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1

Klose, G. Task-oriented modeling for natural language processing systems. Technische Universität Berlin, Fachbereich 13--Informatik, 1993.

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2

Jacobsen, Thomas. Auditory monitoring: On the processing of task-irrelevant ignored spoken language and non-language sounds. Leipziger Universitätsverlag, 2007.

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3

1944-, Krause Jürgen, and Hitzenberger Ludwig, eds. Computer Talk. G. Olms, 1992.

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4

MacWhinney, Brian. Update to The CHILDES project: Tools for analyzing talk. L. Erlbaum, 1992.

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5

Gurikov, Sergey. Algorithmization and programming: preparation for the Unified State Exam in computer science. INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1102077.

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The textbook discusses the basics of algorithmization and programming in Pascal, C++ and Python languages in relation to the tasks of the Unified State Exam (USE) in the discipline "Computer Science and ICT". The levels directly related to the test of the subject's mastery of algorithmic thinking skills, knowledge of the basic constructs of a high-level programming language, and the formation of program development skills in a programming environment are considered. The action of linear, branching and cyclic structures is described; attention is paid to programming based on functions and proce
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6

Bach, Carlo. An interactive knowledge-based shell for configuration tasks. Hartung-Gorre, 1994.

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7

Dellegrotto, John. Computerizing administrative tasks in schools. American Speech-Language-Hearing Association, 1991.

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8

Processing perspectives on task performance. John Benjamins Publishing Company, 2014.

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9

Klose, Gudrun. Task oriented modeling for natural language processing systems. 1993.

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10

Auditory monitoring: On the processing of task-irrelevant ignored spoken language and non-language sounds. Leipziger Universitätsverlag, 2007.

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11

Galley, Michel, Jianfeng Gao, and Lihong Li. Neural Approaches to Conversational AI: Question Answering, Task-Oriented Dialogues and Social Chatbots. Now Publishers, 2019.

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12

Smith, Ronnie W., and D. Richard Hipp. Spoken Natural Language Dialog Systems. Oxford University Press, 1995. http://dx.doi.org/10.1093/oso/9780195091878.001.0001.

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As spoken natural language dialog systems technology continues to make great strides, numerous issues regarding dialog processing still need to be resolved. This book presents an exciting new dialog processing architecture that allows for a number of behaviors required for effective human-machine interactions, including: problem-solving to help the user carry out a task, coherent subdialog movement during the problem-solving process, user model usage, expectation usage for contextual interpretation and error correction, and variable initiative behavior for interacting with users of differing e
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13

Masellis, Maria C. Evidence for temporal processing deficits in children with attention deficit hyperactivity disorder and language impairments on a dichotic listening task. 1998.

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14

Behavior Analysis with Machine Learning Using R. Taylor & Francis Group, 2021.

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15

Ceja, Enrique Garcia. Behavior Analysis with Machine Learning Using R. Taylor & Francis Group, 2021.

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16

Ceja, Enrique Garcia. Behavior Analysis with Machine Learning Using R. CRC Press LLC, 2021.

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17

Ceja, Enrique Garcia. Behavior Analysis with Machine Learning Using R. Taylor & Francis Group, 2021.

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18

Stevenson, Mark, and Yorick Wilks. Word-Sense Disambiguation. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0013.

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Word-sense disambiguation (WSD) is the process of identifying the meanings of words in context. This article begins with discussing the origins of the problem in the earliest machine translation systems. Early attempts to solve the WSD problem suffered from a lack of coverage. The main approaches to tackle the problem were dictionary-based, connectionist, and statistical strategies. This article concludes with a review of evaluation strategies for WSD and possible applications of the technology. WSD is an ‘intermediate’ task in language processing: like part-of-speech tagging or syntactic anal
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19

Antić, Zhenya. Python Natural Language Processing Cookbook: Over 50 recipes to understand, analyze, and generate text for implementing language processing tasks. Packt Publishing, 2021.

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20

Carroll, John. Parsing. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0012.

