Academic literature on the topic 'Spoken Dialog System'

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Journal articles on the topic "Spoken Dialog System"

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Kim, A.-Yeong, Hyun-Je Song, and Seong-Bae Park. "A Two-Step Neural Dialog State Tracker for Task-Oriented Dialog Processing." Computational Intelligence and Neuroscience 2018 (October 18, 2018): 1–11. http://dx.doi.org/10.1155/2018/5798684.

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Dialog state tracking in a spoken dialog system is the task that tracks the flow of a dialog and identifies accurately what a user wants from the utterance. Since the success of a dialog is influenced by the ability of the system to catch the requirements of the user, accurate state tracking is important for spoken dialog systems. This paper proposes a two-step neural dialog state tracker which is composed of an informativeness classifier and a neural tracker. The informativeness classifier which is implemented by a CNN first filters out noninformative utterances in a dialog. Then, the neural tracker estimates dialog states from the remaining informative utterances. The tracker adopts the attention mechanism and the hierarchical softmax for its performance and fast training. To prove the effectiveness of the proposed model, we do experiments on dialog state tracking in the human-human task-oriented dialogs with the standard DSTC4 data set. Our experimental results prove the effectiveness of the proposed model by showing that the proposed model outperforms the neural trackers without the informativeness classifier, the attention mechanism, or the hierarchical softmax.
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Demberg, Vera, Andi Winterboer, and Johanna D. Moore. "A Strategy for Information Presentation in Spoken Dialog Systems." Computational Linguistics 37, no. 3 (September 2011): 489–539. http://dx.doi.org/10.1162/coli_a_00064.

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In spoken dialog systems, information must be presented sequentially, making it difficult to quickly browse through a large number of options. Recent studies have shown that user satisfaction is negatively correlated with dialog duration, suggesting that systems should be designed to maximize the efficiency of the interactions. Analysis of the logs of 2,000 dialogs between users and nine different dialog systems reveals that a large percentage of the time is spent on the information presentation phase, thus there is potentially a large pay-off to be gained from optimizing information presentation in spoken dialog systems. This article proposes a method that improves the efficiency of coping with large numbers of diverse options by selecting options and then structuring them based on a model of the user's preferences. This enables the dialog system to automatically determine trade-offs between alternative options that are relevant to the user and present these trade-offs explicitly. Multiple attractive options are thereby structured such that the user can gradually refine her request to find the optimal trade-off. To evaluate and challenge our approach, we conducted a series of experiments that test the effectiveness of the proposed strategy. Experimental results show that basing the content structuring and content selection process on a user model increases the efficiency and effectiveness of the user's interaction. Users complete their tasks more successfully and more quickly. Furthermore, user surveys revealed that participants found that the user-model based system presents complex trade-offs understandably and increases overall user satisfaction. The experiments also indicate that presenting users with a brief overview of options that do not fit their requirements significantly improves the user's overview of available options, also making them feel more confident in having been presented with all relevant options.
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Huang, Ting-Hao, Walter Lasecki, and Jeffrey Bigham. "Guardian: A Crowd-Powered Spoken Dialog System for Web APIs." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 3 (September 23, 2015): 62–71. http://dx.doi.org/10.1609/hcomp.v3i1.13237.

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Natural language dialog is an important and intuitive way for people to access information and services. However, current dialog systems are limited in scope, brittle to the richness of natural language, and expensive to produce. This paper introduces Guardian, a crowd-powered framework that wraps existing Web APIs into immediately usable spoken dialog systems. Guardian takes as input the Web API and desired task, and the crowd determines the parameters necessary to complete it, how to ask for them, and interprets the responses from the API. The system is structured so that, over time, it can learn to take over for the crowd. This hybrid systems approach will help make dialog systems both more general and more robust going forward.
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Griol, David, José Antonio Iglesias, Agapito Ledezma, and Araceli Sanchis. "A Two-Stage Combining Classifier Model for the Development of Adaptive Dialog Systems." International Journal of Neural Systems 26, no. 01 (January 5, 2016): 1650002. http://dx.doi.org/10.1142/s0129065716500027.

