue systems. An open-source library DeepPavlov is tailored for development of conversational …

A debating ontology for argumentative dialogue systems
S Langhammer – 2018 – oparu.uni-ulm.de
This thesis designs and implements an ontology which encodes the argumentative structure of natural language debates. This Debating Ontology will constitute the database for a prospective Argumentative Dialogue System, whose artificial agent conducts spoken …

Spoken dialog system in bodo language for agro services
A Deka, MK Deka – Advances in Electronics, Communication and …, 2018 – Springer
In this work, a cost effective spoken dialog system and a dialog manager is developed for accessing information like price, weather, and fertilizer agricultural commodity in Bodo language. For the development of SR models, we have collected data from different dialect …

Data-Driven Language Understanding for Spoken Dialogue Systems
N Mrkši? – 2018 – repository.cam.ac.uk
Spoken dialogue systems provide a natural conversational interface to computer applications. In recent years, the substantial improvements in the performance of speech recognition engines have helped shift the research focus to the next component of the …

Building Advanced Dialogue Managers for Goal-Oriented Dialogue Systems
V Ilievski – arXiv preprint arXiv:1806.00780, 2018 – arxiv.org
Goal-Oriented (GO) Dialogue Systems, colloquially known as goal oriented chatbots, help users achieve a predefined goal (eg book a movie ticket) within a closed domain. A first step is to understand the user’s goal by using natural language understanding techniques. Once …

Deep Learning in Spoken and Text-Based Dialog Systems
A Celikyilmaz, L Deng, D Hakkani-Tür – Deep Learning in Natural …, 2018 – Springer
Last few decades have witnessed substantial breakthroughs on several areas of speech and language understanding research, specifically for building human to machine conversational dialog systems. Dialog systems, also known as interactive conversational …

Testing Strategies For Bridging Time-To-Content In Spoken Dialogue Systems
MS Lopez Gambino, S Zarrieß… – … Dialogue Systems …, 2018 – pub.uni-bielefeld.de
What should dialogue systems do while looking for information or planning their next utterance? We conducted a study in which participants listened to (constructed) conversations between a user and an information system. In one condition, the system …

Man-machine dialogue system optimization based on cloud computing
M Jin, H Wang, L Song, Y Li, Y Zeng – Personal and Ubiquitous …, 2018 – dl.acm.org
This paper studies the optimization and implementation of human-machine dialog system based on cloud computing technology. Firstly, the coarse-perceived hash generation based on the formant frequency is studied, and the detail-aware hash generation based on the …

Microsoft dialogue challenge: Building end-to-end task-completion dialogue systems
X Li, S Panda, J Liu, J Gao – arXiv preprint arXiv:1807.11125, 2018 – arxiv.org
This proposal introduces a Dialogue Challenge for building end-to-end task-completion dialogue systems, with the goal of encouraging the dialogue research community to collaborate and benchmark on standard datasets and unified experimental environment. In …

Out-of-domain detection method based on sentence distance for dialogue systems
KJ Oh, DK Lee, C Park, YS Jeong… – … Conference on Big …, 2018 – ieeexplore.ieee.org
For dialogue systems, it is critical to detect the out-of-domain (OOD) utterances in a conversation. We detect OOD sentences occurring in a dialogue based on sentence distances. The sentence distances are measured by sentence embedding vectors using …

Integrating laughter into spoken dialogue systems: preliminary analysis and suggested programme
V Maraev, C Mazzocconi, C Howes… – FAIM/ISCA Workshop …, 2018 – christinehowes.com
This paper presents an exploratory scheme, which aims at investigating perceptual features that characterise laughables (the arguments laughter is related to) in dialogue context. We present the results of a preliminary study and sketch an updated questionnaire on …

Improving User Impression in Spoken Dialog System with Gradual Speech Form Control
Y Kageyama, Y Chiba, T Nose, A Ito – … of the 19th Annual SIGdial Meeting …, 2018 – aclweb.org
This paper examines a method to improve the user impression of a spoken dialog system by introducing a mechanism that gradually changes form of utterances every time the user uses the system. In some languages, including Japanese, the form of utterances changes …

Simulation-Based Usability Evaluation of Spoken and Multimodal Dialogue Systems
S Hillmann, S Hillmann, Baumann – 2018 – Springer
Jacob Nielsen has claimed that “The world is full of useless and frustrating software with functionality and user interfaces that could have been improved if their designers had used current usability engineering methods”[157, p. 22]. This was in 1992, and also 24 years later …

A Context-aware Convolutional Natural Language Generation model for Dialogue Systems
S Mangrulkar, S Shrivastava… – Proceedings of the 19th …, 2018 – aclweb.org
Natural language generation (NLG) is an important component in spoken dialog systems (SDSs). A model for NLG involves sequence to sequence learning. State-of-the-art NLG models are built using recurrent neural network (RNN) based sequence to sequence …

Quro: Facilitating User Symptom Check Using a Personalised Chatbot-Oriented Dialogue System.
S Ghosh, S Bhatia, A Bhatia – Studies in health technology and …, 2018 – books.google.com
Automated conversational agents built with medical applications in mind, have the potential to reduce healthcare readmissions and improve accessibility to medical knowledge. In this work, we demonstrate the development and evaluation of an automated chatbot for triage …

Adversarial Domain Adaptation for Variational Neural Language Generation in Dialogue Systems
VK Tran, LM Nguyen – arXiv preprint arXiv:1808.02586, 2018 – arxiv.org
Domain Adaptation arises when we aim at learning from source domain a model that can per-form acceptably well on a different target domain. It is especially crucial for Natural Language Generation (NLG) in Spoken Dialogue Systems when there are sufficient …

A Situated Dialogue System for Learning Structural Concepts in Blocks World
I Perera, J Allen, CM Teng, L Galescu – Proceedings of the 19th Annual …, 2018 – aclweb.org
We present a modular, end-to-end dialogue system for a situated agent to address a multimodal, natural language dialogue task in which the agent learns complex representations of block structure classes through assertions, demonstrations, and …

Cogent: A Generic Dialogue System Shell Based on a Collaborative Problem Solving Model
L Galescu, CM Teng, J Allen, I Perera – Proceedings of the 19th Annual …, 2018 – aclweb.org
The bulk of current research in dialogue systems is focused on fairly simple task models, primarily state-based. Progress on developing dialogue systems for more complex tasks has been limited by the lack generic toolkits to build from. In this paper we report on our …

Eliciting User Food Preferences in terms of Taste and Texture in Spoken Dialogue Systems
J Zeng, YI Nakano, T Morita, I Kobayashi… – Proceedings of the 3rd …, 2018 – dl.acm.org
Food preference varies from person to person and is not easy to verbalize. This study proposes a dialogue system that elicits the user’s food preference through human-robot interaction. First, as the default knowledge of the dialogue system, we determined the …

Student Evaluations of a (Rude) Spoken Dialogue System Insights from an Experimental Study
R Jucks, GA Linnemann… – Advances in Human …, 2018 – hindawi.com
Communicating with spoken dialogue systems (SDS) such as Apple’s Siri® and Google’s Now is becoming more and more common. We report a study that manipulates an SDS’s word use with regard to politeness. In an experiment, 58 young adults evaluated the spoken …