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This article introduces the concepts and techniques for natural language (NL) parsing, which signifies, using a grammar to assign a syntactic analysis to a string of words, a lattice of word hypotheses output by a speech recognizer or similar. The level of detail required depends on the language processing task being performed and the particular approach to the task that is being pursued. This article further describes approaches that produce ‘shallow’ analyses. It also outlines approaches to parsing that analyse the input in terms of labelled dependencies between words. Producing hierarchical
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21

Liang, Percy, Michael Jordan, and Dan Klein. Probabilistic grammars and hierarchical Dirichlet processes. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.27.

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This article focuses on the use of probabilistic context-free grammars (PCFGs) in natural language processing involving a large-scale natural language parsing task. It describes detailed, highly-structured Bayesian modelling in which model dimension and complexity responds naturally to observed data. The framework, termed hierarchical Dirichlet process probabilistic context-free grammar (HDP-PCFG), involves structured hierarchical Dirichlet process modelling and customized model fitting via variational methods to address the problem of syntactic parsing and the underlying problems of grammar i
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22

Harnish, Stacy M. Anomia and Anomic Aphasia: Implications for Lexical Processing. Edited by Anastasia M. Raymer and Leslie J. Gonzalez Rothi. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199772391.013.7.

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Anomia is a term that describes the inability to retrieve a desired word, and is the most common deficit present across different aphasia syndromes. Anomic aphasia is a specific aphasia syndrome characterized by a primary deficit of word retrieval with relatively spared performance in other language domains, such as auditory comprehension and sentence production. Damage to a number of cognitive and motor systems can produce errors in word retrieval tasks, only subsets of which are language deficits. In the cognitive and neuropsychological underpinnings section, we discuss the major processing
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23

Mikheev, Andrei. Text Segmentation. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0010.

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This article discusses electronic text as essentially just a sequence of characters. Text needs to be segmented at least into linguistic units such as words, punctuation, numbers, alphanumerics, etc. This process is called tokenization. The article mentions that most natural language processing techniques require text to be segmented into sentences as well. It briefly reviews some evaluation metrics and standard resources commonly used for text segmentation tasks. This article presents substantial challenges for computational analysis since tokens are directly attached to each other using pict
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24

Crespo Miguel, Mario. Automatic corpus-based translation of a spanish framenet medical glossary. 2020th ed. Editorial Universidad de Sevilla, 2020. http://dx.doi.org/10.12795/9788447230051.

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Computational linguistics is the scientific study of language from a computational perspective. It aims is to provide computational models of natural language processing (NLP) and incorporate them into practical applications such as speech synthesis, speech recognition, automatic translation and many others where automatic processing of language is required. The use of good linguistic resources is crucial for the development of computational linguistics systems. Real world applications need resources which systematize the way linguistic information is structured in a certain language. There is
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25

Samuelsson, Christer. Statistical Methods. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0019.

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Statistical methods now belong to mainstream natural language processing. They have been successfully applied to virtually all tasks within language processing and neighbouring fields, including part-of-speech tagging, syntactic parsing, semantic interpretation, lexical acquisition, machine translation, information retrieval, and information extraction and language learning. This article reviews mathematical statistics and applies it to language modelling problems, leading up to the hidden Markov model and maximum entropy model. The real strength of maximum-entropy modelling lies in combining
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26

Making things talk. Maker Media, 2017.

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27

Mitkov, Ruslan, ed. The Oxford Handbook of Computational Linguistics. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.001.0001.

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The Oxford Handbook of Computational Linguistics features thirty-eight articles commissioned from experts all over the world. The book describes major concepts, methods, and applications in computational linguistics. Part I looks at linguistic fundamentals and provides an overview of the field suitable for senior undergraduates and non-specialists from other fields of linguistics and related disciplines. Part II describes current tasks, techniques, and tools in natural language processing and aims to meet the needs of post-doctoral workers and others embarking on computational language researc
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28

The childes Project: Tools for Analyzing Talk. 2nd ed. Lawrence Erlbaum, 1991.

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29

Jacquemin, Christian, and Didier Bourigault. Term Extraction and Automatic Indexing. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0033.