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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 history of dialog up to the current moment to predict the next system response. This prediction is performed with an ensemble-based classifier trained for each of the tasks considered, so that a better selection of the next system can be attained weighting the outputs of these specialized classifiers. The codification of the information and the definition of data structures to store the data supplied by the user throughout the dialog makes the estimation of the models from the training data and practical domains manageable. We describe our proposal and its application and detailed evaluation in a practical spoken dialog system.
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Mestrovic, Ana, Luka Bernic, Miran Pobar, Sanda Martincic-Ipsic, and Ivo Ipsic. "A Croatian Weather Domain Spoken Dialog System Prototype." Journal of Computing and Information Technology 18, no. 4 (2010): 309. http://dx.doi.org/10.2498/cit.1001916.

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Ip�i�, Ivo, and Nikola Pave�i�. "An Overview of the Slovenian Spoken Dialog System." Journal of Computing and Information Technology 10, no. 4 (2002): 295. http://dx.doi.org/10.2498/cit.2002.04.04.

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Stoyanchev, Svetlana, and Amanda J. Stent. "Concept Type Prediction and Responsive Adaptation in a Dialogue System." Dialogue & Discourse 3, no. 1 (February 10, 2012): 1–31. http://dx.doi.org/10.5087/dad.2012.101.

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Responsive adaptation in spoken dialog systems involves a change in dialog system behavior in response to a user or a dialog situation. In this paper we address responsive adaptation in the automatic speech recognition (ASR) module of a spoken dialog system. We hypothesize that information about the content of a user utterance may help improve speech recognition for the utterance. We use a two-step process to test this hypothesis: first, we automatically predict the task-relevant concept types likely to be present in a user utterance using features from the dialog context and from the output of first-pass ASR of the utterance; and then, we adapt the ASR's language model to the predicted content of the user's utterance and run a second pass of ASR. We show that: (1) it is possible to achieve high accuracy in determining presence or absence of particular concept types in a post-confirmation utterance; and (2) 2-pass speech recognition with concept type classification and language model adaptation can lead to improved speech recognition performance for post-confirmation utterances.
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Ou, Yang-Yen, Ta-Wen Kuan, Anand Paul, Jhing-Fa Wang, and An-Chao Tsai. "Spoken dialog summarization system with HAPPINESS/SUFFERING factor recognition." Frontiers of Computer Science 11, no. 3 (June 2017): 429–43. http://dx.doi.org/10.1007/s11704-016-6190-2.

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Nagai, Akito. "Spoken dialog system capable of performing natural interactive access." Journal of the Acoustical Society of America 112, no. 1 (2002): 22. http://dx.doi.org/10.1121/1.1500923.

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DELISLE, SYLVAIN, BERNARD MOULIN, and TERRY COPECK. "Surface-marker-based dialog modelling: A progress report on the MAREDI project." Natural Language Engineering 9, no. 4 (November 25, 2003): 325–63. http://dx.doi.org/10.1017/s1351324903003231.

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Most information systems that deal with natural language texts do not tolerate much deviation from their idealized and simplified model of language. Spoken dialog is notoriously ungrammatical, however. Because the MAREDI project focuses in particular on the automatic analysis of scripted dialogs, we needed to develop a robust capacity to analyze transcribed spoken language. This paper summarizes the current state of our work. It presents the main elements of our approach, which is based on exploiting surface markers as the best route to the semantics of the conversation modelled. We highlight the foundations of our particular conversational model, and give an overview of the MAREDI system. We then discuss its three key modules, a connectionist network to recognise speech acts, a robust syntactic analyzer, and a semantic analyzer.
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Dissertations / Theses on the topic "Spoken Dialog System"

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Takeda, Kazuya, Norihide Kitaoka, and Sunao Hara. "Automatic detection of task-incompleted dialog for spoken dialog system based on dialog act N-gram." ISCA(International Speech Communication Association), 2010. http://hdl.handle.net/2237/15498.

