Spoken Dialog Systems 2017


Resources:

  • opendial-toolkit.net .. java-based, domain-independent toolkit for developing spoken dialogue systems

References:

See also:

CLASSiC (Computational Learning in Adaptive Systems for Spoken Conversation) | POMDP (Partially Observable Markov Decision Process) & Dialog SystemsSLP (Spoken Language Programming)


Internationalisation and localisation of spoken dialogue systems
N Laxström, G Wilcock, K Jokinen – Dialogues with Social Robots, 2017 – Springer
Abstract In modern software development, localisation is a straightforward process–assuming internationalisation has been considered during development. The localisation of spoken dialogue systems is less mature, possibly because they differ from common software …

HELPR: A framework to break the barrier across domains in spoken dialog systems
M Sun, YN Chen, AI Rudnicky – Dialogues with Social Robots, 2017 – Springer
Abstract People usually interact with intelligent agents (IAs) when they have certain goals to be accomplished. Sometimes these goals are complex and may require interacting with multiple applications, which may focus on different domains. Current IAs may be of limited …

A Multi-lingual evaluation of the vAssist spoken dialog system. Comparing Disco and RavenClaw
JM Olaso, P Milhorat, J Himmelsbach, J Boudy… – Dialogues with Social …, 2017 – Springer
Abstract vAssist (Voice Controlled Assistive Care and Communication Services for the Home) is a European project for which several research institutes and companies have been working on the development of adapted spoken interfaces to support home care and …

Generative encoder-decoder models for task-oriented spoken dialog systems with chatting capability
T Zhao, A Lu, K Lee, M Eskenazi – arXiv preprint arXiv:1706.08476, 2017 – arxiv.org
Abstract: Generative encoder-decoder models offer great promise in developing domain-general dialog systems. However, they have mainly been applied to open-domain conversations. This paper presents a practical and novel framework for building task …

Spoken language understanding for a nutrition dialogue system
M Korpusik, J Glass – IEEE/ACM Transactions on Audio …, 2017 – ieeexplore.ieee.org
Food logging is recommended by dieticians for prevention and treatment of obesity, but currently available mobile applications for diet tracking are often too difficult and time-consuming for patients to use regularly. For this reason, we propose a novel approach to …

Semantic refinement gru-based neural language generation for spoken dialogue systems
VK Tran, LM Nguyen – arXiv preprint arXiv:1706.00134, 2017 – arxiv.org
Abstract: Natural language generation (NLG) plays a critical role in spoken dialogue systems. This paper presents a new approach to NLG by using recurrent neural networks (RNN), in which a gating mechanism is applied before RNN computation. This allows the …

Natural language generation for spoken dialogue system using rnn encoder-decoder networks
VK Tran, LM Nguyen – arXiv preprint arXiv:1706.00139, 2017 – arxiv.org
Abstract: Natural language generation (NLG) is a critical component in a spoken dialogue system. This paper presents a Recurrent Neural Network based Encoder-Decoder architecture, in which an LSTM-based decoder is introduced to select, aggregate semantic …

Towards End-to-End Spoken Dialogue Systems with Turn Embeddings
AO Bayer, EA Stepanov, G Riccardi – Annual Conference of the …, 2017 – sisl.disi.unitn.it
Abstract Training task-oriented dialogue systems requires significant amount of manual effort and integration of many independently built components; moreover, the pipeline is prone to errorpropagation. End-to-end training has been proposed to overcome these …

A computational model for phonetically responsive spoken dialogue systems
E Raveh, I Steiner, B Möbius – Proc. Interspeech 2017, 2017 – coli.uni-saarland.de
Abstract This paper introduces a model for segment-level phonetic responsiveness. It is based on behavior observed in human-human interaction, and is designed to be integrated into spoken dialogue systems to capture potential phonetic variation and simulate …

Chat Detection in an Intelligent Assistant: Combining Task-oriented and Non-task-oriented Spoken Dialogue Systems
S Akasaki, N Kaji – arXiv preprint arXiv:1705.00746, 2017 – arxiv.org
Abstract: Recently emerged intelligent assistants on smartphones and home electronics (eg, Siri and Alexa) can be seen as novel hybrids of domain-specific task-oriented spoken dialogue systems and open-domain non-task-oriented ones. To realize such hybrid …

