Natural language and machine translation Books

Book SynopsisThis book constitutes the proceedings of the 6th International Workshop on Chatbot Research and Design, CONVERSATIONS 2022, which was held during November 2022.The 12 papers included in this volume were carefully reviewed and selected from a total of 27 submissions. They were organized in topical sections named: chatbot users and user experience; chatbot design and applications.

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Book SynopsisThe two-volume set LNAI 13495 and LNAI 13496, constitute the refereed post-workshop proceedings of the 23rd Chinese Lexical Semantics Workshop, CLSW 2022, held as a virtual event, during May 14-15, 2022. In total the two-volume set includes 39 full papers and 19 short papers which were carefully reviewed and selected from 214 submissions. They are organized in the following topical sections: lexical semantics; corpus linguistics; general linguistics, lexical resources; computational linguistics, applications of natural language processing.Table of ContentsSemantic Prosody: The Study of Gei in BA and BEI Constructions.- Corpus-Based Lexical Features and Thematic Analysis of China's Five-Year Plan for the 21st Century.- Corpus Construction for Generating Knowledge Graph of Sichuan Cuisine.- Building a Semantically Annotated Corpus of Chinese Directional Complements.- BBAE: a Method for Few-Shot Charge Prediction with Data Augmentation and Neural Network.- A Preliminary Quantitative Investigation of Chinese Monosyndetic Coordinators.- Frequency in Chinese Ballad Song Lyrics: A Quantitative Morpheme-Based Study.- Gender-Related Use of Tonal Patterns in Mandarin Chinese: The Case of Sentence-Final Particle ma.- A Quantitative Study on the Low-Degree Adverb “Shaowei”--A Stylistic Perspective.- The Relationship of Lexical Richness to the Quality of CSL Writings.- Research on Korean "Long-before-Short" Preference from the Perspective of Dependency Distance.- A Dependency Structure Annotation for Modality in Chinese News Articles.- How Do People React to COVID-19 Vaccination? A Corpus-based Study of Macau Netizens’ Online Comments.- REFORM IS A JOURNEY: Conceptualizing China’s Reform and Opening-up in the Official News Discourse.- The Emotion Code in Sensory Modalities: An investigation of the relationship between sensorimotor dimensions and emotional valence-arousal.- From Genitive to Conjunctive: Coordinator li55 in Chongqing Mandarin.- The Prediction Function of Collocations on the Quality Assessment of Chinese Second Language Learners’ Oral Production.- Verb Raising and the Construction Mechanism of Synthetic Compounds.- The Construction of Grammatical Synonym Resources of Disyllabic Verbs in Modern Chinese.- Extraction and Application of Verb Event Structure Based on Grammatical Knowledge-Base of Contemporary Chinese(GKB).- Semantic Classification of Adverbial Nouns Based on Syntactic Treebank and Construction of Collocation Da-tabase.- A Framework for Dictionary Development: Building Domain Dictionary for Legal Field.- RoBERTa: An Efficient Dating Method of Ancient Chinese Texts.- Building a Corpus for Chinese Causality Extraction in Futures Domain.- Research on Hotspots of Educational Application of Natural Language Processing Based on LDA Topic Model.- A Metrological Study on the Spatial Narrative of the Qishu Genre: Take A Dream of Red Mansions and Water Margin as Examples.- Chinese Argument Identification Based on Bert.- Irony Recognition in Chinese Text Based on Linguistic Features and Attention Mechanism.- A Phrase Disambiguation Method of “Quanbu V de N” Based on SBERT Model and Syntactic Rule.- Automatic Recognition of Verb-complement Separable Words Based on BCC.