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Intilisano, Antonio Rosario. "Spoken dialog systems: from automatic speech recognition to spoken language understanding." Doctoral thesis, Università di Catania, 2016. http://hdl.handle.net/10761/3920.

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Acosta, Jaime Cesar. "Using emotion to gain rapport in a spoken dialog system." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2009. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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Carter, Teresa G. "Five-Factor Model as a Predictor for Spoken Dialog Systems." NSUWorks, 2016. http://nsuworks.nova.edu/gscis_etd/990.

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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 the Five-Factor Method (FFM) and the Wizard of Oz technique for delivering three system initiatives of the SDS, participants interacted with each of the SDS initiatives in scheduling an airline flight. The three system initiatives were constructed as strict system, which did not allow the user control of the interaction; mixed system, which allowed the user some control of the interaction but with a system override; and user system, which allowed the user control of the interaction. In order to eliminate gender bias in using the FFM as the instrument, participants were matched in gender and age. Participants were 18 years old to 70 years old, passed a hearing test, had no disability that prohibited the use of the SDS, and were native English speakers. Participants completed an adult consent form, a 50-question personality assessment as described by the FFM, and the interaction with the SDS. Participants also completed a system preference indication form at the end of the interaction. Observations for efficiency were recorded on paper by the researcher. Although the findings did not show a definitive predictor for a SDS due to the small population sample, by using a multinomial regression approach to the statistical analysis, odds ratios of the data helped draw conclusions that support certain personality factors as important roles in a user’s preference and efficiency in choosing and using a SDS. This gives an area for future research. Also, the presumption that preference and efficiency always match was not supported by the results from two of the three systems. An additional area for future research was discovered in the gender data. Although not an initial part of the research, the data shows promise in predicting preference and efficiency for certain SDS. Future research is indicated.
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Takeda, Kazuya, Norihide Kitaoka, and Sunao Hara. "Detection of task-incomplete dialogs based on utterance-and-behavior tag N-gram for spoken dialog systems." ISCA(International Speech Communication Association), 2011. http://hdl.handle.net/2237/15499.

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Milhorat, Pierrick. "Une plate-forme ouverte pour la conception et l'implémentation de systèmes de dialogue vocaux en langage naturel." Thesis, Paris, ENST, 2014. http://www.theses.fr/2014ENST0087/document.

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L'interaction vocale avec des systèmes automatiques connaît, depuis quelques années, un accroissement dans l'intérêt que lui porte tant le grand public que la communauté de la recherche. Cette thèse s'inscrit dans ce cadre pour aborder le sujet depuis deux points de vue complémentaires. D'une part, celui apparent de la fiabilité, de l'efficacité et de l'utilisabilité de ces interfaces. D'autre part, les aspects de conception et d'implémentation sont étudiés pour apporter des outils de développement aux concepteurs plus ou moins initiés de tels systèmes. A partir des outils et des évolutions dans le domaine, une plate-forme modulaire de dialogue vocal a été agrégée. L'interaction continue, basée sur une "écoute" permanente du système pose des problèmes de segmentation, de débruitage, de capture de son, de sélection des segments adressés au système, etc... Une méthode simple, basée sur la comparaison des résultats de traitements parallèles a prouvé son efficacité, tout comme ses limites pour une interaction continue avec l'utilisateur. Les modules de compréhension du langage forment un sous-système interconnecté au sein de la plate-forme. Ils sont les adaptations d'algorithmes de l'état de l'art comme des idées originales. Le choix de la gestion du dialogue basé sur des modèles de tâches hiérarchiques, comme c'est la cas pour la plate-forme, est argumenté. Ce formalisme est basé sur une construction humaine et présente, de fait, des obstacles pour concevoir, implémenter, maintenir et faire évoluer les modèles. Pour parer à ceux-ci, un nouveau formalisme est proposé qui se transforme en hiérarchie de tâches grâce aux outils associés
Recently, global tech companies released so-called virtual intelligent personal assistants.This thesis has a bi-directional approach to the domain of spoken dialog systems. On the one hand, parts of the work emphasize on increasing the reliability and the intuitiveness of such interfaces. On the other hand, it also focuses on the design and development side, providing a platform made of independent specialized modules and tools to support the implementation and the test of prototypical spoken dialog systems technologies. The topics covered by this thesis are centered around an open-source framework for supporting the design and implementation of natural-language spoken dialog systems. Continuous listening, where users are not required to signal their intent prior to speak, has been and is still an active research area. Two methods are proposed here, analyzed and compared. According to the two directions taken in this work, the natural language understanding subsystem of the platform has been thought to be intuitive to use, allowing a natural language interaction. Finally, on the dialog management side, this thesis argue in favor of the deterministic modeling of dialogs. However, such an approach requires intense human labor, is prone to error and does not ease the maintenance, the update or the modification of the models. A new paradigm, the linked-form filling language, offers to facilitate the design and the maintenance tasks by shifting the modeling to an application specification formalism
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Figueiredo, Sara Cristina Albuquerque. "Development of a dialog system for interaction with robots." Master's thesis, Universidade de Aveiro, 2014. http://hdl.handle.net/10773/14030.