Proposal of reminiscence therapy system using spoken dialog to suppress dementia
R Nishimura, T Uchiya, T Hirano… – … (GCCE), 2017 IEEE 6th …, 2017 – ieeexplore.ieee.org
The number of dementia patients has increased in recent years. The burden on caregivers has also increased. Nevertheless, no established treatment for dementia exists. Controlling dementia progression is an important goal of dementia treatment. The reminiscence method …

spoken dialogue systems technology and design
DAL Below – pdfs.semanticscholar.org
But here, you can get it easily this spoken dialogue systems technology and design to read. As known, when you read a book, one to remember is not only the PDF, but also the genre of the book. You will see from the PDF that your book chosen is absolutely right. The proper book option …

Towards End-to-End Modeling of Spoken Language Understanding in a Cloud-based Spoken Dialog System
Y Qian, R Ubale, V Ramanaryanan… – … of Dialogue, 2017 – vikramr.com
Abstract We present an ASR-free end-to-end modeling approach to spoken language understanding for a cloud-based modular spoken dialog system. We evaluate the effectiveness of our approach on crowdsourced data collected from non-native English …

DialPort: Real-World Data for Academia Spoken Dialog Systems
T Zhao, Y Du, K Lee, M Eskenazi – alborz-geramifard.com
Abstract This paper describes the DialPort spoken dialog Portal which gives academic dialog system creators the opportunity to connect with other dialog systems and run studies with real users. Indeed, the interaction with real users challenges system builders in ways …

Multimodal spoken dialog system using state estimation by body motion
T Koseki, T Kosaka – … Electronics (GCCE), 2017 IEEE 6th Global …, 2017 – ieeexplore.ieee.org
Spoken dialog systems are presently used widely. However, some users avoid using them because of poor usability and unattractiveness. In this study, we develop a system that captures the user’s movement and estimates the user state. This function is incorporated into …

Integrating Verbal and Nonvebval Input into a Dynamic Response Spoken Dialogue System.
TY Hu, C Raman, SM Maza, L Gui, T Baltrusaitis… – AAAI, 2017 – aaai.org
Abstract In this work, we present a dynamic response spoken dialogue system (DRSDS). It is capable of understanding the verbal/nonverbal language of users and making instant, situation-aware response. Incorporating with two external systems, MultiSense and email …

Selecting type of response for chat-like spoken dialogue systems based on acoustic features of user utterances
K Ohta, R Marumoto, R Nishimura… – Asia-Pacific Signal and …, 2017 – ieeexplore.ieee.org
This paper describes a method of automatically selecting types of responses in conversational dialog systems, such as back-channel responses, changing the topic, or expanding the topic, using acoustic features extracted from user utterances. These features …

Statistical Spoken Dialogue Systems and the Challenges for Machine Learning
S Young – Proceedings of the Tenth ACM International …, 2017 – dl.acm.org
Abstract This talk will review the principal components of a spoken dialogue system and then discuss the opportunities for applying machine learning for building robust high performance open-domain systems. The talk will be illustrated by recent work at Cambridge …

Dialogue Manager for Spoken Dialogue System
S Mahadik, P Dwivedi, M King, B Zhu… – … On Emanations in … – pdfs.semanticscholar.org
Abstract-A Spoken Dialogue System provide is a computer system able to converse with human with human voice. Dialogue Manager is a component of SDS that manages state of dialogue and dialogue strategy. This report presents the literature survey based on DM. The …

Online Learning of Attributed Bi-Automata for Dialogue Management in Spoken Dialogue Systems
M Serras, MI Torres, A Del Pozo – Iberian Conference on Pattern …, 2017 – Springer
Abstract Online learning of dialogue managers is a desirable but often costly property to obtain. Probabilistic Finite State Bi-Automata (PFSBA) have shown to provide a flexible and adaptive framework to achieve this goal. In this paper, an Attributed PFSBA (A-PSFBA) is …

Reward-Balancing for Statistical Spoken Dialogue Systems using Multi-objective Reinforcement Learning
S Ultes, P Budzianowski, I Casanueva, N Mrkši?… – arXiv preprint arXiv …, 2017 – arxiv.org
Abstract: Reinforcement learning is widely used for dialogue policy optimization where the reward function often consists of more than one component, eg, the dialogue success and the dialogue length. In this work, we propose a structured method for finding a good balance …

Acquisition and Assessment of Semantic Content for the Generation of Elaborateness and Indirectness in Spoken Dialogue Systems
L Pragst, K Yoshino, W Minker, S Nakamura… – Proceedings of the …, 2017 – aclweb.org
Abstract In a dialogue system, the dialogue manager selects one of several system actions and thereby determines the system’s behaviour. Defining all possible system actions in a dialogue system by hand is a tedious work. While efforts have been made to automatically …