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Book SynopsisThis book constitutes the refereed proceedings of the 14th International Conference on Combinatorics on Words, WORDS 2023, held in Umeå, Sweden, during June 12–16, 2023.The 19 contributed papers presented in this book were carefully reviewed and selected from 28 submissions. In addition, the volume also contains 3 invited papers. WORDS is the main conference series devoted to combinatorics on words. This area is connected to several topics from computer science and mathematics, including string algorithms, automated proofs, discrete dynamics, number theory and, of course, classical combinatoricsTable of Contents​Invited Papers: Minimal Complexities for Infinite Words Written with d Letters.- Alternate Base Numeration Systems.- On the number of distinct squares in finite sequences: some old and new results. Contributed Papers: Ranking and Unranking k-Subsequence Universal Words.- Longest common subsequence with gap constraints.- On Substitutions Preserving their Return Sets.- Recurrence and frequencies.- Sturmian and infinitely desubstitutable words accepted by an ω-automaton.- String attractors for factors of the Thue-Morse word.- Critical exponent of Arnoux-Rauzy sequences.- On a class of 2-balanced sequences.- Order conditions for languages.- On Sensitivity of Compact Directed Acyclic Word Graphs.- Smallest and Largest Block Palindrome Factorizations.- String attractors of fixed points of k-bonacci-like morphisms.- Magic Numbers in Periodic Sequences.- Dyck Words, Pattern Avoidance, and Automatic Sequences.- Rudin-Shapiro Sums Via Automata Theory and Logic.- Automaticity and Parikh-collinear morphisms.- On the solution sets of entire systems of word equations.- On arch factorization and subword universality for words and compressed words.- Characteristic sequences of the sets of sums of squares as columns of cellular automata.

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Book SynopsisThis book constitutes refereed proceedings from the First International Conference on Speech and Language Technologies for Low-resource Languages, SPELLL 2022, held in Kalavakkam, India, in November 2022. The 25 presented papers were thoroughly reviewed and selected from 70 submissions. The papers are organised in the following topical sections: ​language resources; language technologies; speech technologies; multimodal data analysis; fake news detection in low-resource languages (regional-fake); low resource cross-domain, cross-lingualand cross-modal offensie content analysis (LC4).Table of ContentsLanguage Resources.- Language Technologies.- Speech Technologies.- Multimodal data analysis.- Fake News Detection in Low-Resource Languages (Regional-Fake).- Low Resource Cross-Domain, Cross-Lingualand Cross-Modal Offensie Content Analysis (LC4).

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Book SynopsisThis book constitutes the refereed proceedings of the 27th International Conference on Developments in Language Theory, DLT 2023, held in Umeå, Sweden, during June 12–16, 2023. The 20 full papers included in this book were carefully reviewed and selected from 32 submissions (31 regular ones and one invited).The DLT conference series provides a forum for presenting current developments informal languages and automata. Its scope is very general and includes, among others, the following topics and areas: grammars, acceptors and transducers for words; trees and graphs; relations between formal languages and artificial neural networks; algebraic theories of automata; algorithmic, combinatorial, and algebraic properties of words and languages; variable length codes; symbolic dynamics; cellular automata; groups and semigroups generated by automata; polyominoes and multidimensional patterns; decidability questions; image manipulation and compression; efficient text algorithms; relationships to cryptography, concurrency, complexity theory, and logic; bio-inspired computing; and quantum computing.Table of ContentsTransducers and the Power of Delay.- When the Map is More Exact than the Terrain.- Formal Languages and the NLP Black Box.- On Structural Tractability Parameters for Hard String Problems.- Jumping Automata over Infinite Words.- Isometric Words based on Swap and Mismatch Distance.- Set Augmented Finite Automata over Infinite Alphabets.- Fast detection of specific fragments against a set of sequences.- Weak Inverse Neighborhoods of Languages.- The exact state complexity for the composition of Root and reversal.- Bit catastrophes for the Burrows-Wheeler Transform.- The Domino problem is undecidable on every rhombus subshift.- Synchronization of Parikh Automata.- Completely Distinguishable Automata and the Set of Synchronizing Words.- Zielonka DAG Acceptance and Regular Languages over Infinite Words.- On Word Representable and Multi-Word Representable Graphs.- On the Simon's Congruence Neighborhood of Languages.- Tree-Walking-Storage Automata.- Rewriting rules for arithmetics in alternate base systems.- Synchronizing Automata with Coinciding Cycles.- Approaching Repetition Thresholds Via Local Resampling and Entropy Compression.- Languages Generated by Conjunctive Query Fragments of FC[REG].- Groups whose word problems are accepted by abelian G-automata.