An analysis of the effect of emotional speech synthesis on non-task-oriented dialogue system
Y Chiba, T Nose, T Kase, M Yamanaka… – Proceedings of the 19th …, 2018 – aclweb.org
This paper explores the effect of emotional speech synthesis on a spoken dialogue system when the dialogue is non-task-oriented. Although the use of emotional speech responses has been shown to be effective in a limited domain, eg, scenario-based and counseling …

Dual Latent Variable Model for Low-Resource Natural Language Generation in Dialogue Systems
VK Tran, LM Nguyen – arXiv preprint arXiv:1811.04164, 2018 – arxiv.org
Recent deep learning models have shown improving results to natural language generation (NLG) irrespective of providing sufficient annotated data. However, a modest training data may harm such models performance. Thus, how to build a generator that can utilize as much …

Integration of a Kaldi speech recognizer into a speech dialog system for automotive infotainment applications
T Ranzenberger, C Hacker, F Gallwitz… – … on Electronic Speech …, 2018 – essv2018.de
In this paper we present an evaluation of the Kaldi speech recognizer in an automotive context. We integrate Kaldi into an existing software tool which is used to specify human-machine interfaces including speech dialogs for automotive and non-automotive domains …

… I Trust the Spoken Dialogue System Because It Uses the Same Words as I Do?’—Influence of Lexically Aligned Spoken Dialogue Systems on Trustworthiness and …
GA Linnemann, R Jucks – Interacting with Computers, 2018 – academic.oup.com
One of many ways in which spoken dialogue systems (SDS) are becoming more and more flexible is in their choice of words (eg alignment to the user’s vocabulary). We examined how users perceive such adaptive and non-adaptive SDS regarding trustworthiness and …

Analyses of Example Sentences Collected by Conversation for Example-Based Non-Task-Oriented Dialog System.
Y Kageyama, Y Chiba, T Nose, A Ito – IAENG International Journal of …, 2018 – iaeng.org
Designing an example database is important for handling various users’ utterances in an example-based dialog system, and several approaches to constructing the database have been proposed. This paper focuses on a method for collecting the example sentences …

Enabling Spoken Dialogue Systems for Low-Resourced Languages–End-to-End Dialect Recognition for North Sami
TN Trong, K Jokinen, V Hautamäki – … on Spoken Dialogue Systems …, 2018 – colips.org
In this paper, we tackle the challenge of identifying dialects using deep learning for under-resourced languages. Recent advances in spoken dialogue technology have been strongly influenced by the availability of big corpora, while our goal is to work on the spoken …

Neural Dialogue System with Emotion Embeddings
R Shantala, G Kyselov… – 2018 IEEE First …, 2018 – ieeexplore.ieee.org
Emotional intelligence is a vital human mechanism that allows people to identify and react to different feelings in various environments, especially conversations. That is why it is important to address the emotional aspect of generative dialogue systems. We propose to …

Detecticon: A Prototype Inquiry Dialog System
T Hiraoka, S Motoura, K Sadamasa – colips.org
A prototype inquiry dialog system, dubbed Detecticon, demonstrates its ability to handle inquiry dialogs, including presenting reasonable arguments, tracking user beliefs, and refining its arguments. User interaction is supported by using a natural language interface …

Spoken Dialogue Systems for Medication Management
J Zheng, R Finzel, S Pakhomov, M Gini – www-users.cs.umn.edu
The interest towards spoken dialogue systems has been rapidly growing in the last few years, including in the field of health care. There is a growing need for automated systems that can do more than order airline and movie tickets, find restaurants and hotels, or find …

Handling unknown user arguments in argumentative dialogue systems
N Rach, W Minker, S Ultes – Proceedings of the 32nd International BCS …, 2018 – dl.acm.org
In this work we introduce a scheme to handle unknown user arguments in argumentative Dialogue Systems. We consider systems based on argument games and a graph representation of argument components and discuss how a component that is not present in …

Contextual Topic Modeling For Dialog Systems
C Khatri, R Goel, B Hedayatni, A Metanillou… – arXiv preprint arXiv …, 2018 – arxiv.org
Accurate prediction of conversation topics can be a valuable signal for creating coherent and engaging dialog systems. In this work, we focus on context-aware topic classification methods for identifying topics in free-form human-chatbot dialogs. We extend previous work …

Training Dialogue Systems With Human Advice
M Barlier, R Laroche, O Pietquin – Proceedings of the 17th International …, 2018 – dl.acm.org
One major drawback of Reinforcement Learning (RL) Spoken Dialogue Systems is that they inherit from the general exploration requirements of RL which makes them hard to deploy from an industry perspective. On the other hand, industrial systems rely on human expertise …

Short-Attention Mechanism for Generative Dialogue System
P Si, Y Yang, Y Liu – 2018 IEEE International Conference on …, 2018 – ieeexplore.ieee.org
In recent years, generative dialogue has become the hottest topic in the field of Nature Language Process (NLP). Among the many suggested approaches, the Sequence-tosequence network framework, a variant of traditional Recurrent Neural Network (RNN) …

Task-oriented Dialogue System for Automatic Diagnosis
Q Liu, Z Wei, B Peng, X Dai, H Tou, T Chen, X Huang… – sdspeople.fudan.edu.cn
In this paper, we make a move to build a dialogue system for automatic diagnosis. We first build a dataset collected from an online medical forum by extracting symptoms from both patients’ self-reports and conversational data between patients and doctors. Then we …

Deep reinforcement learning in dialog systems
D Väth – 2018 – elib.uni-stuttgart.de
Die vorliegende Masterarbeit untersucht fortgeschrittene Deep Reinforcement Learning Techniken zum Erlernen von Dialogstrategien. Während viele jüngst veröffentlichte Beiträge im Bereich Reinforcement Learning auf das Erlernen von Atari-Spielen fokussiert sind …

Creating an Emotion Responsive Dialogue System
A Vadehra – 2018 – uwspace.uwaterloo.ca
The popularity of deep neural networks and vast amounts of readily available multi-domain textual data has seen the advent of various domain/task specific and domain agnostic dialogue systems. In our work, we present a general dialogue system that can provide a …

A Bilingual Interactive Human Avatar Dialogue System
DA Ali, M Ahmad, H Al Hassan, P Dozsa, M Hu… – Proceedings of the 19th …, 2018 – aclweb.org
This demonstration paper presents a bilingual (Arabic-English) interactive human avatar dialogue system. The system is named TOIA (time-offset interaction application), as it simulates face-to-face conversations between humans using digital human avatars recorded …

DialCrowd: A toolkit for easy dialog system assessment
K Lee, T Zhao, AW Black, M Eskenazi – Proceedings of the 19th Annual …, 2018 – aclweb.org
When creating a dialog system, developers need to test each version to ensure that it is performing correctly. Recently the trend has been to test on large datasets or to ask many users to try out a system. Crowdsourcing has solved the issue of finding users, but it …

Data-Driven Dialogue Systems: Models, Algorithms, Evaluation, and Ethical Challenges
J Pineau – 2018 – smartech.gatech.edu
The use of dialogue systems as a medium for human-machine interaction is an increasingly prevalent paradigm. A growing number of dialogue systems use conversation strategies that are learned from large datasets. In this talk I will review several recent models and …