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Mestrado em Engenharia de Computadores e Telemática
Service robots operate in the same environment as humans and perform actions that a human usually performs. These robots must be able to operate autonomously in unknown and dynamic environments, as well as to maneuver with several people and know how to deal with them. By complying with these requirements, they are able to successfully address humans and fulfill their requests whenever they need assistance in a certain task. Natural language communication, including speech that is the most natural way of communication between humans, becomes relevant in the field of Human-Robot Interaction (HRI). By endowing service robots with intuitive spoken interfaces, the specification of the human required tasks is facilitated. However, this is a complicated task to achieve due to the resources involved in creating a sufficiently intuitive spoken interface and because of the difficulty of deploying it in different robots. The main objective of this thesis is the definition, implementation and evaluation of a dialogue system that can be easily integrated into any robotic platform and that functions as a flexible base for the creation of any conversational scenario in the Portuguese language. The system must meet the basic requirements for intuitive and natural communications, namely the characteristics of human-human conversations. A system was developed that functions as a base to give continuity to future work on Spoken Dialog Systems. The system incorporates the client-server architecture, where the client runs on the robot and captures what the user says. The client takes advantage on external dialogue management services. They are executed by the server, which processes the audio obtained, returning an appropriate response given the context of the dialogue. The development was based on a critical analysis of the state of the art in order for the system to be as faithful as possible to what is already done. Through the evaluation phase of the system, it was managed to obtain by few volunteers the conclusion that the main objective was accomplished: a base system was created that is flexible enough to explore different contexts of conversation, such as interacting with children or providing information on a university environment.
Os robôs de serviço operam no mesmo ambiente dos humanos e executam ações que um humano normalmente executaria. Estes robôs devem ser capazes de operar de forma autónoma em ambientes desconhecidos e dinâmicos, assim como de manobrar em ambientes com várias pessoas e de saberem lidar com elas. Ao respeitarem estes requisitos, conseguirão abordar com sucesso os humanos e cumprir as suas solicitações sempre que estes precisem de assistência em alguma tarefa. A comunicação por linguagem natural, nomeadamente a fala que é a forma mais abrangente de comunicação entre humanos, torna-se relevante na área da Interação humano-robô (IHR). Ao dotar os robôs de serviço com sistemas de voz intuitivos facilita-se a especificação das tarefas a realizar. No entanto, é uma tarefa complicada de se realizar devido aos recursos envolvidos na criação de uma interação suficientemente intuitiva e devido à dificuldade de funcionar em diversos robôs. O objetivo principal deste trabalho é a definição, implementação e avaliação de um sistema de diálogo que seja de fácil integração em qualquer sistema robótico e que funcione como uma base flexível para qualquer cenário de conversação na língua Portuguesa. Deve obedecer a requisitos base de comunicação intuitiva e natural, nomeadamente a características de conversas entre humanos. Foi desenvolvido um sistema que funciona como uma base para dar continuidade a trabalho futuro em sistemas de diálogo. O sistema incorpora a arquitetura cliente-servidor onde o cliente é executado no robô e capta o que o utilizador diz. O cliente tira partido de serviços de gestão de diálogo externos ao robô, executados pelo servidor, que processa o áudio obtido, devolvendo uma resposta ao cliente adequada ao contexto do diálogo. O desenvolvimento foi baseado numa análise crítica do estado da arte para se tentar manter fiel ao que já foi feito e de forma a se tomarem as principais decisões durante a implementação. Mediante a fase de avaliação do sistema, tanto a nível do ponto de vista da interação como do programador, conseguiu-se obter por parte de alguns voluntários que o objetivo principal foi cumprido: foi criada uma base suficientemente flexível para explorar diferentes contextos de conversação, nomeadamente interagir com crianças ou fornecimento de informações em ambiente universitário.
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Milhorat, Pierrick. "Une plate-forme ouverte pour la conception et l'implémentation de systèmes de dialogue vocaux en langage naturel." Electronic Thesis or Diss., Paris, ENST, 2014. http://www.theses.fr/2014ENST0087.