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Book SynopsisThis book constitutes the refereed proceedings of the 28th International Conference on Applications of Natural Language to Information Systems, NLDB 2023, held in Derby, UK, in June 21–23, 2023The 31 full papers and 14 short papers included in this book were carefully reviewed and selected from 89 submissions. They focus on the developments of the application of natural language to databases and information systems in the wider meaning of the term.Table of ContentsLarge Language Models in the Workplace: A Case Study on Prompt Engineering for Job Type Classification.- How Challenging is Multimodal Irony Detection?.- Less is more: A Prototypical Framework for Efficient Few-Shot Named Entity Recognition.- Don’t Lose the Message while Paraphrasing: A Study on Content Preserving Style Transfer.- A Review of Parallel Corpora for Automatic Text Simplification. Key Challenges Moving Forward.- Explaining a Deep Learning Model for Aspect-Based Sentiment Classification Using Post-hoc Local Classifiers.- Arabic Privacy Policy Corpus and Classification.- SmartEDU: Accelerating Slide Deck Production with Natural Language Processing.- Explainable Integration of Knowledge Graphs using Large Language Models.- Cross-domain and cross-language irony detection: The impact of bias on models’ generalization.- Prompt and Instruction-Based Tuning for Response Generation in Conversational Question Answering.- IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran.- Comparing object recognition models and studying hyperparameter selection for the detection of bolts.- Morphosyntactic Evaluation for Text Summarization in Morphologically Rich Languages: A Case Study for Turkish.- Building Knowledge Graphs in Heliophysics and Astrophysics.- Text to Image Synthesis Using Bridge Generative Adversarial Network and Char CNN Model.- Evaluation of transformer-based models for punctuation and capitalization restoration in Spanish and Portuguese.- Sentence-to-Label Generation Framework for Multi-task Learning of Japanese Sentence Classification and Named Entity Recognition.- Could KeyWord Masking strategy improve language model?.- Regularization, Semi-supervision, and Supervision for a Plausible Attention-Based Explanation.- Node-Weighted Centrality Ranking for Unsupervised Long Document Summarization.- Characterization of the city of the future from a science fiction corpus.- On the Rule-based Extraction of Statistics Reported in Scientific Papers.- GRAM: Grammar-Based Refined-Label Representing Mechanism in the Hierarchical Semantic Parsing Task.- Expanding Domain-specific Knowledge Graphs with Unknown Facts .- Knowledge Graph Representation Learning via Generated Descriptions.- LonXplain: Lonesomeness as a Consequence of Mental Disturbance in Reddit Posts.- A Comparative Study of Evaluation Metrics for Long-Document Financial Narrative Summarization with Transformers.- Effective Information Retrieval, Question Answering and Abstractive Summarization on Large-scale Biomedical Document Corpora.- Abstractive Summarization Based Question-Answer System for Structural Information.- Adversarial Capsule Networks for Romanian Satire Detection and Sentiment Analysis.- A Few-shot Approach to Resume Information Extraction via Prompts.- Decoding Strategies for Code Conciseness and Efficiency in Transformer-Generated Programs.- SP-BERT: A Language Model for Political Text in Scandinavian Languages.- Improving Context-Awareness on Multi-Turn Dialogue Modeling with Extractive Summarization Techniques.- Document Knowledge Transfer for Aspect-Based Sentiment Classification Using a Left-Center-Right Separated Neural Network with Rotatory Attention.- Argument and counter-argument generation: a critical survey.- Novel Benchmark Data Set for Automatic Error Detection and Correction.- Weakly-Supervised Multimodal Learning for Predicting the Gender of Twitter Users.- Cross-Domain Toxic Spans Detection.- How shall a machine call a thing?.- Detecting Artificially Generated Academic Text: the Importance of Mimicking Human Utilization of Large Language Models.- Leveraging Small-BERT and Bio-BERT for Abbreviation Identification in Scientific Text.- RoBERTweet: A BERT Language Model for Romanian Tweets.- Evaluating the Effect of Letter Case on Named Entity Recognition Performance.

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Book SynopsisPreface to the third edition.- Preface to the second edition.- Preface to the first edition.- 1. An Overview of Language Processing.- 2. A Tour of Python.- 3. Corpus Processing Tools.- 4. Encoding and Annotation Scheme.- 5. Python for Numerical Computations.- 6. Topics in Information Theory and Machine Learning.- 7. Linear and Logistic Regression.- 8. Neural Networks.- 9. Counting and Indexing Words.- 10. Dense Vector Representations.- 11. Word Sequences.- 12. Words, Parts of Speech, and Morphology.- 13. Subword Segmentation.- 14. Part-of-Speech and Sequence Annotation.- 15. Self-Attention and Transformers.- 16. Pretraining an Encoder: The BERT Language Model.- 17. Sequence-to-Sequence Architectures: Encoder-Decoders and Decoders.- Index.- References.