Comparison of an End-to-end Trainable Dialogue System with a Modular Statistical Dialogue System
N Braunschweiler, A Papangelis – Proc. Interspeech 2018, 2018 – isca-speech.org
This paper presents a comparison of two dialogue systems: one is end-to-end trainable and the other uses a more traditional, modular architecture. End-to-end trainable dialogue systems recently attracted a lot of attention because they offer several advantages over …

SOGO: A Social Intelligent Negotiation Dialogue System
R Zhao, OJ Romero, A Rudnicky – Proceedings of the 18th International …, 2018 – dl.acm.org
In this paper, we propose a semi-automatic social intelligent negotiation dialogue system that interweaves task utterance with conversational strategies to engage human users in negotiation. Our two-phase system operates sequentially in a reasoning-and-generation …

Creating Large-Scale Argumentation Structures for Dialogue Systems
K Sakai, A Inago, R Higashinaka, Y Yoshikawa… – Proceedings of the …, 2018 – aclweb.org
We are planning to develop argumentative dialogue systems that can discuss various topics with people by using large-scale argumentation structures. In this paper, we describe the creation process of these argumentation structures. We created ten structures each having …

Knowledge Base for a Disaster Management Dialogue System
HY Chan, CH Yang, MH Tsai… – ISARC. Proceedings of …, 2018 – search.proquest.com
This research aims to develop a knowledge base for a disaster management question-answering dialogue system. The rapid growth of the amount of data has led to the variance of data in terms of their formats, sources, and attributes. Hence, the difficulties of decision …

A Multimodal Dialogue System for Conversational Image Editing
TH Lin, T Bui, DS Kim, J Oh – alborz-geramifard.com
In this paper, we present a multimodal dialogue system for Conversational Image Editing. We formulate our multimodal dialogue system as a Partially Observed Markov Decision Process (POMDP) and trained it with Deep Q-Network (DQN) and a user simulator. Our …

Towards Building a Domain Independent Dialog System
P Jwalapuram – 2018 – web2py.iiit.ac.in
This thesis discusses a mixed-initiative, domain independent dialog system based on a hierarchically structured knowledge base. The system is rule-based and uses dependency relations and part-of-speech tags obtained from the Stanford Parser coupled with the …

Improving Dialog Systems Using Knowledge Graph Embeddings
B Carignan – 2018 – curve.carleton.ca
Dialog systems are systems or applications intended to converse with a human user. Recent dialog systems have employed the sequence-to-sequence framework to treat conversation as a translation problem, translating from question to answer in an open-domain …

Data Collection for Dialogue System: A Startup Perspective
Y Kang, Y Zhang, JK Kummerfeld, L Tang… – Proceedings of the 2018 …, 2018 – aclweb.org
Industrial dialogue systems such as Apple Siri and Google Assistant require large scale diverse training data to enable their sophisticated conversation capabilities. Crowdsourcing is a scalable and inexpensive data collection method, but collecting high quality data …

Improving Response Selection in Multi-turn Dialogue Systems
D Chaudhuri, A Kristiadi, J Lehmann… – arXiv preprint arXiv …, 2018 – arxiv.org
Building systems that can communicate with humans is a core problem in Artificial Intelligence. This work proposes a novel neural network architecture for response selection in an end-to-end multi-turn conversational dialogue setting. The architecture applies context …

Improving Taxonomy of Errors in Chat-oriented Dialogue Systems
R Higashinaka, M Araki, H Tsukahara, M Mizukami – colips.org
In previous studies, top-down and bottom-up approaches have been proposed for creating taxonomies of errors in chat-oriented dialogue systems. However, the reported K (kappa) value for the taxonomy based on the top-down approach is low at 0.239, and no evaluation …

Scalable language model adaptation for spoken dialogue systems
A Gandhe, A Rastrow, B Hoffmeister – arXiv preprint arXiv:1812.04647, 2018 – arxiv.org
Language models (LM) for interactive speech recognition systems are trained on large amounts of data and the model parameters are optimized on past user data. New application intents and interaction types are released for these systems over time, imposing …

Enabling Spoken Dialogue Systems for Low-resourced Languages
TN Trong, PK Jokinen, V Hautamäki – … on Spoken Dialog System …, 2018 – helda.helsinki.fi
In this paper, we tackle the challenge of identifying dialects using deep learning for under-resourced languages. Recent advances in spoken dialogue technology have been strongly influenced by the availability of big corpora, while our goal is to work on the spoken …

Topic Aware Open-Domain Dialogue Systems & Evaluations
Y Chen, A Cai – randomized.me
In open-domain dialogue systems, meaningful and coherent dialogue response generation is one of the major problems that requires comprehensive understandings of dialogue histories (Li et al., 2016, 2017), topic selections and other potential factors that can explicitly …

A Dialogue System Recommending Query Sentences in Consideration of User Interest
Y Seki, Y Ueno – 2018 IEEE 7th Global Conference on …, 2018 – ieeexplore.ieee.org
We design and develop a dialogue system with collaborative filtering (CF), analyzing user histories to users and weighted information. For users who do not know what to ask, the system recommends query sentences that users should ask, considering user interest. We …

On Evaluating and Comparing Open Domain Dialog Systems
A Venkatesh, C Khatri, A Ram, F Guo, R Gabriel… – arXiv preprint arXiv …, 2018 – arxiv.org
Conversational agents are exploding in popularity. However, much work remains in the area of non goal-oriented conversations, despite significant growth in research interest over recent years. To advance the state of the art in conversational AI, Amazon launched the …

Recurrent neural network language generation for dialogue systems
TH Wen – 2018 – ethos.bl.uk
Language is the principal medium for ideas, while dialogue is the most natural and effective way for humans to interact with and access information from machines. Natural language generation (NLG) is a critical component of spoken dialogue and it has a significant impact …

Applying Coreference Resolution for Usage in Dialog Systems
G Rolih – 2018 – diva-portal.org
Using references in language is a major part of communication, and understanding them is not a challenge for humans. Recent years have seen increased usage of dialog systems that interact with humans in natural language to assist them in various tasks, but even the most …

External Memory Enhanced Sequence-to-Sequence Dialogue Systems
J Verdegaal – 2018 – pdfs.semanticscholar.org
One of the unique human traits is the ability to converse with each other, which is an artifact of our intelligence. In the field of Artificial Intelligence (AI) much research has been done to model this unique behavior. A natural conversing digital system has long been the holy grail …

End-to-End Dialog systems for Ubuntu dialog corpus
LC Polymenakos, S Singh – workshop.colips.org
Most of the past DSTC tasks involve synthetic dialog datasets or real dialog interaction datasets with highly constrained domains. With this challenge, we propose a more challenging dialog task on the Ubuntu dialog corpus. The Ubuntu Chat Logs refer to a …

Pre-Consulting Dialogue Systems for Telemedicine: Yes/No Intent Classification
T Mairittha, T Okita, S Inoue – Proceedings of the 2018 ACM International …, 2018 – dl.acm.org
Telemedicine is an emerging challenge for the shortage of qualified professionals, particularly in under-resourced regions. Physical assessment by a non-medical doctor is a practice in telemedicine which discovers essential symptom of a patient who needs to …

