Dialog Systems 2016


dialog system / dialog systems / dialogue system / dialogue systems

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Dialog Systems Meta Guide


Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models.
IV Serban, A Sordoni, Y Bengio, AC Courville, J Pineau – AAAI, 2016 – aaai.org
Abstract We investigate the task of building open domain, conversational dialogue systems based on large dialogue corpora using generative models. Generative models produce system responses that are autonomously generated word-by-word, opening up the

How NOT to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation
CW Liu, R Lowe, IV Serban, M Noseworthy… – arXiv preprint arXiv …, 2016 – arxiv.org
Abstract: We investigate evaluation metrics for end-to-end dialogue systems where supervised labels, such as task completion, are not available. Recent works in end-to-end dialogue systems have adopted metrics from machine translation and text summarization to

A network-based end-to-end trainable task-oriented dialogue system
TH Wen, D Vandyke, N Mrksic, M Gasic… – arXiv preprint arXiv …, 2016 – arxiv.org
Abstract: Teaching machines to accomplish tasks by conversing naturally with humans is challenging. Currently, developing task-oriented dialogue systems requires creating multiple components and typically this involves either a large amount of handcrafting, or acquiring

Syntactic filtering and content-based retrieval of twitter sentences for the generation of system utterances in dialogue systems
R Higashinaka, N Kobayashi, T Hirano… – Situated Dialog in …, 2016 – Springer
Abstract Sentences extracted from Twitter have been seen as a valuable resource for response generation in dialogue systems. However, selecting appropriate ones is difficult due to their noise. This paper proposes tackling such noise by syntactic filtering and content-

Multi-domain neural network language generation for spoken dialogue systems
TH Wen, M Gasic, N Mrksic… – arXiv preprint arXiv …, 2016 – arxiv.org
Abstract: Moving from limited-domain natural language generation (NLG) to open domain is difficult because the number of semantic input combinations grows exponentially with the number of domains. Therefore, it is important to leverage existing resources and exploit

Policy networks with two-stage training for dialogue systems
M Fatemi, LE Asri, H Schulz, J He… – arXiv preprint arXiv …, 2016 – arxiv.org
Abstract: In this paper, we propose to use deep policy networks which are trained with an advantage actor-critic method for statistically optimised dialogue systems. First, we show that, on summary state and action spaces, deep Reinforcement Learning (RL) outperforms

Transfer learning for user adaptation in spoken dialogue systems
A Genevay, R Laroche – … of the 2016 International Conference on …, 2016 – dl.acm.org
Abstract This paper focuses on user adaptation in Spoken Dialogue Systems. It is considered that the system has already been optimised with Reinforcement Learning methods for a set of users. The goal is to use and transfer this prior knowledge to adapt the

On-line active reward learning for policy optimisation in spoken dialogue systems
PH Su, M Gasic, N Mrksic, L Rojas-Barahona… – arXiv preprint arXiv …, 2016 – arxiv.org
Abstract: The ability to compute an accurate reward function is essential for optimising a dialogue policy via reinforcement learning. In real-world applications, using explicit user feedback as the reward signal is often unreliable and costly to collect. This problem can be

Can machines talk? Comparison of Eliza with modern dialogue systems
H Shah, K Warwick, J Vallverdú, D Wu – Computers in Human Behavior, 2016 – Elsevier
Abstract To find if current dialogue systems use the same, psychotherapist questioning technique as Joseph Weizenbaum’s 1960 natural language understanding programme, Eliza, the authors carried out an original experiment comparing five successful artificial

A sequence-to-sequence model for user simulation in spoken dialogue systems
LE Asri, J He, K Suleman – arXiv preprint arXiv:1607.00070, 2016 – arxiv.org
Abstract: User simulation is essential for generating enough data to train a statistical spoken dialogue system. Previous models for user simulation suffer from several drawbacks, such as the inability to take dialogue history into account, the need of rigid structure to ensure

Engine-independent asr error management for dialog systems
J Choi, D Lee, S Ryu, K Lee, K Kim, H Noh… – Situated Dialog in …, 2016 – Springer
Abstract This paper describes a method of ASR (automatic speech recognition) engine independent error correction for a dialog system. The proposed method can correct ASR errors only with a text corpus which is used for training of the target dialog system, and it

Automatic Recognition of Conversational Strategies in the Service of a Socially-Aware Dialog System.
R Zhao, T Sinha, AW Black, J Cassell – SIGDIAL Conference, 2016 – aclweb.org
Abstract In this work, we focus on automatically recognizing social conversational strategies that in human conversation contribute to building, maintaining or sometimes destroying a budding relationship. These conversational strategies include self-disclosure, reference to

On the evaluation of dialogue systems with next utterance classification
R Lowe, IV Serban, M Noseworthy, L Charlin… – arXiv preprint arXiv …, 2016 – arxiv.org
Abstract: An open challenge in constructing dialogue systems is developing methods for automatically learning dialogue strategies from large amounts of unlabelled data. Recent work has proposed Next-Utterance-Classification (NUC) as a surrogate task for building

Evaluation of statistical POMDP-based dialogue systems in noisy environments
S Young, C Breslin, M Gaši?, M Henderson… – Situated Dialog in …, 2016 – Springer
Abstract Compared to conventional hand-crafted rule-based dialogue management systems, statistical POMDP-based dialogue managers offer the promise of increased robustness, reduced development and maintenance costs, and scaleability to large open-

Conditional generation and snapshot learning in neural dialogue systems
TH Wen, M Gasic, N Mrksic… – arXiv preprint arXiv …, 2016 – arxiv.org
Abstract: Recently a variety of LSTM-based conditional language models (LM) have been applied across a range of language generation tasks. In this work we study various model architectures and different ways to represent and aggregate the source information in an

Neural Utterance Ranking Model for Conversational Dialogue Systems.
M Inaba, K Takahashi – SIGDIAL Conference, 2016 – aclweb.org
Abstract In this study, we present our neural utterance ranking (NUR) model, an utterance selection model for conversational dialogue agents. The NUR model ranks candidate utterances with respect to their suitability in relation to a given context using neural networks;

Towards a dialogue system that supports rich visualizations of data
A Kumar, J Aurisano, B Di Eugenio, A Johnson… – Proceedings of the 17th …, 2016 – aclweb.org
Abstract The goal of our research is to support fullfledged dialogue between a user and a system that transforms the user queries into visualizations. So far, we have collected a corpus where users explore data via visualizations; we have annotated the corpus for user

Dialogue systems: modeling and prediction of their dynamics
M Kacprzak, A Sawicka, A Zbrzezny – Proceedings of the Second …, 2016 – Springer
Abstract The aim of this paper is to propose a new model for dialogue games. This model applies interpreted systems which are commonly used to define the language semantics in epistemic and temporal logics. Such an approach allows to apply modern model checking