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Book Synopsis1. Large Language Models: An Introduction.- 2. Pre-trained Models.- 3. Prompt-based Learning.- 4. LLM Adaptation and Utilization.- 5. Tuning for LLM Alignment.- 6. LLM Challenges and Solutions.- 7. Retrieval-Augmented Generation.- 8. LLMs in Production.- 9. Multimodal LLMs.- 10. LLMs: Evolution and New Frontiers.- Appendix.

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Book SynopsisPreface.- 1. Introduction to Natural Language Processing in High-Stakes Domains.- 2. NLP in Medicine: Enhancing Diagnostics and Patient Care.- 3. NLP in the Legal Domain: Ensuring Precision and Compliance.- 4. Introduction to NLP in Finance: Sentiment Analysis and Risk Management.- 5. Managing Uncertainty in NLP: Advanced Techniques and Approaches.- 6. NLP for Fraud Detection and Security in Financial Documents.- 7. Multilingual and Cross-Linguistic Challenges in NLP.- 8. NLP in Action: Case Studies from Healthcare, Finance, and Industry.- 9. Generative Large Language Models in Clinical, Legal and Financial Domains.- 10. Responsible and Ethical AI in Natural Language Processing.

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Book SynopsisIntroduction.- Generative AI.- Narratological Background.- Time and Events.- Characters and Plans.- Plot.- Stories with Generative AI.- Summary and Future Directions.

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Book Synopsis._Advances in Knowledge-Enhanced Retrieval Models.._Reconstructing Context: Evaluating Advanced Chunking Strategies for Retrieval-Augmented Generation.._Going Beyond Encoders: Leveraging Decoder Architectures for Learned Sparse Retrieval.._Enhancing Representation Learning for Content-Based Information Retrieval: A Knowledge-Enhanced Geometric Approach.._Applications of Knowledge-Enhanced IR.._OntologyRAG: Better and Faster Biomedical Code Mapping withRetrieval-Augmented Generation (RAG) Leveraging OntologyKnowledge Graphs and Large Language Models.._I Know About “Up”! Enhancing Spatial Reasoning in Visual LanguageModels Through 3D Knowledge Reconstruction.._BladeLoRA: An Enhanced LoRA Method with Adaptive RankSelection and Pruning for Efficient Fine-Tuning.._Evaluating Knowledge Graph Sources for Non-Personalized FinancialAsset Recommendation: 10K Reports vs. Wikidata.

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Book SynopsisConcept-based Explainable AI.- Global Properties from Local Explanations with Concept Explanation Clusters.- From Colors to Classes: Emergence of Concepts in Vision Transformers.- V-CEM: Bridging Performance and Intervenability in Concept-based Models.- Post-Hoc Concept Disentanglement: From Correlated to Isolated Concept Representations.- Concept Extraction for Time Series with ECLAD-ts.- Human-Centered Explainability.- A Nexus of Explainability and Anthropomorphism in AI-Chatbots.- Comparative Explanations: Explanation Guided Decision Making for Human-in-the-Loop Preference Selection.- Generating Rationales Based on Human Explanations for Constrained Optimization.- Algorithmic Knowability: a unified approach to Explanations in the AI Act.- Predicting Satisfaction of Counterfactual Explanations from Human Ratings of Explanatory Qualities.- Explainability, Privacy, and Fairness in Trustworthy AI.- Too Sure for Trust. The Paradoxical Effect of Calibrated Confidence in case of Uncalibrated Trust in Hybrid Decision Making.- The Impact of Concept Explanations and Interventions on Human-machine Collaboration.-Leaking LoRA: An Evaluation of Password Leaks and Knowledge Storage in Large Language Models.- Exploring Explainability in Federated Learning: A Comparative Study on Brain Age Prediction.- The Dynamics of Trust in XAI: Assessing Perceived and Demonstrated Trust Across Interaction Modes and Risk Treatments.- XAI in Healthcare.- Systematic Benchmarking of Local and Global Explainable AI Methods for Tabular Healthcare Data.- A Combination of Integrated Gradients and SRFAMap for Explaining Neural Networks Trained with High-order Statistical Radiomic Features.- FAIR-MED: Bias Detection and Fairness Evaluation in Healthcare Focused XAI.- Weakly Supervised Pixel-Level Annotation with Visual Interpretability.- Assessing the Value of Explainable Artificial Intelligence for Magnetic Resonance Imaging.