Erratum to: Simulation-Based Usability Evaluation of Spoken and Multimodal Dialogue Systems
S Hillmann – … of Spoken and Multimodal Dialogue Systems, 2018 – Springer
The original version of the book was inadvertently published with several typesetting errors in backmatter references, which have been now corrected … The updated online version of the book can be found at https://doi.org/10.1007/978-3-319-62518-8 … © Springer International …

Play Duration based User-Entity Affinity Modeling in Spoken Dialog System
B Xiao, N Monath, S Ananthakrishnan… – arXiv preprint arXiv …, 2018 – arxiv.org
Multimedia streaming services over spoken dialog systems have become ubiquitous. User-entity affinity modeling is critical for the system to understand and disambiguate user intents and personalize user experiences. However, fully voice-based interaction demands …

Cross-Lingual Approaches to Reference Resolution in Dialogue Systems
A Sharaf, A Gupta, H Ge, C Naik, L Mathias – arXiv preprint arXiv …, 2018 – arxiv.org
In the slot-filling paradigm, where a user can refer back to slots in the context during the conversation, the goal of the contextual understanding system is to resolve the referring expressions to the appropriate slots in the context. In this paper, we build on the context …

Memory-augmented Dialogue Management for Task-oriented Dialogue Systems
Z Zhang, M Huang, Z Zhao, F Ji, H Chen… – arXiv preprint arXiv …, 2018 – arxiv.org
Dialogue management (DM) decides the next action of a dialogue system according to the current dialogue state, and thus plays a central role in task-oriented dialogue systems. Since dialogue management requires to have access to not only local utterances, but also the …

Symptoms of cognitive load in interactions with a dialogue system
J Lopes, K Lohan, H Hastie – Proceedings of the Workshop on Modeling …, 2018 – dl.acm.org
Humans adapt their behaviour to the perceived cognitive load of their dialogue partner, for example, delaying non-essential information. We propose that spoken dialogue systems should do the same, particularly in high-stakes scenarios, such as emergency response. In …

A View of the State of the Art of Dialogue Systems
L Ozaeta, M Graña – … Conference on Hybrid Artificial Intelligence Systems, 2018 – Springer
Dialogue systems are becoming central tools in human computer interface systems. New interaction systems, eg Siri, Echo and others, are proposed by the day, and new features are added to these systems at breathtaking pace. The conventional approaches based on …

Multimodal dialogue system evaluation: a case study applying usability standards
A Malchanau, V Petukhova, H Bunt – colips.org
This paper presents an approach to the evaluation of multimodal dialogue systems, applying usability metrics defined in ISO standards. Users’ perceptions of effectiveness, efficiency and satisfaction were correlated with various performance metrics and with interaction …

Context-Aware Dialog Re-Ranking for Task-Oriented Dialog Systems
J Ohmura, M Eskenazi – arXiv preprint arXiv:1811.11430, 2018 – arxiv.org
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 on task-oriented dialogs. Furthermore, no previous …

Deep Learning for User Simulation in a Dialogue System
FL Kreyssig – mi.eng.cam.ac.uk
Spoken Dialogue Systems (SDS) allow human-computer interaction using natural speech. The use of Spoken Dialogue Systems in commercial applications has become common with products such as Amazon’s Echo, Google’s Home, and Apple’s Siri and HomePod. Whilst …

Strategy of the Negative Sampling for Training Retrieval-Based Dialogue Systems
A Nugmanova, A Smirnov, G Lavrentyeva… – arXiv preprint arXiv …, 2018 – arxiv.org
The article describes the new approach for quality improvement of automated dialogue systems for customer support service. Analysis produced in the paper demonstrates the dependency of the quality of the retrieval-based dialogue system quality on the choice of …

KNADIA: Enterprise KNowledge Assisted DIAlogue Systems Using Deep Learning
M Singh, P Agarwal, A Chaudhary… – 2018 IEEE 34th …, 2018 – ieeexplore.ieee.org
In this paper we present the design, architecture and implementation of KNADIA, a conversational dialogue system for intra-enterprise use, providing knowledge-assisted question answering and transactional assistance to employees of a large organization …

Generating Responses Expressing Emotion in an Open-domain Dialogue System
C Huang, OR Zaïane – arXiv preprint arXiv:1811.10990, 2018 – arxiv.org
Neural network-based Open-ended conversational agents automatically generate responses based on predictive models learned from a large number of pairs of utterances. The generated responses are typically acceptable as a sentence but are often dull, generic …

MOOC Guider: An End-to-End Dialogue System for MOOC Users
Y Li, Y Zhang – Asia-Pacific Web (APWeb) and Web-Age Information …, 2018 – Springer
With the growth of the amount of MOOC users and course diversity, it becomes a hard work for a new MOOC user to find a suitable course and gather other information. In this paper, we propose a natural language dialogue based MOOC guider, which helps users to find a …

Adaptive Dialogue System for Disabled Learners: Towards a Learning Disabilities Model
M Taouil, A Begdouri, A Majda – 2018 IEEE 5th International …, 2018 – ieeexplore.ieee.org
In the last decade, a large rise in the number of learners with learning difficulties has been observed. This problem is serious since it has a direct impact on the education of young children and their integration into society in the future. The adoption of tools supported by …

A Manually Annotated Chinese Corpus for Non-task-oriented Dialogue Systems
J Li, Y Song, H Zhang, S Shi – arXiv preprint arXiv:1805.05542, 2018 – arxiv.org
This paper presents a large-scale corpus for non-task-oriented dialogue response selection, which contains over 27K distinct prompts more than 82K responses collected from social media. To annotate this corpus, we define a 5-grade rating scheme: bad, mediocre …

A Clustering Based Adaptive Sequence-to-Sequence Model for Dialogue Systems
D Ren, Y Cai, WH Chan, Z Li – 2018 IEEE International …, 2018 – ieeexplore.ieee.org
Dialogue systems which can communicate with people in natural language is popularly used in entertainments and language learning tools. As the development of deep neural networks, Sequence-to-Sequence models become the main stream models of conversation …

Flexible and Scalable State Tracking Framework for Goal-Oriented Dialogue Systems
R Goel, S Paul, T Chung, J Lecomte, A Mandal… – arXiv preprint arXiv …, 2018 – arxiv.org
Goal-oriented dialogue systems typically rely on components specifically developed for a single task or domain. This limits such systems in two different ways: If there is an update in the task domain, the dialogue system usually needs to be updated or completely re-trained …

Intent Detection for code-mix utterances in task oriented dialogue systems
P Jayarao, A Srivastava – arXiv preprint arXiv:1812.02914, 2018 – arxiv.org
Intent detection is an essential component of task oriented dialogue systems. Over the years, extensive research has been conducted resulting in many state of the art models directed towards resolving user’s intents in dialogue. A variety of vector representations foruser …