The SpeDial datasets: datasets for Spoken Dialogue Systems analytics.
J Lopes, A Chorianopoulou, E Palogiannidi, H Moniz… – LREC, 2016 – speech.kth.se
Abstract The SpeDial consortium is sharing two datasets that were used during the SpeDial project. By sharing them with the community we are providing a resource to reduce the duration of cycle of development of new Spoken Dialogue Systems (SDSs). The datasets

A Wizard-of-Oz Study on A Non-Task-Oriented Dialog Systems That Reacts to User Engagement.
Z Yu, L Nicolich-Henkin, AW Black, AI Rudnicky – SIGDIAL Conference, 2016 – aclweb.org
Abstract In this paper, we describe a system that reacts to both possible system breakdowns and low user engagement with a set of conversational strategies. These general strategies reduce the number of inappropriate responses and produce better user engagement. We

Are you talking to me?: Improving the Robustness of Dialogue Systems in a Multi Party HRI Scenario by Incorporating Gaze Direction and Lip Movement of Attendees
V Richter, B Carlmeyer, F Lier… – Proceedings of the …, 2016 – dl.acm.org
Abstract In this paper, we present our humanoid robot” Meka”, participating in a multi party human robot dialogue scenario. Active arbitration of the robot’s attention based on multi-modal stimuli is utilised to observe persons which are outside of the robots field of view. We

SiAM-dp: an open development platform for massively multimodal dialogue systems in cyber-physical environments
R Neßelrath – 2016 – scidok.sulb.uni-saarland.de
Abstract Cyber-physical Environments (CPEs) enhance natural environments of daily life such as homes, factories, offices, and cars by connecting the cybernetic world of computers and communication with the real physical world. While under the keyword of Industrie 4.0,

On model architecture for a children’s speech recognition interactive dialog system
R Kraleva, V Kralev – arXiv preprint arXiv:1605.07733, 2016 – arxiv.org
Abstract: This report presents a general model of the architecture of information systems for the speech recognition of children. It presents a model of the speech data stream and how it works. The result of these studies and presented veins architectural model shows that

The dialport portal: Grouping diverse types of spoken dialog systems
T Zhao, K Lee, M Eskenazi – Workshop on Chatbots and …, 2016 – workshop.colips.org
Abstract. This paper describes a new spoken dialog portal that connects systems produced by the spoken dialog academic research community and gives them access to real users. We introduce a distributed, multi-modal, multi-agent prototype dialog framework that affords

Deep reinforcement learning for multi-domain dialogue systems
H Cuayáhuitl, S Yu, A Williamson, J Carse – arXiv preprint arXiv …, 2016 – arxiv.org
Abstract: Standard deep reinforcement learning methods such as Deep Q-Networks (DQN) for multiple tasks (domains) face scalability problems. We propose a method for multi-domain dialogue policy learning—termed NDQN, and apply it to an information-seeking

OpenDial: A toolkit for developing spoken dialogue systems with probabilistic rules
P Lison, C Kennington – ACL 2016, 2016 – anthology.aclweb.org
Abstract We present a new release of OpenDial, an open-source toolkit for building and evaluating spoken dialogue systems. The toolkit relies on an information-state architecture where the dialogue state is represented as a Bayesian network and acts as a shared

Personalizing a Dialogue System with Transfer Learning
K Mo, S Li, Y Zhang, J Li, Q Yang – arXiv preprint arXiv:1610.02891, 2016 – arxiv.org
Abstract: 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 can overfit and make it difficult to adapt to different user needs. One way to

Large-scale acquisition of commonsense knowledge via a quiz game on a dialogue system
N Otani, D Kawahara, S Kurohashi, N Kaji… – OKBQA …, 2016 – pdfs.semanticscholar.org
Abstract Commonsense knowledge is essential for fully understanding language in many situations. We acquire large-scale commonsense knowledge from humans using a game with a purpose (GWAP) developed on a smartphone spoken dialogue system. We transform

Toward incremental dialogue act segmentation in fast-paced interactive dialogue systems
R Manuvinakurike, M Paetzel, C Qu… – Proceedings of the …, 2016 – pub.uni-bielefeld.de
Abstract In this paper, we present and evaluate an approach to incremental dialogue act (DA) segmentation and classification. Our approach utilizes prosodic, lexico-syntactic and contextual features, and achieves an encouraging level of performance in offline corpus-

Leveraging dialog systems research to assist biomedical researchers’ interrogation of Big Clinical Data
J Hoxha, C Weng – Journal of biomedical informatics, 2016 – Elsevier
Abstract The worldwide adoption of electronic health records (EHR) promises to accelerate clinical research, which lies at the heart of medical advances. However, the interrogation of such Big Data by clinical researchers can be laborious and error-prone, involving iterative

Conversational In-Vehicle Dialog Systems: The past, present, and future
F Weng, P Angkititrakul, EE Shriberg… – IEEE Signal …, 2016 – ieeexplore.ieee.org
Abstract: Automotive technology rapidly advances with increasing connectivity and automation. These advancements aim to assist safe driving and improve user travel experience. Before the realization of a full automation, in-vehicle dialog systems may reduce

A Two-Stage Combining Classifier Model for the Development of Adaptive Dialog Systems
D Griol, JA Iglesias, A Ledezma… – International journal of …, 2016 – World Scientific
This paper proposes a statistical framework to develop user-adapted spoken dialog systems. The proposed framework integrates two main models. The first model is used to predict the user’s intention during the dialog. The second model uses this prediction and the

Non-task-oriented dialogue system considering user’s preference and human relations
S Kobyashi, M Hagiwara – Transactions of the Japanese …, 2016 – keio.pure.elsevier.com
?? In this paper, we propose a non-task-oriented dialogue system considering user’s preference and human relations. The proposed system has the following two features. First, the system estimates user’s emotions from the analysis results of user’s utterances and

Incremental Generation of Visually Grounded Language in Situated Dialogue (demonstration system)
Y Yu, A Eshghi, O Lemon – Proceedings of the 9th International Natural …, 2016 – aclweb.org
… uk Oliver Lemon Interaction Lab Heriot-Watt University o.lemon@hw.ac.uk We present a multi-modal dialogue system for interactive learning of perceptually grounded word meanings from a human tutor (Yu et al., ). The system …

Dialport: A general framework for aggregating dialog systems
T Zhao, K Lee, M Eskenazi – Proceedings of the Workshop on Uphill …, 2016 – aclweb.org
Abstract This paper describes a new spoken dialog portal that connects systems produced by the spoken dialog research community and gives them access to real users. We introduce a prototype dialog framework that affords easy integration with various remote