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Book SynopsisRule-based XAI Systems & Actionable Explainable AI.- CFIRE: A General Method for Combining Local Explanations.- Which LIME should I trust? Concepts, Challenges, and Solutions.- Explainable Bayesian Optimization.- Bridging the Interpretability Gap in Process Mining: A Comprehensive Approach Combining Explainable Clustering and Generative AI.- Balancing Fairness and Interpretability in Clustering with FairParTree.- Features Importance-based XAI.- Antithetic Sampling for Top-k Shapley Identification.- Detecting Concept Drift with SHapley Additive exPlanations for Intelligent Model Retraining in Energy Generation Forecasting.- Counterfactual Shapley Values for Explaining Reinforcement Learning.- Improving the Weighting Strategy in KernelSHAP.- POMELO: Black-Box Feature Attribution with Full-Input, In-Distribution Perturbations.- Novel Post-hoc & Ante-hoc XAI Approaches.- Explain to Gain: Introspective Reinforcement Learning for Enhanced Performance.- Extending Decision Predicate Graphs for Comprehensive Explanation of Isolation Forest.- Mathematical Foundation of Interpretable Equivariant Surrogate Models.- Interpretable Link Prediction via Neural-Symbolic Reasoning.- CausalAIME: Leveraging Peter-Clark Algorithms and Inverse Modeling for Unified Global Feature Explanation in Healthcare.- XAI for Scientific Discovery.- Interpreting the Structure of Multi-object Representations in Vision Encoders.- Leveraging Influence Functions for Resampling in PINNs.- Safe and Efficient Social Navigation through Explainable Safety Regions Based on Topological Features.- A Biologically Inspired Filter Significance Assessment Method for Model Explanation.

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Book SynopsisApplications of XAI.- Global Explanations of Expected Goal Models in Football.- Comprehensive Explanations Using Natural Language Queries.- A Human-in-the-Loop Approach to Learning Social Norms as Defeasible Logical Constraints.- A Cautionary Tale About ''Neutrally'' Informative AI Tools Ahead of the 2025 Federal Elections in Germany.- Human-Centered XAI & Argumentation.- Evaluating Argumentation Graphs as Global Explainable Surrogate Models for Dense Neural Networks and their Comparison with Decision Trees.- Mind the XAI Gap: A Human-Centered LLM Framework for Democratizing Explainable AI.- Explanations for Medical Diagnosis Predictions Based on Argumentation Schemes.- Spectral Occlusion - Attribution Beyond Spatial Relevance Heatmaps.- Non-experts' Trust in XAI is Unreasonably High.- Explainable and Interactive Hybrid Decision Making.- Exploring Annotator Disagreement in Sexism Detection: Insights from Explainable AI.- Can You Regulate Your Emotions? An Empirical Investigation of the Influence of AI Explanations and Emotion Regulation on Human Decision-Making Factors.- When Bias Backfires: The Modulatory Role of Counterfactual Explanations on the Adoption of Algorithmic Bias in XAI-Supported Human Decision-Making.- Understanding Disagreement Between Humans and Machines in XAI: Robustness, Fidelity, and Region-Based Explanations in Automatic Neonatal Pain Assessment.- On Combining Embeddings, Ontology and LLM to Retrieve Semantically Similar Quranic Verses and Generate their Explanations.- Uncertainty in Explainable AI.- Improving Counterfactual Truthfulness for Molecular Property Prediction through Uncertainty Quantification.- Fast Calibrated Explanations: Efficient and Uncertainty-Aware Explanations for Machine Learning Models.- Explaining Low Perception Model Competency with High-Competency Counterfactuals.- Uncertainty Propagation in XAI: A Comparison of Analytical and Empirical Estimators.