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L'interaction vocale avec des systèmes automatiques connaît, depuis quelques années, un accroissement dans l'intérêt que lui porte tant le grand public que la communauté de la recherche. Cette thèse s'inscrit dans ce cadre pour aborder le sujet depuis deux points de vue complémentaires. D'une part, celui apparent de la fiabilité, de l'efficacité et de l'utilisabilité de ces interfaces. D'autre part, les aspects de conception et d'implémentation sont étudiés pour apporter des outils de développement aux concepteurs plus ou moins initiés de tels systèmes. A partir des outils et des évolutions dans le domaine, une plate-forme modulaire de dialogue vocal a été agrégée. L'interaction continue, basée sur une "écoute" permanente du système pose des problèmes de segmentation, de débruitage, de capture de son, de sélection des segments adressés au système, etc... Une méthode simple, basée sur la comparaison des résultats de traitements parallèles a prouvé son efficacité, tout comme ses limites pour une interaction continue avec l'utilisateur. Les modules de compréhension du langage forment un sous-système interconnecté au sein de la plate-forme. Ils sont les adaptations d'algorithmes de l'état de l'art comme des idées originales. Le choix de la gestion du dialogue basé sur des modèles de tâches hiérarchiques, comme c'est la cas pour la plate-forme, est argumenté. Ce formalisme est basé sur une construction humaine et présente, de fait, des obstacles pour concevoir, implémenter, maintenir et faire évoluer les modèles. Pour parer à ceux-ci, un nouveau formalisme est proposé qui se transforme en hiérarchie de tâches grâce aux outils associés
Recently, global tech companies released so-called virtual intelligent personal assistants.This thesis has a bi-directional approach to the domain of spoken dialog systems. On the one hand, parts of the work emphasize on increasing the reliability and the intuitiveness of such interfaces. On the other hand, it also focuses on the design and development side, providing a platform made of independent specialized modules and tools to support the implementation and the test of prototypical spoken dialog systems technologies. The topics covered by this thesis are centered around an open-source framework for supporting the design and implementation of natural-language spoken dialog systems. Continuous listening, where users are not required to signal their intent prior to speak, has been and is still an active research area. Two methods are proposed here, analyzed and compared. According to the two directions taken in this work, the natural language understanding subsystem of the platform has been thought to be intuitive to use, allowing a natural language interaction. Finally, on the dialog management side, this thesis argue in favor of the deterministic modeling of dialogs. However, such an approach requires intense human labor, is prone to error and does not ease the maintenance, the update or the modification of the models. A new paradigm, the linked-form filling language, offers to facilitate the design and the maintenance tasks by shifting the modeling to an application specification formalism
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Vaienti, Andrea. "Assistenti Vocali: Una Panoramica." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019.