Bootstrapping incremental dialogue systems: using linguistic knowledge to learn from minimal data
D Kalatzis, A Eshghi, O Lemon – arXiv preprint arXiv:1612.00347, 2016 – arxiv.org
Abstract: We present a method for inducing new dialogue systems from very small amounts of unannotated dialogue data, showing how word-level exploration using Reinforcement Learning (RL), combined with an incremental and semantic grammar-Dynamic Syntax (DS)-

Initial implementation of natural language turn-based dialog system
A Wachtel, S Weigelt, WF Tichy – Procedia Computer Science, 2016 – Elsevier
Abstract Our prototype implements a natural language dialog system for Excel spreadsheets. The work is motivated by a pilot study which shows that novice users have difficulties with the formula language of Excel and need interactive assistance. JustLingo 1

Dialogue System Characterisation by Back-channelling Patterns Extracted from Dialogue Corpus.
M Inoue, H Ueno – LREC, 2016 – lrec-conf.org
Abstract In this study, we describe the use of back-channelling patterns extracted from a dialogue corpus as a mean to characterising text-based dialogue systems. Our goal was to provide system users with the feeling that they are interacting with distinct individuals rather

Bootstrapping Development of a Cloud-Based Spoken Dialog System in the Educational Domain From Scratch Using Crowdsourced Data
V Ramanarayanan… – ETS Research …, 2016 – Wiley Online Library
Abstract We propose a crowdsourcing-based framework to iteratively and rapidly bootstrap a dialog system from scratch for a new domain. We leverage the open-source modular HALEF dialog system to deploy dialog applications. We illustrate the usefulness of this framework

A context-aware natural language generation dataset for dialogue systems
O Dušek, F Jurc?cek – Workshop on Collecting and …, 2016 – pdfs.semanticscholar.org
Abstract We present a novel dataset for natural language generation (NLG) in spoken dialogue systems which includes preceding context (user utterance) along with each system response to be generated, ie, each pair of source meaning representation and target natural

Zara: A Virtual Interactive Dialogue System Incorporating Emotion, Sentiment and Personality Recognition.
P Fung, A Dey, FB Siddique, R Lin… – COLING …, 2016 – pdfs.semanticscholar.org
Abstract Zara, or ‘Zara the Supergirl’is a virtual robot, that can exhibit empathy while interacting with an user, with the aid of its built in facial and emotion recognition, sentiment analysis, and speech module. At the end of the 5-10 minute conversation, Zara can give a

Justification and transparency explanations in dialogue systems to maintain human-computer trust
F Nothdurft, W Minker – Situated Dialog in Speech-Based Human …, 2016 – Springer
Abstract This paper describes a web-based study testing the effects of different explanations on the human-computer trust relationship. Human-computer trust has shown to be very important in keeping the user motivated and cooperative in a human-computer interaction.

Towards Using Conversations with Spoken Dialogue Systems in the Automated Assessment of Non-Native Speakers of English.
DJ Litman, SJ Young, MJF Gales, K Knill… – SIGDIAL …, 2016 – aclweb.org
Abstract Existing speaking tests only require nonnative speakers to engage in dialogue when the assessment is done by humans. This paper examines the viability of using off-the-shelf systems for spoken dialogue and for speech grading to automate the holistic scoring of

Assessing user expertise in spoken dialog system interactions
E Ribeiro, F Batista, I Trancoso, J Lopes… – Advances in Speech …, 2016 – Springer
Abstract Identifying the level of expertise of its users is important for a system since it can lead to a better interaction through adaptation techniques. Furthermore, this information can be used in offline processes of root cause analysis. However, not much effort has been put

Development of dialog system powered by textual educational content
OV Bisikalo, SM Dovgalets, P Pijarski… – … , Industry, and High …, 2016 – spiedigitallibrary.org
The advances in computer technology require an interconnection between a man and computer, more specifically, between complex information systems. The paper is therefore dedicated to creation of dialog systems, able to respond to users depending on the

Two are Better than One: An Ensemble of Retrieval-and Generation-Based Dialog Systems
Y Song, R Yan, X Li, D Zhao, M Zhang – arXiv preprint arXiv:1610.07149, 2016 – arxiv.org
Abstract: Open-domain human-computer conversation has attracted much attention in the field of NLP. Contrary to rule-or template-based domain-specific dialog systems, open-domain conversation usually requires data-driven approaches, which can be roughly

A context-aware natural language generator for dialogue systems
O Dušek, F Jur?í?ek – arXiv preprint arXiv:1608.07076, 2016 – arxiv.org
Abstract: We present a novel natural language generation system for spoken dialogue systems capable of entraining (adapting) to users’ way of speaking, providing contextually appropriate responses. The generator is based on recurrent neural networks and the

Neural Emoji Recommendation in Dialogue Systems
R Xie, Z Liu, R Yan, M Sun – arXiv preprint arXiv:1612.04609, 2016 – arxiv.org
Abstract: Emoji is an essential component in dialogues which has been broadly utilized on almost all social platforms. It could express more delicate feelings beyond plain texts and thus smooth the communications between users, making dialogue systems more

A Comparative Analysis of Crowdsourced Natural Language Corpora for Spoken Dialog Systems.
P Braunger, H Hofmann, S Werner, M Schmidt – LREC, 2016 – pdfs.semanticscholar.org
Abstract Recent spoken dialog systems have been able to recognize freely spoken user input in restricted domains thanks to statistical methods in the automatic speech recognition. These methods require a high number of natural language utterances to train the speech

Context-aware Natural Language Generation for Spoken Dialogue Systems.
H Zhou, M Huang, X Zhu – COLING, 2016 – aclweb.org
Abstract Natural language generation (NLG) is an important component of question answering (QA) systems which has a significant impact on system quality. Most tranditional QA systems based on templates or rules tend to generate rigid and stylised responses

Reinforcement Learning for Turn-Taking Management in Incremental Spoken Dialogue Systems.
H Khouzaimi, R Laroche, F Lefevre – IJCAI, 2016 – ijcai.org
Abstract In this article, reinforcement learning is used to learn an optimal turn-taking strategy for vocal human-machine dialogue. The Orange Labs’ Majordomo dialogue system, which allows the users to have conversations within a smart home, has been upgraded to an

Usefulness, localizability, humanness, and language-benefit: additional evaluation criteria for natural language dialogue systems
B AbuShawar, E Atwell – International Journal of Speech Technology, 2016 – Springer
Abstract Human–computer dialogue systems interact with human users using natural language. We used the ALICE/AIML chatbot architecture as a platform to develop a range of chatbots covering different languages, genres, text-types, and user-groups, to illustrate

Control of proclivity toward selling electricity using persuasive dialog system
K Kitagawa, K Kogiso – Control Systems (ISCS), 2016 SICE …, 2016 – ieeexplore.ieee.org
Abstract: This paper proposes an electricity market model consisting of farm owners, an electricity company and a persuasive dialogue system, to adjust an electricity price by controlling owners’ proclivity toward selling their electricity. Numerical examples confirm that