Supervised Clustering of Questions into Intents for Dialog System Applications
I Haponchyk, A Uva, S Yu, O Uryupina… – Proceedings of the 2018 …, 2018 – aclweb.org
Modern automated dialog systems require complex dialog managers able to deal with user intent triggered by high-level semantic questions. In this paper, we propose a model for automatically clustering questions into user intents to help the design tasks. Since questions …

MDKB-Bot: A Practical Framework for Multi-Domain Task-Oriented Dialogue System
Y Lao, W Liu, S Gao, S Li – data-intelligence-journal.org
One of the major challenges to build a task-oriented dialogue system is that dialogue state transition frequently happens between multiple domains such as booking hotels or restaurants. Recently, the encoderdecoder model based on the end-to-end neural network …

Studying Mutual Phonetic Influence with a Web-Based Spoken Dialogue System
E Raveh, I Steiner, I Gessinger, B Möbius – International Conference on …, 2018 – Springer
This paper presents a study on mutual speech variation influences in a human-computer setting. The study highlights behavioral patterns in data collected as part of a shadowing experiment, and is performed using a novel end-to-end platform for studying phonetic …

Finding Mnemo: Hybrid Intelligence Memory in a Crowd-Powered Dialog System
S GOURAVAJHALA, Y JIANG, P KAUR, J CHAAR… – croma.eecs.umich.edu
4. RESULTS Workers generated a total of 500 notes over ten dialogs (average of five notes per worker, ?= 2.87). W e manually annotated each worker note as either being a true positive (matches a ground truth fact) or a false positive (does not match any ground truth …

The Effect of Data Quantity on Dialog System Input Classification Models
J Lipecki, V Lundén – 2018 – diva-portal.org
Detta arbete undersöker hur olika datamängder påverkar olika slags ordvektormodeller för klassificering av indata till dialogsystem. Hypotesen att det finns ett tröskelvärde för träningsdatamängen där täta ordvektormodeller når den högsta moderna utvecklingsnivån …

Improving the Performance of Chat-oriented Dialogue Systems via Dialogue Breakdown Detection
M Inaba, K Takahashi – colips.org
Dialogue breakdown detection is a technique used for identifying inappropriate utterances in dialogue systems that has attracted increased attention, especially in chat-oriented dialogue systems. Although it is generally assumed that dialogue breakdown detection …

Simplified Hierarchical Recurrent Encoder-Decoder for Building End-To-End Dialogue Systems
C Wang, H Jiang – arXiv preprint arXiv:1809.02790, 2018 – arxiv.org
As a generative model for building end-to-end dialogue systems, Hierarchical Recurrent Encoder-Decoder (HRED) consists of three layers of Gated Recurrent Unit (GRU), which from bottom to top are separately used as the word-level encoder, the sentence-level …

Implementation of A Neural Natural Language Understanding Component for Arabic Dialogue Systems
AM Bashir, A Hassan, B Rosman, D Duma… – Procedia computer …, 2018 – Elsevier
Abstract Natural Language Understanding (NLU) is considered a core component in implementing dialogue systems. NLU has been greatly enhanced by deep learning techniques such as word embeddings and deep neural network architectures, but current …

Task graph based task-oriented dialogue system using dialogue map for second language learning
OW Kwon, YK Kim, Y Lee – Future-proof CALL: language …, 2018 – books.google.com
This paper presents a rule-based task-oriented dialogue system for second language learning and a knowledge extraction method which automatically extracts the training data for Natural Language Understanding (NLU) and dialogue rules for dialogue management …

Effect of Mutual Self-Disclosure in Spoken Dialog System on User Impression
S Tada, Y Chiba, T Nose, A Ito – Proceedings, APSIPA Annual Summit …, 2018 – apsipa.org
Many of current spoken dialog systems can conduct non-task-oriented dialog. The systems that can improve user impression are required for users to keep using them. This paper focuses on self-disclosure, that is a process that a person reveals information about …

Automation and Optimisation of Humor Trait Generation in a Vocal Dialogue System
M Riou, S Huet, B Jabaian, F Lefèvre – Proceedings of the Workshop on …, 2018 – aclweb.org
This study pertains to our ongoing work about social artificial vocal interactive agents and their adaptation to users. In this regard, several possibilities to introduce humorous productions in a spoken dialogue system are investigated in order to enhance naturalness …

Nearly Zero-Shot Learning for Semantic Decoding in Spoken Dialogue Systems
LM Rojas-Barahona, I Casanueva… – arXiv preprint arXiv …, 2018 – arxiv.org
This paper presents two ways of dealing with scarce data in semantic decoding using N-Best speech recognition hypotheses. First, we learn features by using a deep learning architecture in which the weights for the unknown and known categories are jointly …

Graph Convolutional Network with Sequential Attention For Goal-Oriented Dialogue Systems
S Banerjee, MM Khapra – 2018 – openreview.net
Domain specific goal-oriented dialogue systems typically require modeling three types of inputs, viz.,(i) the knowledge-base associated with the domain,(ii) the history of the conversation, which is a sequence of utterances and (iii) the current utterance for which the …

Intent Generation for Goal-Oriented Dialogue Systems based on Schema. org Annotations
U ?im?ek, D Fensel – arXiv preprint arXiv:1807.01292, 2018 – arxiv.org
Goal-oriented dialogue systems typically communicate with a backend (eg database, Web API) to complete certain tasks to reach a goal. The intents that a dialogue system can recognize are mostly included to the system by the developer statically. For an open …

Optimization of Information-Seeking Dialogue Strategy for Argumentation-Based Dialogue System
H Katsumi, T Hiraoka, K Yoshino, K Yamamoto… – arXiv preprint arXiv …, 2018 – arxiv.org
Argumentation-based dialogue systems, which can handle and exchange arguments through dialogue, have been widely researched. It is required that these systems have sufficient supporting information to argue their claims rationally; however, the systems often …

Detecting Location-Indicating Phrases in User Utterances for Chat-Oriented Dialogue Systems
H Narimatsu, H Sugiyama, M Mizukami – ceur-ws.org
This paper establishes a method that detects words or phrases that indicate location in Japanese spoken language for a chat-oriented dialogue system. Although conventional methods for detecting words or phrases focus on named entities (NE) s, humans frequently …

Multi-Task Learning for Domain-General Spoken Disfluency Detection in Dialogue Systems
I Shalyminov, A Eshghi, O Lemon – arXiv preprint arXiv:1810.03352, 2018 – arxiv.org
Spontaneous spoken dialogue is often disfluent, containing pauses, hesitations, self-corrections and false starts. Processing such phenomena is essential in understanding a speaker’s intended meaning and controlling the flow of the conversation. Furthermore, this …

Learning Dialogue Strategies for Interview Dialogue Systems That Can Engage in Small Talk
T Nakamura, T Kobori, M Nakano – colips.org
This paper proposes a method with which an interview dialogue system can learn user-friendly dialogue strategies. Conventional interview dialogue systems mainly focus on collecting the user’s information and simply repeat questions. We have previously proposed …

Policy learning for task-oriented dialogue systems via reinforcement learning techniques
C Yin – 2018 – minerva-access.unimelb.edu.au
Task-oriented dialogue systems such as Apple Siri and Microsoft Cortana are becoming increasingly popular and are attracting much attention. Task-oriented dialogue systems aim to serve people as virtual personal assistants. For example, they can help users create …