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Gli assistenti vocali sono uno dei principali cambiamenti nell'interazione tra uomo e macchina del recente passato e consentono molteplici utilizzi che semplificano ed automatizzano attività potenzialmente noiose e ripetitive. Ad oggi, con il continuo sviluppo della tecnologia, i sistemi ad interazione vocale stanno diventando sempre più parte della nostra vita quotidiana, aprendo un nuovo mondo in cui è possibile comunicare con una macchina interagendo come se fosse un essere umano. Questo è possibile grazie alla sofisticata programmazione di tecnologie come l’elaborazione del linguaggio naturale e l’apprendimento automatico, che consentono la comprensione del comando emesso dall'utente e la generazione di una risposta in tempo reale, potendo così creare un dialogo complesso ed eseguire le diverse richieste dell’utente. I numerosi dispositivi a basso costo sviluppati negli ultimi anni hanno permesso di portare gli assistenti vocali nell'utilizzo quotidiano di tutte le persone, permettendo l’esecuzione di qualsiasi azione, dal porre semplici domande informative alla riproduzione di musica o il controllo di elettrodomestici intelligenti tramite il controllo vocale.
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Meurs, Marie-Jean. "Approche stochastique bayésienne de la composition sémantique pour les modules de compréhension automatique de la parole dans les systèmes de dialogue homme-machine." Phd thesis, Université d'Avignon, 2009. http://tel.archives-ouvertes.fr/tel-00634269.

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Les systèmes de dialogue homme-machine ont pour objectif de permettre un échange oral efficace et convivial entre un utilisateur humain et un ordinateur. Leurs domaines d'applications sont variés, depuis la gestion d'échanges commerciaux jusqu'au tutorat ou l'aide à la personne. Cependant, les capacités de communication de ces systèmes sont actuellement limités par leur aptitude à comprendre la parole spontanée. Nos travaux s'intéressent au module de compréhension de la parole et présentent une proposition entièrement basée sur des approches stochastiques, permettant l'élaboration d'une hypothèse sémantique complète. Notre démarche s'appuie sur une représentation hiérarchisée du sens d'une phrase à base de frames sémantiques. La première partie du travail a consisté en l'élaboration d'une base de connaissances sémantiques adaptée au domaine du corpus d'expérimentation MEDIA (information touristique et réservation d'hôtel). Nous avons eu recours au formalisme FrameNet pour assurer une généricité maximale à notre représentation sémantique. Le développement d'un système à base de règles et d'inférences logiques nous a ensuite permis d'annoter automatiquement le corpus. La seconde partie concerne l'étude du module de composition sémantique lui-même. En nous appuyant sur une première étape d'interprétation littérale produisant des unités conceptuelles de base (non reliées), nous proposons de générer des fragments sémantiques (sous-arbres) à l'aide de réseaux bayésiens dynamiques. Les fragments sémantiques générés fournissent une représentation sémantique partielle du message de l'utilisateur. Pour parvenir à la représentation sémantique globale complète, nous proposons et évaluons un algorithme de composition d'arbres décliné selon deux variantes. La première est basée sur une heuristique visant à construire un arbre de taille et de poids minimum. La seconde s'appuie sur une méthode de classification à base de séparateurs à vaste marge pour décider des opérations de composition à réaliser. Le module de compréhension construit au cours de ce travail peut être adapté au traitement de tout type de dialogue. Il repose sur une représentation sémantique riche et les modèles utilisés permettent de fournir des listes d'hypothèses sémantiques scorées. Les résultats obtenus sur les données expérimentales confirment la robustesse de l'approche proposée aux données incertaines et son aptitude à produire une représentation sémantique consistante
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Books on the topic "Spoken Dialog System"

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Engelbrecht, Klaus-Peter. Estimating Spoken Dialog System Quality with User Models. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-31591-6.

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France) International Workshop on Spoken Dialog Systems (2012 Ermenonville. Natural interaction with robots, knowbots and smartphones: Putting spoken dialog systems into practice. Edited by Mariani Joseph. New York: Springer, 2014.

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Dahl, Deborah, ed. Practical Spoken Dialog Systems. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/978-1-4020-2676-8.

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Anna, Dahl Deborah, ed. Practical spoken dialog systems. Dordrecht: Kluwer Academic Publishing, 2004.

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Schmitt, Alexander, and Wolfgang Minker. Towards Adaptive Spoken Dialog Systems. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-4593-7.