A dialogue system for evaluating explanations
D Walton – Argument Evaluation and Evidence, 2016 – Springer
Abstract This chapter presents a theory of explanation by building a dialectical system that has speech act rules that define the kinds of moves allowed, such as putting forward an argument, requesting an explanation and offering an explanation. Pre and post-condition

Architecting an intelligent tutoring system with an affective dialogue module
S Jiménez, R Juárez-Ramírez… – Software …, 2016 – ieeexplore.ieee.org
… of TIPOO develop- ment. The prototype version is composed of 7 classes, Fig. 8 shows the dialogue system class diagram. Figure 8. Class diagram of affective dialogue module (models and controllers). C. The Integration of …

Content analyses of personal emergency response calls: Towards a more robust spoken dialogue-based personal emergency response system
V Young – 2016 – search.proquest.com
… Keywords: aging-in-place, assistive technology, personal emergency response, personal emergency response system, content analysis, speech corpus, older adult, spoken dialogue system. iii. Acknowledgments. … Transcripts (p.46). SDS: spoken dialogue system (p.17). …

LVCSR System on a Hybrid GPU-CPU Embedded Platform for Real-Time Dialog Applications.
AV Ivanov, PL Lange, D Suendermann-Oeft – SIGDIAL Conference, 2016 – aclweb.org
… 1 Introduction Many of nowadays’ spoken dialog systems are dis- tributed systems whose major components, such as speech recognition, spoken language under- standing, and dialog managers, are located in the cloud (Suendermann, 2011). …

Using a dialogue system based on dialogue maps for computer assisted second language learning
SK Choi, OW Kwon, YK Kim, Y Lee – CALL communities and …, 2016 – books.google.com
Abstract. In order to use dialogue systems for computer assisted second-language learning systems, one of the difficult issues in such systems is how to construct large-scale dialogue knowledge that matches the dialogue modelling of a dialogue system. This paper describes

Policy optimization of dialogue management in spoken dialogue system for out-of-domain utterances
Y Xu, P Huang, J Tang, Q Huang… – Asian Language …, 2016 – ieeexplore.ieee.org
Abstract: This paper addresses the policy optimization of a dialogue management scheme based on partially observable Markov decision processes (POMDP), which is designed for out-of-domain (OOD) utterances processing in spoken dialogue system. First, POMDP-

lopment of data-intensive dialogue systems: An object-oriented approach” by B. Schewe, K.-D. Schewe
R Studer – … System Concepts: Towards a consolidation of views, 2016 – books.google.com
With respect to a user-centered approach, the paper discusses a lot of important process issues in section 1. Notable examples are “that the software development process has to be an evolutionary one…”, and “… the development process is a learning process. At the

Incremental Generation of Visually Grounded Language in Dialogue (demonstration system)
A Eshghi, Y Yu, O Lemon – The 9th International Natural Language …, 2016 – aclweb.org
… ac. uk Oliver Lemon Interaction Lab Heriot-Watt University o. lemon@ hw. ac. uk We present a multi-modal dialogue system for interactive learning of perceptually grounded word meanings from a human tutor (Yu et al.,). The …

Towards an end to end Dynamic Dialogue System
V Bhalla – researchgate.net
Abstract The large scale development of conversational dialogue systems is one of the challenges hindering advances in an active research area in machine learning, that of interactive learning. This concept paper proposes an end to end dynamic dialogue

Multimodality and Spoken Dialogue Systems
S Johar – Emotion, Affect and Personality in Speech, 2016 – Springer
Abstract Broaching communication from an interdisciplinary perspective, the present chapter attends to the diverse ways in which multimodal principles can be applied to current speech systems to seek natural and seamless human computer interaction capabilities. Offering

Research data supporting” Conditional Generation and Snapshot Learning in Neural Dialogue Systems”
TH Wen, N Mrksic, S Young – 2016 – repository.cam.ac.uk
Cambridge restaurant dialogue domain dataset collected for developing neural network based dialogue systems. The two papers published based on this dataset are: 1. A Network-based End-to-End Trainable Task-oriented Dialogue System 2. Conditional Generation and

YUILA at the NTCIR-12 Short Text Challenge: Combining Twitter Data with Dialogue System Logs.
H Ueno, T Yabuki, M Inoue – NTCIR, 2016 – research.nii.ac.jp
YUILA at the NTCIR-12 Short Text Challenge: Combining Twitter Data with Dialogue System Logs Hiroshi Ueno Yamagata University, Japan tmk56575@st.yamagata- u.ac.jp … The task resembles to the realiza- tion of example-based dialogue systems. In example-based dialogue

Rapid Prototyping of Form-driven Dialogue Systems Using an Open-source Framework.
S Stoyanchev, P Lison, S Bangalore – SIGDIAL Conference, 2016 – aclweb.org
Abstract Most human-machine communication for information access through speech, text and graphical interfaces are mediated by forms–ie lists of named fields. However, deploying form-filling dialogue systems still remains a challenging task due to the effort and skill

Leveraging POMDPs Trained with User Simulations and Rule-based Dialogue Management in a Spoken Dialogue System.
S Quarteroni, G Riccardi, P Roberti – academia.edu
Abstract We have developed a complete spoken dialogue framework that includes rule-based and trainable dialogue managers, speech recognition, spoken language understanding and generation modules, and a comprehensive web visualization interface.

Language Portability for Dialogue Systems: Translating a Question-Answering System from English into Tamil.
S Ravi, R Artstein – SIGDIAL Conference, 2016 – anthology.aclweb.org
Abstract A training and test set for a dialogue system in the form of linked questions and responses is translated from English into Tamil. Accuracy of identifying an appropriate response in Tamil is 79%, compared to the English accuracy of 89%, suggesting that

Research data supporting” On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Systems”
PH Su, M Gasic, N Mrksic, L Rojas-Barahona, S Ultes… – 2016 – repository.cam.ac.uk
This repository contains the data presented in the paper” On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Systems” in ACL 2016. Two separate datasets as described in section 4 of the paper are presented: 1. DialogueEmbedding/It contains the

Sequence-to-Sequence Learning for End-to-End Dialogue Systems
J Van Landeghem – 2016 – researchgate.net
There is strong evidence that over the next few years, dialogue research will quickly move towards large-scale data-driven model approaches, in particular in the form of end-to-end trainable systems as is the case for other language-related applications such as speech

Initiations and Interruptions in a Spoken Dialog System
L Nicolich-Henkin, C Rose, AW Black – … of the 17th Annual Meeting of …, 2016 – aclweb.org
Abstract Choosing an appropriate way for a spoken dialog system to initiate a conversation is a challenging problem, and, if done incorrectly, can negatively affect people’s performance on other important tasks. We describe the results of a study in which

Vaidya: A Spoken Dialog System for Health Domain
P Danda, BML Srivastava, M Shrivastava – Proceedings of the 13th …, 2016 – aclweb.org
Abstract In this paper, we introduce Vaidya, a spoken dialog system which is developed as part of the ITRA1 project. The system is capable of providing an approximate diagnosis by accepting symptoms as freeform speech in real-time on both laptop and hand-held devices.