Unsupervised Counselor Dialogue Clustering for Positive Emotion Elicitation in Neural Dialogue System
N Lubis, S Sakti, K Yoshino, S Nakamura – Proceedings of the 19th …, 2018 – aclweb.org
Positive emotion elicitation seeks to improve user’s emotional state through dialogue system interaction, where a chatbased scenario is layered with an implicit goal to address user’s emotional needs. Standard neural dialogue system approaches still fall short in this situation …

Automatic template feature extraction and the application to utterance in a dialogue system
Y Mikami, M Hagiwara – … of the 2nd International Conference on …, 2018 – dl.acm.org
In this paper, we propose an automatic template features extraction method and apply it to utterance generation in a dialogue system. Template-based utterance generation has been widely used in many dialogue systems because of its robustness. Although variety of …

What Information Should a Dialogue System Understand?: Collection and Analysis of Perceived Information
K Mitsuda, R Higashinaka… – … on Spoken Dialog Systems, 2018 – books.google.com
It is important for chat-oriented dialogue systems to be able to understand the various information from user utterances. However, no study has yet clarified the types of information that should be understood by such systems. With this purpose in mind, we collected and …

Generating Personalized Virtual Agent in Speech Dialogue System for People with Dementia
S Nakatani, S Saiki, M Nakamura, K Yasuda – International Conference on …, 2018 – Springer
Our research group has been studying a speech communication system with a virtual agent (VA), to support person-centered care (PCC) of people with dementia (PWD). The current system uses the 3D model based on an unreal character for the VA. Because the unfamiliar …

Now We Are Talking! Flexible and Open Goal-Oriented Dialogue Systems for Accessing Touristic Services
U ?im?ek, D Fensel – e-Review of Tourism Research – journals.tdl.org
Goal-oriented dialogue systems have drawn interest from the academia and industry since the 1950s. The application areas vary between the likes of well-defined customer service processes and complex planning tasks. The practical applications are mostly developed …

Learning to Interrupt the User at the Right Time in Incremental Dialogue Systems
A Chýlek, J Švec, L Šmídl – … Workshop on Temporal, Spatial, and Spatio …, 2018 – Springer
Continuous processing of input in incremental dialogue systems might result in the need of interrupting a user’s utterance when clarification or rapport is needed. Being able to predict the right time when to interrupt the utterance can be another step to a more human-like …

The use of associative semantic preprocessor in the interactive dialogue systems in natural language
VE Sachkov – Proceedings of the Institute for System Programming of …, 2018 – mathnet.ru
The article explores the possibility of using an associative-semantic preprocessor for special text processing in natural language. The use of associations allow to abstract from the direct meaning of a word and to replace it with a set of other words. This has also the opposite …

End-to-End Task-Oriented Dialogue System with Distantly Supervised Knowledge Base Retriever
L Qin, Y Liu, W Che, H Wen, T Liu – Chinese Computational Linguistics …, 2018 – Springer
Task-oriented dialog systems usually face the challenge of querying knowledge base. However, it usually cannot be explicitly modeled due to the lack of annotation. In this paper, we introduce an explicit KB retrieval component (KB retriever) into the seq2seq dialogue  …

Advanced Social Interaction with Agents: 8th International Workshop on Spoken Dialog Systems
M Eskenazi, L Devillers, J Mariani – 2018 – Springer
The International Workshop on Spoken Dialogue Systems (IWSDS) series provides an international forum for the presentation of research and applications as well as a place where lively discussions can take place between academic and industrial researchers …

Expert Evaluation of a Spoken Dialogue System in a Clinical Operating Room
J Miehle, N Gerstenlauer, D Ostler, H Feußner… – Proceedings of the …, 2018 – aclweb.org
With the emergence of new technologies, the surgical working environment becomes increasingly complex and comprises many medical devices which have to be monitored and controlled. With the aim of improving productivity and reducing the workload for the …

Smart Entertainment-A Critiquing Based Dialog System for Eliciting User Preferences and Making Recommendations
SG Patil – Natural Language Processing and Information Systems …, 2018 – books.google.com
We present a Critiquing based dialog system that can make media content recommendations to users by eliciting information through active exploration of user preferences for item attributes. The system and user communicate through a natural …

Augmenting Natural Language Generation with external memory modules in Spoken Dialogue Systems
M Sun – mlsalt.eng.cam.ac.uk
Abstract Semantically Conditioned LSTM (SC-LSTM) is one of the state-of-the-art models in the Natural Language Generation of the Spoken Dialogue Systems. Though it has a Dialogue Act (DA) cell which enables the generations to condition on DA information …

Analyzing Motivating Texts for Modelling Human-Like Motivation Techniques in Emotionally Intelligent Dialogue Systems
P Swieczkowska, R Rzepka, K Araki – Biologically Inspired Cognitive …, 2018 – Springer
In this paper, we present studies on human-like motivational strategies which eventually will allow us to implement motivational support in our general dialogue system. We conducted a study on user comments from a discussion platform Reddit and identified text features that …

Estimating User Satisfaction Impact in Cities using Physical Reaction Sensing and Multimodal Dialogue System
Y Matsuda, D Fedotov, Y Takahashi, Y Arakawa… – 2018 – colips.org
Following the increase in use of smart devices, various real-time environmental information becomes available everywhere. To provide more context-aware information, we also need to know emotion and a satisfaction level in a viewpoint of users. In this paper, we define it as …

Out-of-Domain Slot Value Detection for Spoken Dialogue Systems with Context Information
Y Kobayashi, T Yoshida, K Iwata… – 2018 IEEE Spoken …, 2018 – ieeexplore.ieee.org
This paper proposes an approach to detecting-of-domain slot values from user utterances in spoken dialogue systems based on contexts. The approach detects keywords of slot values from utterances and consults domain knowledge (ie, an ontology) to check whether the …

Customization of an example-based dialog system with user data and distributed word representations
E Seto, R Nishimura, N Kitaoka – 2018 Asia-Pacific Signal and …, 2018 – ieeexplore.ieee.org
There is a need to develop spoken dialog systems which are capable of engaging in natural conversations with people, for example, the socially-isolated elderly. We propose an example-based dialog system featuring an adaptation method which customizes the dialog …

Smart Entertainment-A Critiquing Based Dialog System for Eliciting User Preferences and Making Recommendations
RR Ramnani, S Sengupta, TR Ravilla… – … on Applications of Natural …, 2018 – Springer
We present a Critiquing based dialog system that can make media content recommendations to users by eliciting information through active exploration of user preferences for item attributes. The system and user communicate through a natural …

Improving Robustness of Neural Dialog Systems in a Data-Efficient Way with Turn Dropout
I Shalyminov, S Lee – arXiv preprint arXiv:1811.12148, 2018 – arxiv.org
Neural network-based dialog models often lack robustness to anomalous, out-of-domain (OOD) user input which leads to unexpected dialog behavior and thus considerably limits such models’ usage in mission-critical production environments. The problem is especially …

