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Table Card RUSMARC
Title: Studies in corpus linguistics ;. Parallel corpora for contrastive and translation studies: new resources and applications. — v. 90.
Other creators: Doval Reixa Irene; Sánchez Nieto María Teresa
Collection: Электронные книги зарубежных издательств; Общая коллекция
Subjects: Corpora (Linguistics); Contrastive linguistics.; Translating and interpreting — Study and teaching.; LANGUAGE ARTS & DISCIPLINES / Linguistics / Historical & Comparative; EBSCO eBooks
Document type: Other
File type: PDF
Language: English
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Table of Contents

  • Parallel Corpora for Contrastive and Translation Studies
  • Editorial page
  • Title page
  • Copyright page
  • Table of contents
  • Acknowledgments
  • Parallel corpora in focus
    • 1. Three decades of parallel corpora in linguistic studies
    • 2. Processing and using today’s parallel corpora: Some trends
      • 2.1 The process perspective
      • 2.2 The product perspective
    • 3. Structure of this volume and presentation of contributions
    • References
  • Parallel corpora. Background and processing
    • Comparable parallel corpora
      • 1. Introduction
      • 2. Comparable parallel corpora
      • 3. Universals of translation
      • 4. What makes parallel corpora comparable, and does size matter?
      • 5. The sampling challenge of the NSPC
      • 6. Testing of the gravitational pull hypothesis
      • 7. Conclusions
      • Acknowledgment
      • References
    • Living with parallel corpora
      • 1. Parallel corpora and research on translation: Some landmarks
      • 2. Parallel corpora and the study of translation: Potentials and limitations
        • 2.1 Parallel vs. comparable corpora?
        • 2.2 Advantages and uses of parallel corpora
      • 3. Case study 1: Analysing the Translation of Meal Names with a Parallel Corpus as the Main Source of Data
      • 4. Case study 2: Analysing the construction –‘ment’ adverb + adjective in Catalan translations with a parallel corpus as a supplementary source of data
      • 5. Concluding remarks
      • Acknowledgement
      • References
    • Working with parallel corpora
      • 1. Introduction
      • 2. Concepts
      • 3. Resources
      • 4. Uses of parallel corpora
      • 5. Needs analysis
      • 6. Parallel corpora: Building or using
      • 7. Applications
      • 8. Useful strategies
      • 9. Conclusions
      • Acknowledgment
      • References
    • Innovations in parallel corpus alignment and retrieval
      • 1. Introduction
      • 2. Corpus annotations
        • 2.1 General corpus annotation
        • 2.2 Exploiting parallel corpora for annotation
        • 2.3 Language-specific corpus annotation
      • 3. Aligning parallel corpora
      • 4. Retrieval from parallel corpora
      • 5. Conclusion
      • Acknowledgments
      • References
  • Parallel corpora. Creation, annotation and access
    • InterCorp
      • 1. Introduction
      • 2. Description of the corpus
        • 2.1 The Spanish part of the corpus
      • 3. Using the corpus
      • 4. Specific tools: Translation equivalents database
      • 5. Exploiting ‘InterCorp’
      • 6. Conclusion
      • Acknowledgment
      • References
    • Corpus PaGeS
      • 1. Introduction
      • 2. Components and content
      • 3. Text preprocessing, textual mark-up and metadata
      • 4. Alignment
      • 5. Search and display features
      • 6. Server architecture and publishing data
      • 7. Summary and outlook
      • Acknowledgement
      • References
    • Building EPTIC
      • 1. Introduction: Why another corpus of European Parliament speeches?
      • 2. What EPTIC looks like
        • 2.1 One corpus, fourteen subcorpora
        • 2.2 Practical details: Size and availability
      • 3. Building EPTIC
        • 3.1 Selecting and obtaining raw corpus materials
        • 3.2 Transcribing the oral data
        • 3.3 Adding metadata
        • 3.4 Performing text-to-text alignment
        • 3.5 Performing text-to-video alignment
        • 3.6 POS-tagging, lemmatization and indexing
      • 4. An example: English loan words in Italian and French
      • 5. Conclusion: Teaming up
      • Acknowledgement
      • References
    • Enriching parallel corpora with multimedia and lexical semantics
      • 1. Introduction
      • 2. The CLUVI Corpus
        • 2.1 Corpus description
        • 2.2 Tagging the CLUVI Corpus
        • 2.3 Extending the CLUVI Corpus with multimedia data
      • 3. The SensoGal Corpus
      • 4. Conclusion
      • References
    • Discourse annotation in the MULTINOT corpus
      • 1. Introduction
      • 2. The MULTINOT corpus
      • 3. Annotation procedure
        • 3.1 Selecting the “training” corpus
        • 3.2 Instantiating the theory
        • 3.3 Designing annotation schemes and guidelines
        • 3.4 Performing annotation experiments
        • 3.5 Evaluating the annotations
        • 3.6 Large-scale annotation of the whole corpus
      • 4. Annotating thematization in English and Spanish
      • 5. Annotating modality in English and Spanish
      • 6. Annotating metadiscourse markers in English and Spanish
      • 7. Summary and concluding remarks
      • Acknowledgement
      • References
    • PEST
      • 1. General
      • 2. PEST corpus
      • 3. The Russian–Finnish section: Can a parallel corpus be balanced?