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Book SynopsisFür Leser, die bereits die Grundlagen der Wissensverarbeitung und Computernetzwerke beherrschen, gibt das Buch einen Überblick über innovative Verfahren, die die automatisierte Suche, Recherche, Klassifikation und Verwaltung von Texten im Kontext dezentraler Systeme und vor allem im WWW erlauben. Besondere Aufmerksamkeit wird dabei auf eine personalisierte Verarbeitung gerichtet, die auch zeitliche Aspekte, wie z. B. das digitale Vergessen, einbeziehen. An vielen Stellen werden auf interessante und neuartige Art und Weise Analogien aus anderen Wissensgebieten, so z. B. zur Verarbeitung von Informationen und zum Lernen im menschlichen Gehirn sowie der Natur schlechthin genutzt.Table of ContentsWissensverarbeitung im menschlichen Gehirn - Lernen - Netzwerke für die Textanalyse - Digitale Updates und digitales Vergessen - Exploration von Netzwerkstrukturen - Konzepte des Text Minings in dezentralen Systemen - Informationsmanagement im Web

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Book SynopsisThis book discusses various aspects of text data mining. Unlike other books that focus on machine learning or databases, it approaches text data mining from a natural language processing (NLP) perspective. The book offers a detailed introduction to the fundamental theories and methods of text data mining, ranging from pre-processing (for both Chinese and English texts), text representation and feature selection, to text classification and text clustering. It also presents the predominant applications of text data mining, for example, topic modeling, sentiment analysis and opinion mining, topic detection and tracking, information extraction, and automatic text summarization. Bringing all the related concepts and algorithms together, it offers a comprehensive, authoritative and coherent overview. Written by three leading experts, it is valuable both as a textbook and as a reference resource for students, researchers and practitioners interested in text data mining. It can also be used for classes on text data mining or NLP.Table of ContentsChapter 1. Introduction.- Chapter 2. Data Annotation and Preprocessing.- Chapter 3. Text Representation.- Chapter 4. Text Representation with Pretraining and Fine-tuning.- Chapter 5. Text classification.- Chapter 6. Text Clustering.- Chapter 7. Topic Model.- Chapter 8. Sentiment Analysis and Opinion Mining.- Chapter 9. Topic Detection and Tracking.- Chapter 10. Information Extraction.- Chapter 11. Automatic Text Summarization.

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Book SynopsisThis book gathers selected papers presented at the International Conference on Sentimental Analysis and Deep Learning (ICSADL 2021), jointly organized by Tribhuvan University, Nepal; Prince of Songkla University, Thailand; and Ejesra during June, 18–19, 2021. The volume discusses state-of-the-art research works on incorporating artificial intelligence models like deep learning techniques for intelligent sentiment analysis applications. Emotions and sentiments are emerging as the most important human factors to understand the prominent user-generated semantics and perceptions from the humongous volume of user-generated data. In this scenario, sentiment analysis emerges as a significant breakthrough technology, which can automatically analyze the human emotions in the data-driven applications. Sentiment analysis gains the ability to sense the existing voluminous unstructured data and delivers a real-time analysis to efficiently automate the business processes. Meanwhile, deep learning emerges as the revolutionary paradigm with its extensive data-driven representation learning architectures. This book discusses all theoretical aspects of sentimental analysis, deep learning and related topics.Table of ContentsAnalysis of Healthcare Industry Using Machine Learning Approach: A Case Study in Bengaluru Region.- Dynamic Document Localization for Ecient Mining.- SentiSeries: A Trilogy of Customer Reviews, Sentiment Analysis and Time Series.- Video Summarization using Fully Convolutional Residual Dense Network.- An Efficient Deep Learning Approach for Detecting Pneumonia Using the Convolutional Neural Network.- QMCDS: Quantum Memory for Cloud Data Storage.- A Study towards Bangla Fake News Detection using Machine Learning and Deep Learning.- A Deep Learning Approach to Analyze the Propagation of Pandemic in America.- Graph Convolution Based Joint Learning of Rumour with Content, User Credibility, Propagation Context and Cognitive as well as Emotion Signals.- Deep Learning based Real Time Object Classification and Recognition using Supervised Learning Approach.