Dialogue Systems and Conversational Agents for Patients with Dementia: The Human–Robot Interaction
A Russo, G D’Onofrio, A Gangemi, F Giuliani… – Rejuvenation …, 2018 – liebertpub.com
This study aimed to identify and describe the fundamental characteristics of spoken dialogue systems, and their role in supporting human–robot interaction and enabling the communication between socially assistive robots and patients with dementia. First, this work …

A Neural Method for Goal-Oriented Dialog Systems to interact with Named Entities
J Rajendran, J Ganhotra, X Guo, M Yu, S Singh – 2018 – openreview.net
Many goal-oriented dialog tasks, especially ones in which the dialog system has to interact with external knowledge sources such as databases, have to handle a large number of Named Entities (NEs). There are at least two challenges in handling NEs using neural …

How People Negotiate? From the Analysis of a Dialogue Corpus to a Dialogue System
M Koit – 2018 Innovations in Intelligent Systems and …, 2018 – ieeexplore.ieee.org
We study human-human negotiations in a dialogue corpus with the aim to develop a dialogue system. The empirical material is formed by telemarketing calls where sales clerks of an educational company are offering the training courses of the company to prospective …

Speech understanding for spoken dialogue systems: From corpus harvesting to grammar rule induction
E Iosif, I Klasinas, G Athanasopoulou… – Computer Speech & …, 2018 – Elsevier
We investigate algorithms and tools for the semi-automatic authoring of grammars for spoken dialogue systems (SDS) proposing a framework that spans from corpora creation to grammar induction algorithms. A realistic human-in-the-loop approach is followed balancing …

Agricultural Human-Machine Dialogue System Development Based on Semantic and Location Similarity of Short Text Model
Q Wei, C Zhong, J Yu, C Luo… – 2018 2nd IEEE Advanced …, 2018 – ieeexplore.ieee.org
To the problem that the reply accuracy is low and its can’t answer common chat topics at the same time in agricultural man-machine dialogue, a similarity model is proposed by a comprehensive consideration of semantic words and position words, a system development …

Overview of the NLPCC 2018 Shared Task: Spoken Language Understanding in Task-Oriented Dialog Systems
X Zhao, Y Cao – CCF International Conference on Natural Language …, 2018 – Springer
This paper presents the overview for the shared task at the 7 th CCF Conference on Natural Language Processing & Chinese Computing (NLPCC 2018): Spoken Language Understanding (SLU) in Task-oriented Dialog Systems. SLU usually consists of two parts …

A Unified Neural Architecture for Joint Dialog Act Segmentation and Recognition in Spoken Dialog System
T Zhao, T Kawahara – Proceedings of the 19th Annual SIGdial Meeting …, 2018 – aclweb.org
In spoken dialog systems (SDSs), dialog act (DA) segmentation and recognition provide essential information for response generation. A majority of previous works assumed ground-truth segmentation of DA units, which is not available from automatic speech recognition …

Exploring the Impact of Elaborateness and Indirectness on User Satisfaction in a Spoken Dialogue System
J Miehle, W Minker, S Ultes – Adjunct Publication of the 26th Conference …, 2018 – dl.acm.org
We present a study addressing the questions of how varying communication styles of a spoken user interface are perceived by users and whether there exist global preferences in the communication styles elaborateness and indirectness. A total of 60 participants had two …

Exploring the importance of context and embeddings in neural NER models for task-oriented dialogue systems
P Jayarao, C Jain, A Srivastava – arXiv preprint arXiv:1812.02370, 2018 – arxiv.org
Named Entity Recognition (NER), a classic sequence labelling task, is an essential component of natural language understanding (NLU) systems in task-oriented dialog systems for slot filling. For well over a decade, different methods from lookup using …

Incorporating the Structure of the Belief State in End-to-End Task-Oriented Dialogue Systems
L Shu, P Molino, M Namazifar, B Liu, H Xu, H Zheng… – alborz-geramifard.com
End-to-end trainable networks try to overcome error propagation, lack of generalization and overall brittleness of traditional modularized task-oriented dialoguesystem architectures. Most proposed models expand on the sequence-to-sequence architecture. Some of them …

A Study on a Spoken Dialogue System with Cooperative Emotional Speech Synthesis Using Acoustic and Linguistic Information
M Yamanaka, Y Chiba, T Nose, A Ito – International Conference on …, 2018 – Springer
This study examines an emotion labeling method for a system utterance of a non-task-oriented spoken dialogue system. The conventional study proposed the cooperative emotion labeling, which generates an emotional speech with an emotion label estimated …

An Efficient Framework for Development of Task-Oriented Dialog Systems in a Smart Home Environment
Y Park, S Kang, J Seo – Sensors, 2018 – mdpi.com
In recent times, with the increasing interest in conversational agents for smart homes, task-oriented dialog systems are being actively researched. However, most of these studies are focused on the individual modules of such a system, and there is an evident lack of research …

Towards a structured evaluation of improv-bots: Improvisational theatre as a non-goal-driven dialogue system
M Skeppstedt, M Ahltorp – ceur-ws.org
We have here suggested a structured procedure for evaluating artificially produced improvisational theatre dialogue. We have, in addition, provided some examples of dialogues generated within the evaluation framework suggested. Although the end goal of a …

Multi-Modal Robot Apprenticeship: Imitation Learning Using Linearly Decayed DMP+ in a Human-Robot Dialogue System
Y Wu, R Wang, LF D’Haro, RE Banchs… – 2018 IEEE/RSJ …, 2018 – ieeexplore.ieee.org
Robot learning by demonstration gives robots the ability to learn tasks which they have not been programmed to do before. The paradigm allows robots to work in a greater range of real-world applications in our daily life. However, this paradigm has traditionally been …

Advancing the State of the Art in Open Domain Dialog Systems through the Alexa Prize
C Khatri, B Hedayatnia, A Venkatesh, J Nunn… – arXiv preprint arXiv …, 2018 – arxiv.org
Building open domain conversational systems that allow users to have engaging conversations on topics of their choice is a challenging task. Alexa Prize was launched in 2016 to tackle the problem of achieving natural, sustained, coherent and engaging open …

Virtual Doctor: An Intelligent Human-Computer Dialogue System for Quick Response to People in Need
S Mallios – 2018 – corescholar.libraries.wright.edu
One of the challenges of our society is the existence of chronic-related conditions and diseases among the elderly and people at risk. Apart from the welfare of people, a significant impact of this phenomenon is the accumulation of high financial costs for both individuals …

Auto-Dialog Systems: Implementing Automatic Conversational Man-Machine Agents by Using Artificial Intelligence & Neural Networks
A Bala, T Padmaja, GKD Gopisettry – chsd-theresacollege.net
Many companies are hoping to develop bots to have natural conversations indistinguishable from human ones, and many are claiming to be using Neuro-Linguistic Programming and Deep Learning techniques to make this possible. Microsoft is making big bets on chat bots …

Situated reference resolution using visual saliency and crowdsourcing-based priors for a spoken dialog system within vehicles
T Misu – Computer Speech & Language, 2018 – Elsevier
In this paper, we address issues in situated language understanding in a moving car. More specifically, we propose a reference resolution method to identify user queries about specific target objects in their surroundings. We investigate methods of predicting which target object …