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Terms are pervasive in scientific and technical documents and their identification is a crucial issue for any application dealing with the analysis, understanding, generation, or translation of such documents. In particular, the ever-growing mass of specialized documentation available on-line, in industrial and governmental archives or in digital libraries, calls for advances in terminology processing for tasks such as information retrieval, cross-language querying, indexing of multimedia documents, translation aids, document routing and summarization, etc. This article presents a new domain o
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30

Talk to Your Computer: Speech Recognition Made Easy. Waveside Publishing, 1999.

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31

Trost, Harald. Morphology. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0002.

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This article discusses in detail computational morphology with examples from various languages. It deals with the processing of words in both their graphemic, i.e. written, and their phonemic, i.e. spoken form. It has a wide range of practical applications such as spelling correction or automated hyphenation. It further seeks the fact that these tasks may seem simple to a human but they pose hard problems to a computer program. This article provides insights into why this is so and what techniques are available to tackle these tasks. It discusses the sort of information that is expressed by mo
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32

Smakotina, Natalia A., Anna A. Teleguz, Lyudmila I. Tolstobrova, and Marina V. Gordienko. English for Food Production Technologists. English for Food Industry Technologists. Novosibirsk State Technical University, 2022. http://dx.doi.org/10.17212/978-5-7782-4780-2.

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The textbook "English for Food Production Technologists" English for food technologists is intended for second-year students specializing in the field of training "Product technology and catering organization (19.03.04 ): Profile: Technology and Organization of Restaurant Service", "Management: Profile: Management in the food industry" (38.03.02). The purpose of the textbook is to form a foreign language communicative competence based on a given situational professionally – oriented context. The structure of the textbook. The textbook consists of four modules with three sections, blocks of con
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33

Lopatenko, Andrei, and Thushan Ganegedara. Natural Language Processing with TensorFlow: The Definitive NLP Book to Implement the Most Sought-After Machine Learning Models and Tasks. Packt Publishing, Limited, 2022.

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34

Igoe, Tom. Making Things Talk: Practical Methods for Connecting Physical Objects. Maker Media, Incorported, 2007.

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35

Making things talk: Learning by discovery. 2nd ed. O'Reilly Media, 2011.

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36

(Editor), Rupert Wegerif, and Peter Scrimshaw (Editor), eds. Computers and Talk in the Primary Classroom (Language and Education Library , No 12). Multilingual Matters Limited, 1998.

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37

Igoe, Tom. Making Things Talk: Using Sensors, Networks, and Arduino to See, Hear, and Feel Your World. O'Reilly Media, Incorporated, 2011.

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38

Making Things Talk: Using Sensors, Networks, and Arduino to See, Hear, and Feel Your World. Maker Media, Inc, 2011.

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39

Mastering Transformers : Build State-Of-The-Art Models for Natural Language Processing and Multi-Modal Tasks: The Journey from BERT to CLIP and Stable Diffusion. Packt Publishing, Limited, 2024.

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40

Ufimtseva, Nataliya V., Iosif A. Sternin, and Elena Yu Myagkova. Russian psycholinguistics: results and prospects (1966–2021): a research monograph. Institute of Linguistics, Russian Academy of Sciences, 2021. http://dx.doi.org/10.30982/978-5-6045633-7-3.

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The monograph reflects the problems of Russian psycholinguistics from the moment of its inception in Russia to the present day and presents its main directions that are currently developing. In addition, theoretical developments and practical results obtained in the framework of different directions and research centers are described in a concise form. The task of the book is to reflect, as far as it is possible in one edition, firstly, the history of the formation of Russian psycholinguistics; secondly, its methodology and developed methods; thirdly, the results obtained in different research
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41

Shengelia, Revaz. Modern Economics. Universal, Georgia, 2021. http://dx.doi.org/10.36962/rsme012021.

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Economy and mankind are inextricably interlinked. Just as the economy or the production of material wealth is unimaginable without a man, so human existence and development are impossible without the wealth created in the economy. Shortly, both the goal and the means of achieving and realization of the economy are still the human resources. People have long ago noticed that it was the economy that created livelihoods, and the delays in their production led to the catastrophic events such as hunger, poverty, civil wars, social upheavals, revolutions, moral degeneration, and more. Therefore, the
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