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Book SynopsisPart I Concepts and Technology.- Chapter 1 Introduction to Natural Language Processing.- Chapter 2 N-gram Language Model.- Chapter 3 Part-of-Speech Tagging.- Chapter 4 Syntax and Parsing.- Chapter 5 Meaning Representation.- Chapter 6 Semantic Analysis.- Chapter 7 Pragmatic Analysis and Discourse.- Chapter 8 Transfer Learning and Transformer Technology.- Chapter 9 Major Natural Language Processing Applications.- Part II Natural Language Processing Workshops with Python Implementation in 14 Hours.- Chapter 10 Workshop#1 Basics of Natural Language Toolkit (Hour 1-2).- Chapter 11 Workshop#2 N-grams Modeling with Natural Language Toolkit (Hour 3-4).- Chapter 12 Workshop#3 Part-of-Speech Tagging using Natural Language Toolkit (Hour 5-6).- Chapter 13 Workshop#4 Semantic Analysis and Word Vectors using spaCy (Hour 7-8).- Chapter 14 Workshop#5 Sentiment Analysis and Text Classification (Hour 9-10).- Chapter 15 Workshop#6 Transformers with spaCy and TensorFlow (Hour11-12).- Chapter 16. Workshop#7 Building Chatbot with TensorFlow and Transformer Technology (Hour 13-14).

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Book SynopsisText-to-speech (TTS) aims to synthesize intelligible and natural speech based on the given text. It is a hot topic in language, speech, and machine learning research and has broad applications in industry. This book introduces neural network-based TTS in the era of deep learning, aiming to provide a good understanding of neural TTS, current research and applications, and the future research trend. This book first introduces the history of TTS technologies and overviews neural TTS, and provides preliminary knowledge on language and speech processing, neural networks and deep learning, and deep generative models. It then introduces neural TTS from the perspective of key components (text analyses, acoustic models, vocoders, and end-to-end models) and advanced topics (expressive and controllable, robust, model-efficient, and data-efficient TTS). It also points some future research directions and collects some resources related to TTS. This book is the first to introduce neural TTS in a comprehensive and easy-to-understand way and can serve both academic researchers and industry practitioners working on TTS.Table of Contents

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Book SynopsisThis collection surveys the state of the art of computer-assisted literary translation (CALT), making the case for its potential to enhance literary translation research and practice.The volume brings together early career and established scholars from around the world in countering prevailing notions around the challenges of effectively implementing contemporary CALT applications in literary translation practice which has traditionally followed the model of a single translator focused on a single work. The book begins by addressing key questions on the definition of literary translation, examining its sociological dimensions and individual translator perspective. Chapters explore the affordances of technological advancements and availability of new tools in such areas as post-edited machine translation (PEMT) in expanding the boundaries of what we think of when we think of literary translation, looking to examples from developments in co-translation, collaborative translation, crowd-sourced translation and fan translation. As the first book of its kind dedicated to the contribution CALT in its various forms can add to existing and future scholarship, this volume will be of interest to students and scholars in Translation Studies, especially those working in literary translation, machine translation and translation technologies.Table of ContentsIntroduction ANDREW ROTHWELL, ANDY WAY AND ROY YOUDALEPart 1: The Automated and Post-Edited Machine Translation of Literature1 Literary-Adapted Machine Translation in a Well-Resourced Language Pair: Explorations with More Data and Wider ContextsANTONIO TORAL, ANDREAS VAN CRANENBURGH, AND TIA NUTTERS2 ‘I Am a Bit Surprised’: Literary Translation and Post-Editing Processes CompareWALTRAUD KOLB3 Mark My Keywords: A Translator-Specific Exploration of Style in Literary Machine TranslationMARION WINTERS AND DOROTHY KENNYPart 2: Machine Translation Applications in Literary Translation4 MT and CAT: Challenges, Irrelevancies or Opportunities for Literary Translation?JAMES LUKE HADLEY5 Retranslating Proust Using CAT, MT and Other ToolsANDREW ROTHWELL6 Author-Tailored Neural Machine Translation Systems for Literary WorksANTONI OLIVER7 Machine Translation of Chinese Fantasy (Xianxia) Novels: An Investigation Into the Leading Websites Translating Chinese Internet Literature Into EnglishSHUYIN ZHANG8 Up and About, or Betwixt and Between?: The Poetry of a Translation MachineTIM VAN DE CRUYS9 Metaphor in Literary Machine Translation: Style, Creativity and LiterarinessALETTA G. DORSTPart 3: Corpus Linguistics, Text-Visualisation and Literary Translation10 KonText in Trilingual Studies—Supporting Phraseology Translation Based on the EPB CorpusANGELIKA PELJAK-ŁAPIŃSKA11 Voyant Tools’ Little Outing: How a Text Reading and Analysis Environment Can Help Literary TranslatorsLISA HORENBERG12 (Re)creating Equivalence of Stylistic Effect: A Corpus-Aided MethodologyTEREZA ŠPLÍCHALOVÁPart 4: Applying Specialised Electronic Tools to Literary Translation13 The ExperimentAVRAHAM J. ROOS14 Augmenting and Informing the Translation Process through Workflow-Enabled CALT ToolsSASHA MILE RUDAN, EUGENIA KELBERT, LAZAR KOVACEVIC, MATTHEW REYNOLDS, AND SINISHA RUDAN