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Schmitt, Alexander. Towards Adaptive Spoken Dialog Systems. New York, NY: Springer New York, 2013.

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Suendermann, David. Advances in commercial deployment of spoken dialog systems. New York: Springer, 2011.

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Suendermann, David. Advances in Commercial Deployment of Spoken Dialog Systems. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9610-7.

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Smith, Ronnie W. Spoken natural language dialog systems: A practical approach. New York: Oxford University Press, 1994.

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Engelbrecht, Klaus-Peter. Estimating Spoken Dialog System Quality with User Models. Springer, 2012.

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Book chapters on the topic "Spoken Dialog System"

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Yang, Zhaojun, Gina-Anne Levow, and Helen Meng. "Crowdsourcing for Spoken Dialog System Evaluation." In Crowdsourcing for Speech Processing, 217–40. Oxford, UK: John Wiley & Sons, Ltd, 2013. http://dx.doi.org/10.1002/9781118541241.ch8.

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Ipšić, Ivo, France Mihelič, and Nikola Pavešić. "Analysis of Different Dialog Strategies in the Slovenian Spoken Dialog System." In Text, Speech and Dialogue, 315–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48239-3_57.

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Ribeiro, Eugénio, Fernando Batista, Isabel Trancoso, José Lopes, Ricardo Ribeiro, and David Martins de Matos. "Assessing User Expertise in Spoken Dialog System Interactions." In Advances in Speech and Language Technologies for Iberian Languages, 245–54. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49169-1_24.

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Wu, Zhiyong, Helen Meng, Hui Ning, and Sam C. Tse. "A Corpus-Based Approach for Cooperative Response Generation in a Dialog System." In Chinese Spoken Language Processing, 614–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11939993_63.

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Deka, Aniruddha, and Manoj Kumar Deka. "Spoken Dialog System in Bodo Language for Agro Services." In Lecture Notes in Electrical Engineering, 623–31. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4765-7_65.

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Adiba, Amalia Istiqlali, Takeshi Homma, Dario Bertero, Takashi Sumiyoshi, and Kenji Nagamatsu. "Delay Mitigation for Backchannel Prediction in Spoken Dialog System." In Lecture Notes in Electrical Engineering, 129–43. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8395-7_10.

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Lopes, José, Maxine Eskenazi, and Isabel Trancoso. "Incorporating ASR Information in Spoken Dialog System Confidence Score." In Lecture Notes in Computer Science, 403–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28885-2_45.

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Ryu, Seonghan, Jaiyoun Song, Sangjun Koo, Soonchoul Kwon, and G. G. Lee. "Detecting Multiple Domains from User’s Utterance in Spoken Dialog System." In Natural Language Dialog Systems and Intelligent Assistants, 101–11. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19291-8_10.

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Jung, Sohyeon, Seonghan Ryu, Sangdo Han, and G. G. Lee. "DietTalk: Diet and Health Assistant Based on Spoken Dialog System." In Natural Language Dialog Systems and Intelligent Assistants, 113–18. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19291-8_11.

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Klarner, Martin, and Bernd Ludwig. "Hybrid Natural Language Generation in a Spoken Language Dialog System." In KI 2004: Advances in Artificial Intelligence, 97–111. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30221-6_9.

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Conference papers on the topic "Spoken Dialog System"

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Nederhof, Mark-Jan, Gosse Bouma, Rob Koeling, and Gertjan van Noord. "Grammatical analysis in the OVIS spoken-dialogue system." In Interactive Spoken Dialog Systems. Morristown, NJ, USA: Association for Computational Linguistics, 1997. http://dx.doi.org/10.3115/1641462.1641476.

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Agarwal, Rajeev. "Towards a PURE spoken dialogue system for information access." In Interactive Spoken Dialog Systems. Morristown, NJ, USA: Association for Computational Linguistics, 1997. http://dx.doi.org/10.3115/1641462.1641479.