Designing a Learning Analytics Application to Improve Learner Success in Interactions Based on Multimodal Dialogue Systems
EF Olivares, P Albert, J van Helvert… – … Conference on Immersive …, 2016 – Springer
Abstract Learning processes supported by multimodal interaction systems demand effective tools to measure learner performance and provide meaningful feedback to stakeholders. This paper reviews key features and discusses the implementation of a learning analytics

INTERVIEW WITH AN AVATAR: A REAL-TIME ENGAGEMENT TRACKING-ENABLED CLOUD-BASED MULTIMODAL DIALOG SYSTEM FOR LEARNING AND …
V Ramanarayanan, P Lange, D Pautler, Z Yu… – sail.usc.edu
ABSTRACT Recent advances in immersive computing technology have the potential to accelerate development of engaging intelligent agents that can guide one or multiple phases of learner instruction, learning, and assessment (both formative and summative).

A framework for improving error detection and correction in spoken dialog systems
D Griol, JM Molina – Soft Computing, 2016 – Springer
Abstract Despite the recent improvements in performance and reliably of the different components of dialog systems, it is still crucial to devise strategies to avoid error propagation from one another. In this paper, we contribute a framework for improved error detection and

Privacy in Cloud-Based Data Collection Practices for Commercial Dialogue Systems
C Doran, BA Hockey, E Horowitz – 2016 AAAI Fall Symposium Series, 2016 – aaai.org
Abstract There is a natural tension between obtaining the dream data for development purposes and addressing privacy concerns. Data is so crucial to the development of language technology that addressing this tension between data needs and privacy needs is

Estimating the User’s State before Exchanging Utterances Using Intermediate Acoustic Features for Spoken Dialog Systems.
Y Chiba, T Nose, M Ito, A Ito – IAENG International Journal of Computer …, 2016 – iaeng.org
Abstract—The spoken dialog system (SDS) is an example of a speech interface and has been included in several devices to help users operate the system. The SDS is beneficial for the user because it does not restrict the style of the user’s input utterances, but sometimes

Adapting Spoken Dialog Systems Towards Domains and Users
M Sun – 2016 – lti.cs.cmu.edu
Abstract Spoken dialog systems have been widely used, such as the voice applications or agents in smart phone or smart car environments. However, speech systems are built using the developers’ understanding of the application domain and of potential users in the field,

Modeling a Dialog System for Movie Recommendations Based on The Movie Database
KS Nenova – isl.anthropomatik.kit.edu
Abstract Many people look for a recommendation, when they are choosing which movie to watch. Some ask friends, others search the internet. In this thesis we introduce another way to get a movie recommendation-using a dialog system, that gets to know the users by

Spoken dialog systems based on online generated stochastic finite-state transducers
LF Hurtado, J Planells, E Segarra, E Sanchis – Speech Communication, 2016 – Elsevier
Abstract In this paper, we present an approach for the development of spoken dialog systems based on the statistical modelization of the dialog manager. This work focuses on three points: the modelization of the dialog manager using Stochastic Finite-State

Optimising spoken dialogue systems using Gaussian process reinforcement learning for a large action set
TFW Nicholson, M Gaši? – mlsalt.eng.cam.ac.uk
… Solution Thomas FW Nicholson (tfwn2), Milica Gaši? (mg436) Cambridge University EngineeringDepartment Optimising spoken dialogue systems using Gaussian process reinforcement learning for a large action set View as MDP: Actions: dialogue actions State:

Using Tweets as” Ice-Breaking” Sentences in a Social Dialog System
A Andonov, M Schmidt, J Niehues… – … ; 12. ITG Symposium; …, 2016 – ieeexplore.ieee.org
Abstract: Many goal-oriented spoken dialog systems lack a social component like small talk which often features in human-human communication. In this work we aim to alleviate part of this problem by generating sentences which have the goal to appeal to the user and

Multi-sentence Level Natural Language Generation for Dialogue System
J Cao, G Chen, L Wu, Y Zhang, Z Luo – International Conference on …, 2016 – Springer
Abstract In multi-sentence level natural language generation (NLG) system, the first task is to classify the constraint-value pairs into several groups. Following that, each group will be translate to a talk session. In this paper, we propose three classification algorithms. The first

An Affective Utility Model of User Motivation for Counselling Dialogue Systems
Z Callejas, D Griol – International Workshop on Future and Emerging …, 2016 – Springer
Abstract Counselling dialogue systems are designed to help users to change and monitor their behaviours in order to achieve beneficial goals, such as the acquisition of healthy habits. To be effective, it is important that these systems include a model that accounts for

Task-oriented spoken dialog system for second-language learning
OW Kwon, YK Kim, Y Lee – CALL communities and culture–short …, 2016 – books.google.com
Abstract. This paper introduces a Dialog-Based Computer Assisted second-Language Learning (DB-CALL) system using task-oriented dialogue processing technology. The system promotes dialogue with a second-language learner for a specific task, such as

Dialogue Systems and Dialogue Management
D Burgan – 2016 – dtic.mil
Abstract: A spoken dialogue system (SDS) is a specialised form of computer system that operates as an interface between users and the application, using spoken natural language as the primary means of communication. The motivation for spoken interaction with such

A Deep Learning Methodology for Semantic Utterance Classification in Virtual Human Dialogue Systems
D Datta, V Brashers, J Owen, C White… – … Conference on Intelligent …, 2016 – Springer
Abstract This paper describes the development of a deep learning methodology for semantic utterance classification (SUC) for use in domain-specific dialogue systems. Semantic classifiers need to account for a variety of instances where the utterance for the semantic

Using Dialogue System Technology to Support Interactive History Learning
D Traum – people.ict.usc.edu
Abstract We describe the use of spoken dialogue technology to enhance informal history learning. We describe several uses for this technology, including allowing learners to engage in natural interactions at a historical site, allowing learners to talk with recreations of

A Corpus of Word-Aligned Asked and Anticipated Questions in a Virtual Patient Dialogue System.
A Gokcen, E Jaffe, J Erdmann, M White, D Danforth – LREC, 2016 – ling.ohio-state.edu
Abstract We present a corpus of virtual patient dialogues to which we have added manually annotated gold standard word alignments. Since each question asked by a medical student in the dialogues is mapped to a canonical, anticipated version of the question, the corpus

