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Spoken dialogue systems provide a natural conversational interface to computer applications. In recent years, the substantial improvements in the performance of speech recognition engines have helped shift the research focus to the next component of the dialogue system pipeline: the one in charge of language understanding. The role of this module is to translate user inputs into accurate representations of the user goal in the form that can be used by the system to interact with the underlying application. The challenges include the modelling of linguistic variation, speech recognition errors and the effects of dialogue context. Recently, the focus of language understanding research has moved to making use of word embeddings induced from large textual corpora using unsupervised methods. The work presented in this thesis demonstrates how these methods can be adapted to overcome the limitations of language understanding pipelines currently used in spoken dialogue systems.
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Data-Driven Language Understanding for Spoken Dialogue Systems
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LAP LAMBERT Academic Publishing Mär 2019, 2019
ISBN 10: 6139473039
ISBN 13: 9786139473038
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Spoken dialogue systems provide a natural conversational interface to computer applications. In recent years, the substantial improvements in the performance of speech recognition engines have helped shift the research focus to the next component of the dialogue system pipeline: the one in charge of language understanding. The role of this module is to translate user inputs into accurate representations of the user goal in the form that can be used by the system to interact with the underlying application. The challenges include the modelling of linguistic variation, speech recognition errors and the effects of dialogue context. Recently, the focus of language understanding research has moved to making use of word embeddings induced from large textual corpora using unsupervised methods. The work presented in this thesis demonstrates how these methods can be adapted to overcome the limitations of language understanding pipelines currently used in spoken dialogue systems. 156 pp. Englisch. Codice articolo 9786139473038
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Data-Driven Language Understanding for Spoken Dialogue Systems
Editore:
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139473039
ISBN 13: 9786139473038
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Spoken dialogue systems provide a natural conversational interface to computer applications. In recent years, the substantial improvements in the performance of speech recognition engines have helped shift the research focus to the next component of the dialogue system pipeline: the one in charge of language understanding. The role of this module is to translate user inputs into accurate representations of the user goal in the form that can be used by the system to interact with the underlying application. The challenges include the modelling of linguistic variation, speech recognition errors and the effects of dialogue context. Recently, the focus of language understanding research has moved to making use of word embeddings induced from large textual corpora using unsupervised methods. The work presented in this thesis demonstrates how these methods can be adapted to overcome the limitations of language understanding pipelines currently used in spoken dialogue systems. Codice articolo 9786139473038
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Data-Driven Language Understanding for Spoken Dialogue Systems
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LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139473039
ISBN 13: 9786139473038
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Data-Driven Language Understanding for Spoken Dialogue Systems
Editore:
LAP LAMBERT Academic Publishing Mär 2019, 2019
ISBN 10: 6139473039
ISBN 13: 9786139473038
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Spoken dialogue systems provide a natural conversational interface to computer applications. In recent years, the substantial improvements in the performance of speech recognition engines have helped shift the research focus to the next component of the dialogue system pipeline: the one in charge of language understanding. The role of this module is to translate user inputs into accurate representations of the user goal in the form that can be used by the system to interact with the underlying application. The challenges include the modelling of linguistic variation, speech recognition errors and the effects of dialogue context. Recently, the focus of language understanding research has moved to making use of word embeddings induced from large textual corpora using unsupervised methods. The work presented in this thesis demonstrates how these methods can be adapted to overcome the limitations of language understanding pipelines currently used in spoken dialogue systems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 156 pp. Englisch. Codice articolo 9786139473038
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Data-Driven Language Understanding for Spoken Dialogue Systems
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LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139473039
ISBN 13: 9786139473038
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Paperback. Condizione: Brand New. 156 pages. 8.66x5.91x0.36 inches. In Stock. Codice articolo zk6139473039
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Data-Driven Language Understanding for Spoken Dialogue Systems
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LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139473039
ISBN 13: 9786139473038
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Da: preigu, Osnabrück, Germania
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Taschenbuch. Condizione: Neu. Data-Driven Language Understanding for Spoken Dialogue Systems | Nikola Mrk¿i¿ | Taschenbuch | 156 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786139473038 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 116538699
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