Using Paraphrasing and Memory-Augmented Models to Combat Data Sparsity in Question Interpretation with a Virtual Patient Dialogue System
L Jin, D King, A Hussein, M White… – Proceedings of the …, 2018 – aclweb.org
When interpreting questions in a virtual patient dialogue system, one must inevitably tackle the challenge of a long tail of relatively infrequently asked questions. To make progress on this challenge, we investigate the use of paraphrasing for data augmentation and neural …

Using Artificial Intelligence-Based Argument Theory To Generate Automated Patient Education Dialogues: An Interactive Educational Dialogue System For Families Of …
B Rose-Davis – 2018 – dalspace.library.dal.ca
Juvenile Idiopathic Arthritis (JIA) is a chronic rheumatic disease affecting between 1 and 4 out of 1000 children in Canada, with outcomes including pain, prolonged dependence on medications, and disability. To allow families to effectively self-manage chronic conditions …

Using Reinforcement Learning for Dialogue Act Classification in Task-oriented Conversation Systems
Q Xia – DEStech Transactions on Computer Science and …, 2018 – dpi-proceedings.com
… Besides these famous applications, enterprises still want to make specific-domain dialog systems which not only … TABLE I. EXAMPLE CONVERSATION OF DIALOG SYSTEM … results in DA classification task, but also improves the overall performance of the dialogue system …

Dialogue Models for Bilingual Human-Computer Interaction in a City Information System
J Schwarz, V Matoušek – fi.muni.cz
… Abstract. In this paper we report on some special problems arising during the building of a bilingual dialogue system, concerning especially parsing and dia- logue modeling … They meet the needs of more complex tasks that have to be handled by the dialogue system …

A multimodal dialogue framework for cloud-based companion systems
M Kraus, G Behnke, P Bercher, M Schiller… – … Spoken Dialog Systems …, 2018 – uni-ulm.de
Companion systems are cooperative, cognitive systems aiming at assisting a user in everyday situations. Therefore, these systems require a high level of availability. One option to meet this requirement is to use a web-deployable architecture. In this demo paper, we …

Adaptive Visual Dialog for Intelligent Tutoring Systems
J Ahn, M Chang, P Watson, R Tejwani… – … Conference on Artificial …, 2018 – Springer
… 1 Introduction. Conversational dialog systems allow people to communicate with intelligent software in a natural way. Natural … state. 2 Adaptive Visual Dialog System. Figure 1 shows a prototype implementation of Adaptive Visual Dialog …

A Method for Dataset Creation for Dialogue State Classification in Voice Control Systems for the Internet of Things
I Shilin, L Kovriguina, D Mouromtsev… – … Readings in Language …, 2018 – ceur-ws.org
… In this paper, we present a methodology to cre- ate initial training data for voice-controlled devices which helps to design and track dialogue system states … There are two different paradigms for the design of dialogue systems and voice inter- faces …

Learners’ satisfaction comparison between text and speech dialogue-based computer assisted language learning system
SK Choi, OW Kwon, YK Kim – Future-proof CALL: language …, 2018 – books.google.com
… 2017. eurocall2017. 693 Choi, SK, Kwon, OW, Kim, YK, & Lee, YK (2016). Using a dialogue system based on dialogue maps for computer assisted second language learning … 2016. eurocall2016. 546 Dingli, A., & Scerri, D.(2013). Building a hybrid: chatterbot-dialog system …

NIPS Conversational Intelligence Challenge 2017 Winner System: Skill-based Conversational Agent with Supervised Dialog Manager
I Yusupov, Y Kuratov – Proceedings of the 27th International Conference …, 2018 – aclweb.org
… Dialogue Corpus (Lowe et al., 2015)) makes it possible to train end-to-end dialog systems (Sordoni et al … Figure 2: Dialog system and user interaction flow … How NOT to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response …

Quantized-Dialog Language Model for Goal-Oriented Conversational Systems
RC Gunasekara, D Nahamoo, LC Polymenakos… – arXiv preprint arXiv …, 2018 – arxiv.org
… dialog learning track of the sixth edi- tion of the Dialog System Technology Challenges … Gasic, B. Thomson, and JD Williams, “POMDP-based statistical spoken dialog systems: A review … Bengio, AC Courville, and J. Pineau, “Building end-to-end dialogue systems using generative …

Debate Dialog for News Question Answering System ‘NetTv’-Debate Based on Claim and Reason Estimation
R Marumoto, K Tanaka, T Takiguchi… – IWSDS, May, 2018 – me.cs.scitec.kobe-u.ac.jp
… In this study, in order to help users to understand news deeply, we are developing a dialog system which can debate with users about any news … News Navigation System based on Proactive Dia- logue Strategy. Int’l Workshop Spoken Dialogue Systems, 2015D Page 8 …

Impact of Tutor Errors on Student Engagement in a Dialog Based Intelligent Tutoring System
S Afzal, V Shashidhar, R Sindhgatta… – … Conference on Intelligent …, 2018 – Springer
… Student response analysis (henceforth SRA) is the task of labeling student answers with categories that can help a dialog system to generate appropriate and effective feedback on errors [4]. The SRA takes the valid student answer and evaluates it against the model reference …

Intelligent Assistant System based on Natural Language Dialog using Ontology-Based in a Case Study of Computer Science Department, RMUTT
P Nilaphruek, J Krohkaew, N Promthong – 2018 – researchgate.net
… construction and evaluation of health dialog systems for patients and consumers [7]. Such systems can provide health information and counseling using natural language dialog. Nevertheless, they suggested that a further development of plan-based dialog system should apply …

Automatic Data Gathering System for Social Dialog
G Lee, Y Lim, J Choi – 2018 – robotics.auckland.ac.nz
… Challenges in Building Highly Interactive Dialogue Systems. Ai Magazine … Automatic Recognition of Conversational Strategies in the Service of a Socially-Aware Dialog System. Proceedings of the 17th annual SIGDIAL Meeting on Discourse and Dialogue (SIGDIAL 2016) …

The Role of Dialogue User Data in the Information Interaction Design of Conversational Systems
H Candello, C Pinhanez – … Conference of Design, User Experience, and …, 2018 – Springer
… Serban, IVS, Sordoni, A., Bengio, Y., Courville, A., Pineau, J.: Building end-to-end dialogue systems using generative hierarchical neural network models … Yu, Z., Nicolich-Henkin, L., Black, AW, Rudnicky, A.: A Wizard-of-Oz study on a non-task-oriented dialog systems that reacts …

Smart enough to talk with us? foundations and challenges for dialogue capable ai systems
BJ Grosz – Computational Linguistics, 2018 – MIT Press
… I presented my first paper, the paper that laid out the basics of a computational model of discourse structure, at the 1975 ACL meeting. Then, after several decades of research centered on dialogue systems, my research focus shifted to modeling collaboration …

KoMMDia: Dialogue-Driven Assistance System for Fault Diagnosis and Correction in Cyber-Physical Production Systems
J Rahm, M Graube, R Müller, T Klaeger… – 2018 IEEE 23rd …, 2018 – ieeexplore.ieee.org
… For this, our adaptive information space uses five information sources to derive possible cases and their solutions, and accordingly all this information needs to be included in our case descriptions: a) The dialogue system elicits a natural language description provided by the …

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