Designing Interactive Experiences to Explore Artwork Collections: a Multimedia Dialogue System Supporting Visits in Museum Exhibits.
A Origlia, E Leone, A Sorgente, P Vanacore… – AI* CH@ AI* IA, 2016 – ceur-ws.org
Abstract. Speech and natural language processing have a central role in the implementation of systems designed to make the museum more reactive to users’ inputs and to improve the overall interaction quality. In this paper, we present the design and implementation of a

Natural language dialog system considering speaker’s emotion for open-ended conversation
T Takahashi, K Mera, Y Kurosawa… – The Journal of the …, 2016 – asa.scitation.org
To respond appropriately to an utterance, human-like communication system, should consider not only words in the utterance but also the speaker’s emotion. We thus proposed a natural language dialog system that can estimate the user’s emotion from utterances and

Related Word Recommendation Mechanism for Speech Dialogue System
Y Ishida, T Uchiya, K Yamamoto… – … (NBiS), 2016 19th …, 2016 – ieeexplore.ieee.org
Abstract: In recent years, speech dialogue systems have de-veloped remarkably. This university has developed and publishedthe” MMDAgent” voice interaction system toolkit as open source software. MMDAgent uses” Julius” and” HTS” for speech recognition and

Platon: Dialog Management and Rapid Prototyping for Multilingual Multi-user Dialog Systems
M Gropp, A Schmidt, T Kleinbauer, D Klakow – … Conference on Text …, 2016 – Springer
Abstract We introduce Platon, a domain-specific language for authoring dialog systems based on Groovy, a dynamic programming language for the Java Virtual Machine (JVM). It is a fully-featured tool for dialog management that is also particularly suitable for, but not

Exploring Contingent Step Decomposition in a Tutorial Dialogue System.
PW Jordan, PL Albacete, S Katz – UMAP (Extended Proceedings), 2016 – ceur-ws.org
ABSTRACT We explore the effectiveness of a simple algorithm for adaptively deciding whether to further decompose a step in a line of reasoning during tutorial dialogue. We compare two versions of a tutorial dialogue system, Rimac: one that always decomposes a

Evaluating Dialogue Systems
K Kirsch – 2016 – nats-www.informatik.uni-hamburg.de
I am satisfied with the performance of the system Strongly disagree 1–2–3–4–5–6–7 Strongly agree It is simple to use Strongly disagree 1–2–3–4–5–6–7 Strongly agree It is fun to use Strongly disagree 1–2–3–4–5–6–7 Strongly agree It does what I expect it to do Strongly disagree

Vaidya: A Spoken Dialog System for Health Domain
PDBML Srivastava, M Shrivastava – 13th International Conference on …, 2016 – aclweb.org
Abstract In this paper, we introduce Vaidya, a spoken dialog system which is developed as part of the ITRA1 project. The system is capable of providing an approximate diagnosis by accepting symptoms as freeform speech in real-time on both laptop and hand-held devices.

Turn-taking enhancement in spoken dialogue systems with reinforcement learning
H Khouzaimi – 2016 – tel.archives-ouvertes.fr
Incremental dialogue systems are able to process the user’s speech as it is spoken (without waiting for the end of a sentence before starting to process it). This makes them able to take the floor whenever they decide to (the user can also speak whenever she wants, even if the

Spoken dialog system framework supporting multiple concurrent sessions
M Qasim, S Hussain, T Habib… – … and Standardization of …, 2016 – ieeexplore.ieee.org
Abstract: Spoken dialog systems are becoming increasingly popular to provide information to people. Different frameworks are available that provide the necessary infrastructure to develop a dialog system for any domain and language. The support for multiple concurrent

Cooperative dialogue system for decision making based on statistical dialogue management
T Hiraoka – 2016 – isw3.naist.jp
Many researches in the dialogue research community have worked on the constructing goal-oriented dialogue system so far. However though, these previous researches focus on the situation where the dialogue system tries to achieve either the user goal or the system (or its

Introduction to statistical spoken dialogue systems
M Gašic – 2016 – cl.cam.ac.uk
? A spoken dialogue system is a computer system that enables human computer interaction where primary input is speech. … ? Speech does not need to be the only input. We can interact with machines also using touch, gesture or facial expressions and these are multi-modal dialogue

Personalized news event retrieval for small talk in social dialog systems
L Bechberger, M Schmidt, A Waibel… – … ; 12. ITG Symposium; …, 2016 – ieeexplore.ieee.org
Abstract: This paper presents the NewsTeller system which retrieves a news event based on a user query and the user’s general interests. It can be used by a social dialog system to initiate news-related small talk. The NewsTeller system is implemented as a pipeline with

Study on Optimal Spoken Dialogue System for Robust Information Search in the Real World
?? – 2016 – eprints.lib.hokudai.ac.jp
Recently, the spoken dialogue systems those enable users to intuitively and directly operate services and smartphones with voice commands and information search become popular. However, there is still a remaining challenge that there are not many users with the habitual

Spoken dialogue BIM systems–an application of big data in construction
I Motawa – Facilities, 2016 – emeraldinsight.com
… particularly for building maintenance and refurbishment. Design/methodology/approach: The proposed system integrates cloud-based spoken dialogue system and case-based reasoning BIM system. Findings: The system acts as …

Measuring Heterogeneous User Behaviors During the Interaction with Dialog Systems
D Griol, JM Molina – International Conference on Practical Applications of …, 2016 – Springer
Abstract In this paper, we describe a technique to develop simulated user agents that are able to interact with dialog systems. By means of these agents, it is possible not only to automatically evaluate the overall operation of the dialog system, but also to assess the

Ellipsis and Coreference Resolution in a Computerized Virtual Patient Dialogue System
CJ Lin, CW Pao, YH Chen, CT Liu, HH Hsu – Journal of medical systems, 2016 – Springer
Abstract This paper describes the design of an ellipsis and coreference resolution module integrated in a computerized virtual patient dialogue system. Real medical diagnosis dialogues have been collected and analyzed. Several groups of diagnosis-related concepts

Backchanneling via Twitter Data for Conversational Dialogue Systems
M Inaba, K Takahashi – International Conference on Speech and …, 2016 – Springer
Abstract Backchanneling plays a crucial role in human-to-human communication. In this study, we propose a method for generating a rich variety of backchanneling, which is not just limited to simple “hm” or “sure” responses, to realize smooth communication in

Dynamic Control of Proclivity toward Selling Electricity Using Persuasive Dialogue System
K Kitagawa, K Kogiso – SICE Journal of Control, Measurement, and …, 2016 – jstage.jst.go.jp
Abstract: This paper proposes an electricity market model comprising farm owners, an electricity company, and a persuasive dialogue system, to dynamically adjust electricity price by controlling owners’ proclivity toward selling their electricity. Several numerical examples