A Phonetic Adaptation Module for Spoken Dialogue Systems
E Raveh, I Steiner – … and Pragmatics of Dialogue, 2017 – pdfs.semanticscholar.org
Abstract This paper presents a novel component for spoken dialogue systems, which adds the functionality of adapting the system’s speech output based on the user’s input. The adaptation in done on the phonetic level for adopting the user’s speech characteristics …

Collection of Example Sentences for Non-task-Oriented Dialog Using a Spoken Dialog System and Comparison with Hand-Crafted DB
Y Kageyama, Y Chiba, T Nose, A Ito – International Conference on Human …, 2017 – Springer
Abstract Designing a question-answer database is important to make natural conversation for an example-based dialog system. We focused on the method to collect the example sentences by actual conversations with the system. In this study, examples in the database …

Deep Learning for Acoustic Addressee Detection in Spoken Dialogue Systems
A Pugachev, O Akhtiamov, A Karpov… – Conference on Artificial …, 2017 – Springer
Abstract The addressee detection problem arises in real spoken dialogue systems (SDSs) which are supposed to distinguish the speech addressed to them from the speech addressed to real humans. In this work, several modalities were analyzed, and acoustic data …

Multilingual spoken dialog systems for handheld devices
BML Srivastava – 2017 – researchgate.net
Abstract Technological advancements have made human beings dependent on machines in unprecedented ways. High precision in many tasks and a vast, tractable memory confirms their presence as an integral part of human lifestyle. Human-machine interaction, then, is the …

User-Adaptive A Posteriori Restoration for Incorrectly Segmented Utterances in Spoken Dialogue Systems
K Komatani, N Hotta, S Sato… – Dialogue & Discourse, 2017 – dad.uni-bielefeld.de
Abstract Ideally, the users of spoken dialogue systems should be able to speak at their own tempo. Thus, the systems needs to interpret utterances from various users correctly, even when the utterances contain pauses. In response to this issue, we propose an approach …

Integrating logical reasoning and probabilistic graphical models for spoken dialog system
H Xu – 2017 – ttu-ir.tdl.org
In recent times, partially observable Markov decision processes (POMDPs), an instance of probabilistic sequential decision making under partial observability, have been used to create SDS. These systems use the inherent capabilities of POMDPs to model (and account …

Utterance Intent Classification of a Spoken Dialogue System with Efficiently Untied Recursive Autoencoders
T Kato, A Nagai, N Noda, R Sumitomo, J Wu… – … and Dialogue, 2017 – aclweb.org
Abstract Recursive autoencoders (RAEs) for compositionality of a vector space model were applied to utterance intent classification of a smartphone-based Japanese-language spoken dialogue system. Though the RAEs express a nonlinear operation on the vectors of child …

Natural Language Input for In-Car Spoken Dialog Systems: How Natural is Natural?
P Braunger, W Maier – … SIGdial Meeting on Discourse and Dialogue, 2017 – aclweb.org
Abstract Recent spoken dialog systems are moving away from command and control towards a more intuitive and natural style of interaction. In order to choose an appropriate system design which allows the system to deal with naturally spoken user input, a definition …

LD-SDS: Towards an Expressive Spoken Dialogue System based on Linked-Data
A Papangelis, P Papadakos, M Kotti… – arXiv preprint arXiv …, 2017 – arxiv.org
Abstract: In this work we discuss the related challenges and describe an approach towards the fusion of state-of-the-art technologies from the Spoken Dialogue Systems (SDS) and the Semantic Web and Information Retrieval domains. We envision a dialogue system named …

Extrinsic Versus Intrinsic Evaluation of Natural Language Generation for Spoken Dialogue Systems and Social Robotics
H Hastie, H Cuayáhuitl, N Dethlefs, S Keizer… – Dialogues with Social …, 2017 – Springer
Abstract In the past 10 years, very few published studies include some kind of extrinsic evaluation of an NLG component in an end-to-end-system, be it for phone or mobile-based dialogues or social robotic interaction. This may be attributed to the fact that these types of …

Towards Deep End-of-Turn Prediction for Situated Spoken Dialogue Systems
A Maier, J Hough, D Schlangen – … of INTERSPEECH 2017, 2017 – pub.uni-bielefeld.de
Abstract We address the challenge of improving live end-of-turn detection for situated spoken dialogue systems. While traditionally silence thresholds have been used to detect the user’s end-ofturn, such an approach limits the system’s potential fluidity in interaction …