      • 4. Other sections of the corpus
        • 4.1 The Sweden–Finland section
        • 4.2 The Russia–Sweden section
        • 4.3 Multilateral international treaties
      • 5. Great expectations
      • Acknowledgement
      • References
    • Indexation and analysis of a parallel corpus using CQPweb
      • 1. Introduction
      • 2. The corpora
      • 3. Corpus compilation and indexation
        • 3.1 Preparation of texts
        • 3.2 Uploading the files to CQPweb
          • Step 1: Creating directories
          • Step 2: Encoding and indexing corpora in CWB
          • Step 3: Aligning the subcorpora
          • Step 4: Copying the files to CQPweb
          • Step 5: Activating the corpora on the web interface
      • 4. Corpus analysis
      • 5. Conclusion
      • Acknowledgements
      • References
    • P-ACTRES 2.0
      • 1. Introduction
      • 2. Description of the corpus
        • 2.1 Composition
        • 2.2 Building of the corpus: Computational procedure
          • 2.2.1 Technologies
          • 2.2.2 Workflow
          • 2.2.3 User interface
        • 2.3 P-ACTRES 1.0 VS P-ACTRES 2.0
      • 3. Usefulness and usability in cross-linguistic research
      • 4. Conclusions
      • Acknowledgements
      • References
    • An overview of Basque corpora and the extraction of certain multi-word expressions from a translational corpus
      • 1. Introduction
      • 2. An overview of Basque corpora
      • 3. Design, compilation and annotation of the Aleuska corpus
      • 4. Extraction of MWEs
      • 5. Conclusion
      • References
  • Parallel corpora. Tools and applications
    • Strategies for building high quality bilingual lexicons from comparable corpora
      • 1. Introduction
      • 2. Pruning lexicons built through transitiviy
        • 2.1 Basic assumptions
        • 2.2 The pruning method
      • 3. Pruning bilingual cognates
        • 3.1 Basic assumptions
        • 3.2 The pruning method
      • 4. Experiments
        • 4.1 Derivation by transitivity
        • 4.2 Comparable corpora
          • 4.2.1 Validation
          • 4.2.2 Evaluation of the dictionaries generated by transitivity
        • 4.3 Bilingual cognates
          • 4.3.1 Existing resources
          • 4.3.2 Size of the extracted lexicons
          • 4.3.3 Evaluation of the cognate-based extraction
          • 4.3.4 Error analysis
      • 5. Conclusions and future work
      • Acknowledgements
      • References
    • Discovering bilingual collocations in parallel corpora
      • 1. Introduction
      • 2. Previous research on bilingual collocation extraction
      • 3. The proposed strategy
        • 3.1 Extracting monolingual collocation candidates
        • 3.2 Bilingual distributional semantics model
        • 3.3 Bilingual alignment of monolingual collocations
      • 4. Evaluation
        • 4.1 Data
        • 4.2 Monolingual extraction and bilingual alignment
        • 4.3 Results
        • 4.4 Error analysis
      • 5. Conclusions
      • Acknowledgements
      • References
    • Normalization of shorthand forms in French text messages using word embedding and machine translation
      • 1. Introduction
      • 2. Previous work
      • 3. Corpus and preprocessing
        • 3.1 Corpus
        • 3.2 Preprocessing
      • 4. Methodologies, tools and experiments
        • 4.1 Methodologies
        • 4.2 Tools and experiments
          • ‘multivec’
          • ‘moses’
      • 5. Results analysis
      • 6. Conclusion
      • 7. Future work
      • Acknowledgment
      • References
  • Subject index

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