"Corpus-based contrastive and translation research are areas that keep evolving in the digital age, as the range of new corpus resources and tools expands, opening up to different approaches and application contexts. The current book contains a selection of papers which focus on corpora and translation research in the digital age, outlining some recent advances and explorations. After an introductory chapter which outlines language technologies applied to translation and interpreting with a view to identifying challenges and research opportunities, the first part of the book is devoted to current advances in the creation of new parallel corpora for under-researched areas, the development of tools to manage parallel corpora or as an alternative to parallel corpora, and new methodologies to improve existing translation memory systems. The contributions in the second part of the book address a number of cutting-edge linguistic issues in the area of contrastive discourse studies and translation analysis on the basis of comparable and parallel corpora in several languages such as English, German, Swedish, French, Italian, Spanish, Portuguese and Turkish, thus showcasing the richness of the linguistic diversity carried out in these recent investigations. Given the multiplicity of topics, methodologies and languages studied in the different chapters, the book will be of interest to a wide audience working in the fields of translation studies, contrastive linguistics and the automatic processing of language"--.

• Corpora in Translation and Contrastive Research in the Digital Age
• Editorial page
• Title page
• Copyright page
• Table of contents
• Corpus resources and tools: Looking back and going ahead
  • 1. Corpus resources
  • 2. Corpus-related tools
    • 2.1 Translation memory systems
    • 2.2 Corpus management tools
  • 3. Impact on corpus-based translation and contrastive studies
  • 4. Organization of the volume and chapter overview
  • Acknowledgements
  • References
• Part I. Corpus resources and tools
• Chapter 1. Now what?: A fresh look at language technologies and resources for translators and interpreters
  • 1. Introduction
  • 2. Current and emerging trends
    • 2.1 Automating translation and crowdsourcing
    • 2.2 Displacing traditional forms of interpreting
  • 3. Some data tools and resources
    • 3.1 Corpora
    • 3.2 CAI tools
  • 4. Translators and interpreters’ technology uptake
  • 5. Food for thought
  • Acknowledgements
  • Funding
  • References
• Chapter 2. ZHEN: A directional parallel corpus of Chinese source texts and English translations
  • 1. Introduction
  • 2. A brief overview of the Chinese-English translation scenario
  • 3. Chinese-English parallel corpora
  • 4. The ZHEN corpus
    • 4.1 Text selection
    • 4.2 Parallel text alignment
    • 4.3 Corpus compilation
  • 5. Applications of ZHEN
  • 6. Conclusion and future directions
  • References
  • Appendix
• Chapter 3. Word alignment in a parallel corpus of old English prose: From asymmetry to inter-syntactic annotation
  • 1. Introduction
  • 2. Background
  • 3. The design of an aligned parallel corpus of old English prose
  • 4. Inter-syntax and asymmetry
  • 5. The scope and components of the inter-syntax
  • 6. Conclusion and further research
  • The following abbreviations are used in this section
  • Funding
  • References
• Chapter 4. Semantic textual similarity based on deep learning: Can it improve matching and retrieval for Translation Memory tools?
  • 1. Introduction
  • 2. Methodology
    • 2.1 InferSent
    • 2.2 Universal sentence encoder
    • 2.3 Sentence BERT
  • 3. Dataset and experiments
  • 4. Evaluation and results
  • 5. Analysis of typical errors
  • 6. Conclusion
  • Acknowledgements
  • Funding
  • References
• Chapter 5. TAligner 3.0: A tool to create parallel and multilingual corpora
  • 1. Introduction
  • 2. Evolution of TAligner 3.0
    • 2.1 TRACE Corpus Tagger/Aligner 1.0©
    • 2.2 TRACEAligner 2.0
    • 2.3 TAligner 3.0
  • 3. Building and querying corpora in TAligner 3.0
    • 3.1 Building corpora
    • 3.2 Querying corpora
  • 4. Corpora created using TAligner 3.0
    • 4.1 Narrative corpora
    • 4.2 Theatre corpora
  • 5. Conclusions
  • Acknowledgements
  • Funding
  • References
• Chapter 6. Developing a corpus-informed tool for Spanish professionals writing specialised texts in English
  • 1. Introduction
  • 2. Parallel corpora: Applications in cross-linguistic research
  • 3. Comparable corpora: Applications in cross-linguistic research