Leveraging commonsense reasoning and multimodal perception for robot spoken dialog systems
D Lu, S Zhang, P Stone, X Chen – … Systems (IROS), 2017 IEEE …, 2017 – ieeexplore.ieee.org
Probabilistic graphical models, such as partially observable Markov decision processes (POMDPs), have been used in stochastic spoken dialog systems to handle the inherent uncertainty in speech recognition and language understanding. Such dialog systems suffer …

Towards a spoken dialog system capable of acoustic-prosodic entrainment
A Weise – 2017 – pdfs.semanticscholar.org
The term entrainment refers to the tendency of human participants in a conversation to adapt to their interlocutor in various ways. This phenomenon affects virtually all aspects of communication from the length of utterances, to words and grammatical constructions that …

Spoken dialogue BIM systems–an application of big data in construction
I Motawa – Facilities, 2017 – emeraldinsight.com
Purpose With the rapid development in the internet technologies, the applications of big data in construction have seen considerable attention. Currently, there are many input/output modes of capturing construction knowledge related to all construction stages. On the other …

Learning concepts through conversations in spoken dialogue systems
R Jia, L Heck, D Hakkani-Tür… – Acoustics, Speech and …, 2017 – ieeexplore.ieee.org
Spoken dialogue systems must be able to recover gracefully from unexpected user inputs. In many cases, these unexpected utterances may be within the scope of the system, but include previously unseen phrases that the system cannot interpret. In this work, we …

Ontology-based framework for a multi-domain spoken dialogue system
MS Yakoub, SA Selouani – Journal of Ambient Intelligence and …, 2017 – Springer
Abstract Multi-domain spoken dialogue is a challenging field where the objective of the most proposed ideas is to mimic the human–human dialogue. This paper proposes to tackle the domain selection problem in the context of multi-domain spoken dialogue as a set theory …

Miscommunication handling in spoken dialog systems based on error-aware dialog state detection
CH Wu, MH Su, WB Liang – EURASIP Journal on Audio, Speech, and …, 2017 – Springer
Abstract With the exponential growth in computing power and progress in speech recognition technology, spoken dialog systems (SDSs) with which a user interacts through natural speech has been widely used in human-computer interaction. However, error-prone …

Novel Methods for Natural Language Generation in Spoken Dialogue Systems
O Dušek – 2017 – dspace.cuni.cz
Title: Novel Methods for Natural Language Generation in Spoken Dialogue Systems Author: Ond?ej Dušek Department: Institute of Formal and Applied Linguistics Supervisor: Ing. Mgr. Filip Jur?í?ek, Ph. D., Institute of Formal and Applied Linguistics Abstract: This thesis …

Regularized Neural User Model for Goal Oriented Spoken Dialogue Systems
M Serras, MI Torres, A del Pozo – pdfs.semanticscholar.org
Abstract User simulation is widely used to generate artificial dialogues in order to train statistical spoken dialogue systems and perform evaluations. This paper presents a neural network approach for user modeling that exploits an encoderdecoder bidirectional …

Spoken Dialogue Agent System for Writing Resumes while Practicing Job Interviews
K Sumi, K Morita – Theory and Practice of Computation: Proceedings …, 2017 – World Scientific
We propose a system that automatically generates a resume while an agent and a user interact. This research is a prototype for automatically generating dialogue questions without preparing a dialogue pattern in advance. The agent prepares the questions for a job …

Spoken dialog summarization system with HAPPINESS/SUFFERING factor recognition
YY Ou, TW Kuan, A Paul, JF Wang, AC Tsai – Frontiers of Computer …, 2017 – Springer
Abstract This work presents a spoken dialog summarization system with HAPPINESS/SUFFERING factor recognition. The semantic content is compressed and classified by factor categories from spoken dialog. The transcription of automatic speech recognition is then …

Exploring ASR-free end-to-end modeling to improve spoken language understanding in a cloud-based dialog system
Y Qian, R Ubale, V Ramanaryanan… – … (ASRU), 2017 IEEE, 2017 – ieeexplore.ieee.org
Spoken language understanding (SLU) in dialog systems is generally performed using a natural language understanding (NLU) model based on the hypotheses produced by an automatic speech recognition (ASR) system. However, when new spoken dialog  …

Simulation-Based Usability Evaluation of Spoken and Multimodal Dialogue Systems
S Hillmann – 2017 – 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 …

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