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Potential of Dedicated Language Processing Units in Computer Voice Interaction
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In: Idaho Conference on Undergraduate Research (2017)
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Abstract:
This research explores the possibility of using a combination of a phonetic feature based binary encoding format for phonemes and dedicated coprocessors to improve computer voice interactions. While both speech synthesis and speech recognition have made great strides recently current performance still leaves much to be desired. Dedicated graphics cards and binary encoding have had a huge impact on computer graphics in the last two decades, and could do the same for voice interactions. Sources for this research consist primarily of course text books and documentation from open source software projects. Recently Google's TensorFlow AI, and NVIDIA's CUDA make experimental research practical. This research indicates that it would be worthwhile to conduct experimental research on dedicated language processing units that use binary phonetic encoding.
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Keyword:
Artificial Intelligence and Robotics; Computational Linguistics; Graphics and Human Computer Interfaces; Phonetics and Phonology
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URL: https://scholarworks.boisestate.edu/icur/2016/Poster_Session/121
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11 |
An outline of type-theoretical approaches to lexical semantics
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In: ISSN: 2299-856X ; EISSN: 2299-8470 ; Journal of Language Modelling ; https://hal.archives-ouvertes.fr/hal-01802968 ; Journal of Language Modelling, Institute of Computer Science, Polish Academy of Sciences, Poland, 2017, 5 (2), pp.165-178. ⟨10.15398/jlm.v5i2.200⟩ (2017)
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12 |
Classifiers, Sorts, and Base Types in the Montagovian Generative Lexicon and Related Type Theoretical Frameworks for Lexical Compositional Semantics
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In: Modern Perspectives in Type-Theoretical Semantics ; https://hal.archives-ouvertes.fr/hal-01471256 ; Modern Perspectives in Type-Theoretical Semantics, Studies in Linguistics and Philosophy (98), pp.163-188, 2017, 978-3-319-50422-3. ⟨10.1007/978-3-319-50422-3_7⟩ (2017)
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СОСТАВ И СТРУКТУРА КОРПУСА ТЕКСТОВ RUSSIAN DECEPTION BANK, ПРЕДНАЗНАЧЕННОГО ДЛЯ РАЗРАБОТКИ МЕТОДИК ДИАГНОСТИРОВАНИЯ ЛЖИ В РЕЧИ
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14 |
Domain adaptation for statistical machine translation and neural machine translation
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Zhang, Jian. - : Dublin City University. School of Computing, 2017. : Dublin City University. ADAPT, 2017
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In: Zhang, Jian orcid:0000-0001-5659-5865 (2017) Domain adaptation for statistical machine translation and neural machine translation. PhD thesis, Dublin City University. (2017)
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Detection of verbal multi-word expressions via conditional random fields with syntactic dependency features and semantic re-ranking
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In: Maldonado, Alfredo orcid:0000-0001-8426-5249 , Han, Lifeng orcid:0000-0002-3221-2185 , Moreau, Erwan orcid:0000-0001-7692-526X , Alsulaimani, Ashjan, Chowdhury, Koel, Vogel, Carl orcid:0000-0001-8928-8546 and Liu, Qun orcid:0000-0002-7000-1792 (2017) Detection of verbal multi-word expressions via conditional random fields with syntactic dependency features and semantic re-ranking. In: 13th Workshop on Multiword Expressions (MWE 2017), Apr 2017, Valencia, Spain. (2017)
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16 |
Incorporating visual information into neural machine translation
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Calixto, Iacer. - : Dublin City University. School of Computing, 2017. : Dublin City University. ADAPT, 2017
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In: Calixto, Iacer (2017) Incorporating visual information into neural machine translation. PhD thesis, Dublin City University. (2017)
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Dublin City University participation in the VTT track at TRECVid 2017
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In: Afli, Haithem orcid:0000-0002-7449-4707 , Hu, Feiyan orcid:0000-0001-7451-6438 , Du, Jinhua orcid:0000-0002-3267-4881 , Cosgrove, Daniel, McGuinness, Kevin orcid:0000-0003-1336-6477 , O'Connor, Noel E. orcid:0000-0002-4033-9135 , Arazo Sánchez, Eric, Zhou, Jiang orcid:0000-0002-3067-8512 and Smeaton, Alan F. orcid:0000-0003-1028-8389 (2017) Dublin City University participation in the VTT track at TRECVid 2017. In: TRECVid workshop, 13-15 Nov 2017, Gaithersburg, Md., USA. (2017)
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Machine translation of morphologically rich languages using deep neural networks
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Passban, Peyman. - : Dublin City University. School of Computing, 2017. : Dublin City University. ADAPT, 2017
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In: Passban, Peyman (2017) Machine translation of morphologically rich languages using deep neural networks. PhD thesis, Dublin City University. (2017)
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19 |
Entity linking for Tweets
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In: Basile, Pierpaolo orcid:0000-0002-0545-1105 and Caputo, Annalina orcid:0000-0002-7144-8545 (2017) Entity linking for Tweets. Encyclopedia with Semantic Computing and Robotic Intelligence, 1 (1). pp. 1-9. ISSN 2529-7376 (2017)
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How do users perceive information: analyzing user feedback while annotating textual units
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In: Arora, Piyush orcid:0000-0003-0055-345X and Jones, Gareth J.F. orcid:0000-0003-2923-8365 (2017) How do users perceive information: analyzing user feedback while annotating textual units. In: CHIIR 2017 Workshop on Supporting Complex Search Tasks, 11 Mar 2017, Oslo, Norway. (2017)
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