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Book SynopsisFrom tech giants to plucky startups, the world is full of companies boasting that they are on their way to replacing human interpreters, but are they right? Interpreters vs Machines offers a solid introduction to recent theory and research on human and machine interpreting, and then invites the reader to explore the future of interpreting. With a foreword by Dr Henry Liu, the 13th International Federation of Translators (FIT) President, and written by consultant interpreter and researcher Jonathan Downie, this book offers a unique combination of research and practical insight into the field of interpreting.Written in an innovative, accessible style with humorous touches and real-life case studies, this book is structured around the metaphor of playing and winning a computer game. It takes interpreters of all experience levels on a journey to better understand their own work, learn how computers attempt to interpret and explore possible futures for human interpreters. <Trade ReviewJonathan Downie continues his mission to bring interpreting research to the people. Outspokenly, he tackles fundamental questions for interpreters in the 21st Century. Firmly grounded in Interpreting Studies, Downie interlaces research with anecdotes well-founded in any interpreter’s daily life. It is an equally trailblazing and sulphurous book on the aspirations of machine interpreting, and the fatal mistake of not making a difference. The book is a welcome addition both to the debate on the future of interpreting and to my students’ literature list. Elisabet Tiselius, Stockholm University, SwedenA deep exploration of the limits of language, technology and the enabling power of human mediation in promoting understanding. This book puts interpreters back in the driver's seat, where they belong.Ewandro Magalhaes, Technology Advocate and Former Chief Interpreter in the UN System, USATable of ContentsIntroductionLevel One – The fundamentalsChapter 1: What is interpreting?Chapter 2: How humans interpretChapter 3: How computers "interpret"Level Two – How machines gained the upper handChapter 4: How we wrecked our own PRChapter 5: Speech translation's marvellous (but misleading) marketing Level Three – Choose your interpreting futureChapter 6: Human interpreting as a stopgapChapter 7: Hanging on with legal help Chapter 8: Mastering niches Chapter 9: Making interpreting matter againLevel Four – Interpreting that beats the botsChapter 10: Beating the bots Stage One: taking back interpreting PRChapter 11: Marketing interpreting that mattersChapter 12: Deliver more than wordsChapter 13: Coaching and supervisionLevel Five – One last thoughtChapter 14: It's time to call a truceBibliographyIndex

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Book SynopsisHannah Silva's My Child, the Algorithm, is one of the best books I read this year. Merging the cozy familiarity of child-rearing with the mysterious tension of AI {...}, she has created a new genre of personal narrative, and a story whose grief, hope and curiosity takes on poetic, spiritual dimensions, even when exploring the most common chambers of the human heart. —Michelle Tea, author, Knocking Myself UpMy Child, the Algorithm tells a story of finding joy after betrayal. Like a male seahorse, Hannah Silva carried a baby made from her partner's egg. But when she gave birth, her partner left, and Hannah found herself navigating life alone with her child.Hannah started playing with a precursor to ChatGPT—wondering what AI could tell us about love. To her surprise, she was moved by the results. The algorithm prompted Hannah to share her explorations of dating, sex, friendship, and life as a queer parent in London. With the help and disruption of two unreliable narrators, a toddler and an algorithm, Hannah deconstructs her story, unraveling everything she has been taught to want, and finds alternative ways of thinking, loving, and parenting today.

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