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Itoh, Toshihiko, Akihiro Denda, Satoru Kogure, and Seiichi Nakagawa. "A robust dialogue system with spontaneous speech understanding and cooperative response." In Interactive Spoken Dialog Systems. Morristown, NJ, USA: Association for Computational Linguistics, 1997. http://dx.doi.org/10.3115/1641462.1641474.

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Rats, M. M. M., R. J. van Vark, and J. P. M. de Vreught. "Corpus--based information presentation for a spoken public transport information system." In Interactive Spoken Dialog Systems. Morristown, NJ, USA: Association for Computational Linguistics, 1997. http://dx.doi.org/10.3115/1641462.1641481.

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Maier, Elisabeth, Norbert Reithinger, and Jan Alexandersson. "Clarification dialogues as measure to increase robustness in a spoken dialogue system." In Interactive Spoken Dialog Systems. Morristown, NJ, USA: Association for Computational Linguistics, 1997. http://dx.doi.org/10.3115/1641462.1641468.

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Planells, Joaquin, Lluís-F. Hurtado, Encarna Segarra, and Emilio Sanchis. "A multi-domain dialog system to integrate heterogeneous spoken dialog systems." In Interspeech 2013. ISCA: ISCA, 2013. http://dx.doi.org/10.21437/interspeech.2013-459.

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Brison, Eric, and Nadine Vigouroux. "Robust comprehension in a spoken dialog system." In 4th European Conference on Speech Communication and Technology (Eurospeech 1995). ISCA: ISCA, 1995. http://dx.doi.org/10.21437/eurospeech.1995-298.

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Sakuma, Jin, Shinya Fujie, and Tetsunori Kobayashi. "Response Timing Estimation for Spoken Dialog System using Dialog Act Estimation." In Interspeech 2022. ISCA: ISCA, 2022. http://dx.doi.org/10.21437/interspeech.2022-746.

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Stent, Amanda, Svetlana Stenchikova, and Matthew Marge. "DIALOG SYSTEMS FOR SURVEYS: THE RATE-A-COURSE SYSTEM." In 2006 IEEE Spoken Language Technology Workshop. IEEE, 2006. http://dx.doi.org/10.1109/slt.2006.326792.

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Xu, Wei, and Alex Rudnicky. "Language modeling for dialog system." In 6th International Conference on Spoken Language Processing (ICSLP 2000). ISCA: ISCA, 2000. http://dx.doi.org/10.21437/icslp.2000-29.

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Reports on the topic "Spoken Dialog System"

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Bohus, Dan, and Alex Rudnicky. Integrating Multiple Knowledge Sources for Utterance-Level Confidence Annotation in the CMU Communicator Spoken Dialog System. Fort Belvoir, VA: Defense Technical Information Center, November 2002. http://dx.doi.org/10.21236/ada461099.

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Allen, James. Rapidly Customizable Spoken Dialogue Systems. Fort Belvoir, VA: Defense Technical Information Center, January 2009. http://dx.doi.org/10.21236/ada493272.

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Walker, Marilyn, and Rebecca Passonneau. DATE: A Dialogue Act Tagging Scheme for Evaluation of Spoken Dialogue Systems. Fort Belvoir, VA: Defense Technical Information Center, January 2001. http://dx.doi.org/10.21236/ada460992.

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Stibler, Kathleen, and James Denny. A Three-Tiered Evaluation Approach for Interactive Spoken Dialogue Systems. Fort Belvoir, VA: Defense Technical Information Center, January 2001. http://dx.doi.org/10.21236/ada460931.

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Robinson, Susan M., Antonio Roque, Ashish Vaswani, David Traum, Charles Hernandez, and Bill Millspaugh. Evaluation of a Spoken Dialogue System for Virtual Reality Call for Fire Training. Fort Belvoir, VA: Defense Technical Information Center, January 2007. http://dx.doi.org/10.21236/ada461549.

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Sanders, Gregory A., and Audrey N. Le. Effects of Speech Recognition Accuracy on the Performance of DARPA Communicator Spoken Dialogue Systems. Fort Belvoir, VA: Defense Technical Information Center, January 2004. http://dx.doi.org/10.21236/ada523241.

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