Zara: A Virtual Interactive Dialogue System Incorporating Emotion, Sentiment and Personality Recognition
PN Fung, A Dey, FB Siddique, R Lin… – … of COLING 2016 …, 2016 – repository.ust.hk
Zara, or ‘Zara the Supergirl’is a virtual robot, that can exhibit empathy while interacting with an user, with the aid of its built in facial and emotion recognition, sentiment analysis, and speech module. At the end of the 5-10 minute conversation, Zara can give a personality

Mimicing the Man: a Persona-based Dialogue System
M Johnson – 2016 – stanford.edu
The purpose of this project is to develop an end-to-end, open domain dialogue system that emulates the persona of a specific person. End-to-end dialogue systems, or less formally known as chat bots, typically exist as conversational agents used to communicate with a

Text classification for spoken dialogue systems
R Sergienko – 2016 – oparu.uni-ulm.de
The main objective of this thesis is the application and evaluation of text classification approaches for speech-based utterance classification problems in the field of advanced spoken dialogue system (SDS) design. SDSs are speech-based human-machine interfaces

Challenges in Building Highly-Interactive Dialog Systems.
NG Ward, D DeVault – AI Magazine, 2016 – pdfs.semanticscholar.org
Abstract Spoken dialog researchers have recently demonstrated highly-interactive systems in several domains. This paper considers how to build on these advances to make systems more robust, easier to develop, and more scientifically significant. We identify key

Target-Based State and Tracking Algorithm for Spoken Dialogue System.
M Li, Z He, J Wu – INTERSPEECH, 2016 – pdfs.semanticscholar.org
Abstract Conventional spoken dialogue systems use frame structure to represent dialogue state. In this paper, we argue that using target distribution to represent dialogue state is much better than using frame structure. Based on the proposed target-based state, two

Effect of sympathetic relation and unsympathetic relation in multi-agent spoken dialogue system
Y Shibahara, K Yamamoto… – … : Concepts, Theory And …, 2016 – ieeexplore.ieee.org
Abstract: Recently, spoken dialog systems using speech recognition technology have been becoming popular. Such as chat-like dialog systems, these systems which do not have any specific purpose are called “Non-Task-oriented spoken dialog system”. In this study, we

A Spoken Dialog System for Coordinating Information Consumption and Exploration
S Fujie, I Fukuoka, A Mugita, H Takatsu… – Proceedings of the …, 2016 – dl.acm.org
Abstract Passive consumption of information is boring in most cases and even painful in some cases, especially when the information content is delivered by employing speech media. The user of a speech-based information delivery system, for example a text-to-

Dialog-based User Interface for a Smart Home System
A Liu – pl.csie.ntut.edu.tw
… Patterns of designing voice command systems and dialog systems have been observed in a speech-based user interface system. … General Terms Smart home systems, user interface, user interaction, patterns Keywords user interface, user interaction, smart home, dialog system …

Managing Linguistic and Terminological Variation in a Medical Dialogue System
LCLDB Pierre, ZS Rosset – 2016 – lrec-conf.org
Abstract We introduce a dialogue task between a virtual patient and a doctor where the dialogue system, playing the patient part in a simulated consultation, must reconcile a specialized level, to understand what the doctor says, and a lay level, to output realistic

Exploratory analysis of real personal emergency response call conversations: considerations for personal emergency response spoken dialogue systems
V Young, E Rochon… – Journal of …, 2016 – jneuroengrehab.biomedcentral.com
Background The purpose of this study was to derive data from real, recorded, personal emergency response call conversations to help improve the artificial intelligence and decision making capability of a spoken dialogue system in a smart personal emergency

An Incremental Dialogue System for Learning Visually Grounded Language (demonstration system)
Y Yu, A Eshghi, O Lemon – SEMDIAL 2016 JerSem – pdfs.semanticscholar.org
Abstract We present a multi-modal dialogue system for interactive learning of perceptually grounded word meanings from a human tutor. The system integrates an incremental, semantic, and bi-directional grammar framework–Dynamic Syntax and Type Theory with

Research Data Supporting” Multi-domain Neural Network Language Generation for Spoken Dialogue Systems”
W Tsung-Hsien, M Gasic, N Mrksic, R Barahona… – 2016 – repository.cam.ac.uk
This is a natural language generation dataset collected from Amazon Mechanical Turk used in this paper” Multi-domain Neural Network Language Generation for Spoken Dialogue Systems” in NAACL-HLT 2016. It contains two domains regarding to consumer electronics:

Computational Interpersonal Communication: Communication Studies and Spoken Dialogue Systems
DJ Gunkel – communication+ 1, 2016 – scholarworks.umass.edu
Abstract With the advent of spoken dialogue systems (SDS), communication can no longer be considered a human-to-human transaction. It now involves machines. These mechanisms are not just a medium through which human messages pass, but now occupy

Small Talk Improves User Impressions of Interview Dialogue Systems.
T Kobori, M Nakano, T Nakamura – SIGDIAL Conference, 2016 – aclweb.org
Abstract This paper addresses the problem of how to build interview systems that users are willing to use. Existing interview dialogue systems are mainly focused on obtaining information from users, thus they just repeatedly ask questions. We propose a method for

Evaluating the spoken dialogue system of a conversational character: A Simulation Study
Y Alvarado, CR Gatica, GV Gil Costa… – … Argentino de Ciencias …, 2016 – sedici.unlp.edu.ar
Currently, there are many applications like human-computer interactions in which speech technology plays an important role. In particular, embodied conversational character interfaces research has produced widely divergent results and it has tended to focus on the

Development environment of a spoken dialogue system based on PRINTEPS
R Nishimura, Y Takase… – … Electronics, 2016 IEEE 5th …, 2016 – ieeexplore.ieee.org
Abstract: In this paper, we describe the development of a spoken dialogue system based on PRINTEPS architecture. This spoken dialogue system is composed of five modules (speech recognition, language understanding, dialogue management, response generation, speech

Information retrieval approach to humorous response generation in dialog systems: a baseline
V Blinov, V Bolotova, P Braslavski – 2016 – dialog-21.ru
ABSTRACT In this paper, we present a baseline IR-based solution to humorous response generation in dialog systems. We describe 1) a corpus consisting of about 48,000 jokes gathered from the VK social network, 2) about 80 test stimuli, 3) BM25 and popularity-based

UT Dialogue System at NTCIR-12 STC.
S Sato, S Ishiwatari, N Yoshinaga, M Toyoda… – …, 2016 – pdfs.semanticscholar.org
ABSTRACT This paper reports a dialogue system developed at the University of Tokyo for participation in NTCIR-12 on the short text conversation (STC) pilot task. We participated in the Japanese STC task on Twitter and built a system that selects plausible responses for an