  • 4. Promociona-TÉ: A comparable-corpus-informed writing tool
    • 4.1 Writing in English for specific purposes
    • 4.2 The corpus: ACTEaS_Promo
    • 4.3 Generating herbal tea promotional texts
    • 4.4 Writing assistance
    • 4.5 Tool programming and architecture
    • 4.6 Advantages of the tool
  • 5. Conclusions
  • Acknowledgements
  • Funding
  • References
• Part II. Corpus-based studies and explorations
• Chapter 7. English and Spanish discourse markers in translation: Corpus analysis and annotation
  • 1. Introduction
  • 2. Data and methodology
  • 3. Corpus analysis phase
    • 3.1 Some previous work on English DMs
    • 3.2 Translation analysis of in fact
    • 3.3 Translation analysis of actually
    • 3.4 Translation analysis of really
    • 3.5 Analysis of the back translations
    • 3.6 Lexico-semantic field construction
  • 4. Corpus annotation phase
  • 5. Summary and concluding remarks
  • References
  • Appendix. List of subcorpora within Opus2 parallel corpus
• Chapter 8. The discourse markers well and so and their equivalents in the Portuguese and Turkish subparts of the TED-MDB corpus
  • Introduction
  • Research aims and method of analysis
  • The TED-MDB corpus
  • Related work: The view from speech annotation
    • A scheme for spoken language (Crible 2017)
    • Treatment of question-response sequences in various frameworks and TED-MDB
  • Data analysis
    • The case of well and its translations to Portuguese and Turkish in TED-MDB
    • The case of so and its translations to Portuguese and Turkish in TED-MDB
    • Discourse markers in question-response pairs
  • Conclusion and future work
  • Acknowledgements
  • Funding
  • References
• Chapter 9. Variation of evidential values in discourse domains: A contrastive corpus-based study (English and Spanish)
  • 1. Introduction
  • 2. Evidentiality and multifunctionality
    • 2.1 Evidentiality
    • 2.2 Classification of evidential expressions
    • 2.3 Multifunctionality
  • 3. Methodology
    • 3.1 Hypotheses and research objectives
    • 3.2 Corpora and object of analysis: Evidential expressions
    • 3.3 Criteria for the analysis of evidential expressions
    • 3.4 Procedure of annotation
  • 4. Results and discussion
    • 4.1 Results for evidential values, experiential domains, and discourse domains and genres in English
    • 4.2 Results for evidential values, experiential domains, and discourse domains and genres in Spanish
    • 4.3 Discussion: Comparison of Results in English and Spanish
  • 5. Conclusions
  • Acknowledgements
  • Funding
  • Dictionaries
  • References
• Chapter 10. The translation for dubbing of Westerns in Spain: An exploratory corpus-based analysis
  • 1. Introduction
  • 2. Theoretical framework
  • 3. Parallel corpus selection and data compilation process
  • 4. Origin
  • 5. Corpus analysis
    • 5.1 Introduction
    • 5.2 Figures of authority
    • 5.3 Firearms
    • 5.4 Other translation strategies
    • 5.5 Censorial issues
  • 6. Conclusions
  • References
  • Databases and dictionaries
• Chapter 11. Generic analysis of mobile application reviews in English and Spanish: A contrastive corpus-based study
  • Introduction
  • Theoretical framework
    • Genre analysis
    • Appraisal theory
  • The mobile application review genre and the corpus
    • General characteristics of mobile application and game reviews
    • Comparison with reviews about other products and from other platforms
    • Corpus
  • Generic stages in mobile application reviews
    • Lexicogrammatical features of stages
    • Patterns observed in the stages
    • Most important problems in the (automatic) analysis of application and game reviews
  • Summary and concluding remarks
  • References
• Chapter 12. Exploring variation in translation with probabilistic language models
  • 1. Introduction
  • 2. Corpus data
  • 3. Methods
    • 3.1 Probabilistic language models and analysis of translation variation
    • 3.2 Comparing language models by relative entropy
  • 4. Analysis and results
    • 4.1 Translation direction: Originals vs. Translation/Interpreting
    • 4.2 Translation mode: Translation vs. Interpreting
  • 5. Summary and discussion
  • Acknowledgements
  • Funding
  • References
• Chapter 13. Binomial adverbs in Germanic and Romance Languages: A corpus-based study
  • 1. Introduction
  • 2. Related work
  • 3. Corpus preparation
  • 4. Identification of candidates
  • 5. Candidate ranking
  • 6. Expression boundaries
  • 7. Translation variants
  • 8. Conclusions
  • Acknowledgements
  • Funding
  • References
  • Appendix
• Index