Root Cause Analysis of Miscommunication Hotspots in Spoken Dialogue Systems.
S Georgiladakis, G Athanasopoulou… – …, 2016 – pdfs.semanticscholar.org
Abstract A major challenge in Spoken Dialogue Systems (SDS) is the detection of problematic communication (hotspots), as well as the classification of these hotspots into different types (root cause analysis). In this work, we focus on two classes of root cause,

Richard: Towards a Dialogue System Supporting Automatic Event Identification
Y Jiang, T Dong, AB Cremers, J Köhler – ksiresearch.org
Abstract A dialogue system, Richard, for free communication on daily issues is under construction. Daily issues are classified into tree-structured event knowledge-base. For each event topic, we retrieve dialogue examples from the Internet. Basic-level Upper Ontologies

Configuration and evaluation of a constrained nutrition dialogue system
E Tuan – 2016 – dspace.mit.edu
Logging daily food intake and nutritional information is a proven way to lose weight. However, research shows that existing approaches for the prevention and treatment of excess weight gain are ineffective, burdensome, and often times, inaccurate. Thus, we have

Automatic creation of scenarios for evaluating spoken dialogue systems via user-simulation
R López-Cózar – Knowledge-Based Systems, 2016 – Elsevier
Abstract This paper proposes a novel technique to create scenarios that can be used by a user simulator for exhaustively evaluating spoken dialogue systems. The scenarios are automatically created from simple scenario-templates that the systems’ developers create

From Dialogue Corpora to Dialogue Systems: Generating a Chatbot with Teenager Personality for Preventing Cyber-Pedophilia
Á Callejas-Rodríguez, E Villatoro-Tello, I Meza… – … Conference on Text …, 2016 – Springer
Abstract A conversational agent, also known as chatbot, is a machine conversational system which interacts with human users via natural language. Traditionally, chatbot technology is built under certain set of “manually” elaborated conversational rules. However, given the

A survey on human machine dialogue systems
S Mallios, N Bourbakis – Information, Intelligence, Systems & …, 2016 – ieeexplore.ieee.org
Abstract: Dialogue systems are computer systems that communicate with a human in spoken or written form. Their popularity has increased in recent years and they attract a large research and development interest. In this paper, a survey on dialogue systems is

Five-Factor Model as a Predictor for Spoken Dialog Systems
T Carter – 2016 – search.proquest.com
Abstract Human behavior varies widely as does the design of spoken dialog systems (SDS). The search for predictors to match a user’s preference and efficiency for a specific dialog interface type in an SDS was the focus of this research. By using personality as described by

Continuously Improving Natural Language Understanding for Robotic Systems through Semantic Parsing, Dialog, and Multi-modal Perception
J Thomason – 2016 – pdfs.semanticscholar.org
Page 1. Continuously Improving Natural Language Understanding for Robotic Systems through Semantic Parsing, Dialog, and Multi-modal Perception Jesse Thomason The University of Texas at Austin jesse@cs.utexas.edu Doctoral Dissertation Proposal November 23, 2016 …

Improving the Probabilistic Framework for Representing Dialogue Systems with User Response Model.
M Li, Z Chen, J Wu – INTERSPEECH, 2016 – pdfs.semanticscholar.org
Abstract A probabilistic framework for goal-driven spoken dialogue systems (SDSs) has been proposed by us in a previous work. In the framework, a target distribution, instead of the frame structure, is used to represent the dialogue state at each turn. The targetbased

Towards a corpus of speech emotion for interactive dialog systems
D Bertero, FB Siddique, P Fung – … and Standardization of …, 2016 – ieeexplore.ieee.org
Abstract: We present and discuss an ongoing data collection and annotation effort to build a large corpus on speech emotion detection. We collected 207 hours of public speech data from TED talks. We highlight the expected relation between the API output emotion

Are we all disfluent in our own special way and should dialogue systems also be?
S Betz, MS Lopez Gambino – Elektronische …, 2016 – pub.uni-bielefeld.de
Abstract: This study explores inter-and intra-speaker variation in use of timemanagement strategies. How do speakers differ in their use of pauses, fillers and other resources aimed at managing time while they plan their next contribution? Taking a rather qualitative approach,

Development of trainable policies for spoken dialogue systems
TC Le – dspace.cuni.cz
Abstract Development of trainable policies for spoken dialogue systems Thanh Le In humanhuman interaction, speech is the most natural and effective manner of communication. Spoken Dialogue Systems (SDS) have been trying to bring that high level

Rational Decision Support with a Natural Language Dialogue System
D Mäurer – 2016 – tuprints.ulb.tu-darmstadt.de
In the past decades, technological advance has led to a revival of natural language dia-logue systems (or conversational agents). Now, conversational agents are used for profes-sional purposes such as customer support, marketing, e-learning, and tutoring purposes,

Automatic dialogue scoring for a second language learning system
JX Huang, KS Lee, OW Kwon… – CALL communities and …, 2016 – books.google.com
… However, considering it is a dialogue system, some factors of unrestricted spontaneous speech should also be considered in the scoring. … In Proceedings of the 2015 International Workshop on Spoen Dialogue Systems (IWSDS). https://doi. …

Multi-label Topic Classification of Turkish Sentences Using Cascaded Approach for Dialog Management System
G So?anc?o?lu, B Köro?lu, O A??n – 2016 – tsdconference.org
… Detecting the topic of customer question would enable the dialogue system to find the corresponding answer more effectively. … Key words: text classification, question answering, dialogue system, multi-label classification 1 Introduction …

Classification of Utterance Acceptability Based on BLEU Scores for Dialogue-Based CALL Systems
R Kuwa, X Wang, T Kato, S Yamamoto – International Conference on Text …, 2016 – Springer
… learning game. IEICE TRANS. Inf. Syst. 97(7), 1830–1841 (2014). 4. Raux, A., Eskenazi, M.: Using task-oriented spoken dialogue systems for language learning: potential, practical applications and challenges. In: InSTIL/ICALL …

THE ROLE OF A COGNITIVE BASED MODEL IN MULTIMODAL INTERACTION SYSTEMS DIALOGUE MANAGEMENT.
JS Prates, SJ Rigo, CA Costa… – … Journal on WWW …, 2016 – search.ebscohost.com
… In Advances in Natural Multimodal Dialogue Systems (pp. 265-285). … (2002) “MATCH: An architecture for multimodal dialogue systems.” Proceedings of the 40th Annual Meeting on Association for Computational Linguistics.Association for Computational Linguistics. Page 14. …

Dialogue enabling speech-to-text user assistive agent system for hearing-impaired person
S Lee, S Kang, DK Han, H Ko – Medical & biological engineering & …, 2016 – Springer
… hearing-impaired. The future work is to improve on the intelligent assistive agent by combining automatic context awareness method to establish the active location-based dialogue system. Acknowledgments. This research was …