Weekly questionnaire

1. Feb 12-14. First contact with the browser and on-line materials.
2. Feb 17-21. Language technologies and the Information Society
3. Feb 24-28. Information overload and methods to improve data-management.
4. Mar 3-7. Multilinguality is a barrier to communication. We will review translation technology and its potential to help overcome that problem.
5. Mar 10-14. Machine Translation (MT) is a possible way of overcoming language barriers. However output quality is often a problem for MT systems.
6. Mar 17-21. We are going to learn more about MT: history, methods, approaches, best known systems, etc.
7. Mar 24-28. Linguistic Diversity on the Internet: Assessment of the Contribution of Machine Translation. Multilingual resources
8. Apr 31-4. Corpus Linguistics.
9. Apr 7-11. Submission of Report A. See the list of submitted reports (Apr. 16).
10. Apr 14. Evaluation of Machie Translation systems
11. Apr 28. Evaluation of Machie Translation systems
12. May 5-9.Evaluation of Machie Translation systems
13. May 12-16. Submission of Report B.
    Evaluation of search and content retrieval engines on internet (1)
14. May 19-23. Evaluation of search and content retrieval engines on internet (and 2)
15. May 26-30. Submission of Report C. Review.

1. Feb 12-14.
   Objective of the week:
   • First contact with the browser and on-line materials.
   • Course objectives.
   • Evaluation.
   • Deadlines.
   • Assignments
     In relation to good report writing, it is important to acknowledge:
     • who is the publisher/writer of a document,
     • what is its function or role,
     • the date
   • Remember the recomendations of the Evaluation section.
2. Feb 17-21
   Objective of the week: Language technologies and the Information Society
   • Questions for the week:
     1. What is the "Information Society"?
     2. What is the role of HLTCentral.org?
     3. Why language technologies are so important for the Information Society?
   • References on-line:
     • Information Society (Document from I*M Europe)
     • Living and Working Together in the Information Society (Discussion Document from HLTCentral).
     • Information Policy for an Information Society (Paper by Mairéad Browne - caché).
     • Human Language Technologies and the information society (Presentation of Action Line, by the EC: caché)
     • What is Language Technology, by Hans Uszkoreit (caché in PDF)
     • What is Computational Linguistics?, by Hans Uszkoreit (caché)
     • Language Engineering (Brouchure by HLTCentral: caché)
     • Language Technology in Agribusiness: http://www.multilingual.com/
     • The complexity of natural language.
   • Other on Internet
     • EUROPA y la "Sociedad de la Información": http://www.bib.uc3m.es/~mendez
3. Feb 24
   Objective of the week: Information overload and methods to improve data-management.
   • "Having too much information can be as dangerous as having too little" (David Lewis)
     These are the questions we should answer this week:
     1. Why "knowledge" is of more value than "information"?
     2. Does the possesion of big quantities of data imply that we are well informed?
     3. How many words of technical information are recorded every day?
     4. What is the most convenient way of representing information? Why?
     5. How can computer science and language technologies help manage information?
     6. Why language can sometimes be seen as a barrier to communication? How can this change?
   • References on-line:
     • FAQs at the University of Toronto (caché)
     • Information fatigue syndrome
     • Information technologies for the new society
4. Mar 3-7.
   Objective of the week: Language technology and engineering
   • Questionaire:
     1. In what ways does Language Engineering improves the use of language?
     2. Language Tecnology, Language Engineering and Computational Linguistics. Similarities and differences.
     3. Which are the main techniques used in Language Engineering?
     4. Which language resources are essential components of Language Engineering?
     5. Check for the following terms:
        • natural language processing
        • translator's workbench
        • shallow parser
        • formalism
        • speech recognition
        • text alignment
        • authoring tools
        • controlled language
        • domain
   • References on-line:
     • What is Language Technology, by Hans Uszkoreit (caché in PDF)
     • What is Computational Linguistics?, by Hans Uszkoreit (caché)
     • Language Engineering (Brouchure by HLTCentral: caché)
5. Mar 10-14.
   Objective of the week: Multilinguality
   • Multilinguality is a barrier to communication. We will review translation technology and its potential to help overcome that problem. These are the questions of the week:
     1. In the translation curricula, which factors make technology more indispensable?
     2. Do professional interpreters and literary translators need translation technology? Which are the tools they need for their job?
     3. In what ways is documentation becoming electronic? How does this affect the industry?
     4. What is the focus of the localization industry? Do you believe there might be a job for you in that industry sector?
     5. Define internationalization, globalization and localization. How do they affect the design of software products?
     6. Are translation and localization the same thing? Explain the differences.
     7. What is a translation workstation? Compare it with a standard localization tool.
     8. Machine translation vs. human translation. Do you agree that translation excellence goes beyond technology? Why?
     9. Which profiles should any person with a University degree in Translation be qualified for?
   • Reference on-line
     • Is it worth learning translation technology
     • 6th EAMT Workshop: Teaching Machine Translation
     • Bibliography selected by Harold Somers
6. Mar 17-21
   Objective of the week: Machine Translation
   • Machine Translation (MT) is a possible way of overcoming language barriers. However quality is often a problem. Let us see why.
     1. Why is translation such a difficult task?
     2. Which are the main problems of MT?
     3. Which parts of Linguistics are more relevant for MT?
     4. How many different types of ambiguity are there?
     5. Illustrate your discussion with:
        • Two examples of lexical ambiguity
        • One example of structural ambiguity
        • Three lexical and structural mismatches
        • Three collocations
        • Two idiomatic expressions
   • References on-line
     • Why computers do not translate better, by John Hutchins
     • Translation problems, by D J Arnold
     • More examples of collocations, idioms and other lexical mismatches
     • The complexity of natural language (ppt)
7. Mar 24-28
   Objective of the week: Machine Translation II
   • We now know that MT is difficult, despite the fact of being the first and more widespread computer-based application related to natural language. This week we are going to learn about MT: history, methods, approaches, best known systems, etc.
     1. Which are the most usual interpretations of the term "machine translation" (MT)?
     2. What do FAHQT and ALPAC mean in the evolution of MT?
     3. List some of the major methods, techniques and approaches
     4. Where was MT ten years ago?
     5. New directions and foreseeable breakthroughs of MT in the sort term.
   • References
     • Multilingual information managment: Machine Translation, by Bente Maegaard
     • Reflections on the history and present state of machine translation, John Hutchins
     • Introducción a la traducción automática
8. Apr 31-4
   Objectives of the week: Assessment of the Contribution of Machine Translation to Linguistic Diversity on the Internet
   • Can MT contribute to solve the problem of language diversity for international communication?
     1. Which are Internet's essential features?
     2. What is the role of minority languages on the Internet (Catalan, Basque...)?
     3. In what ways can Machine Translation be applied on the Internet?
   • References on-line:
     • Linguistic Diversity on the Internet: Assessment of the Contribution of Machine Translation (caché)
     • Multilingual resources
9. Apr 7-11. Friday 11th Submission deadline for Report A. See the list of submitted reports (Apr. 16).
   
10. Apr 14. Evaluation of Machie Translation systems
    • SYSTRAN: http://www.systransoft.com (from Gachot)
    • GOOGLE: http://translate.google.com
    • ProMT: http://www.translate.ru/ (antes Stylus)
    • FreeTRANSLATION: http://ets.freetranslation.com:5081/ (licensed by Transparent Language TranscendRT)
    • Traductor de EL Mundo: http://www.el-mundo.es/traductor/ (licensed by Softissimo)
    • Alphaworks.ibm/
11. Apr 28. Evaluation of Machie Translation systems. Try your own examples (see also my list).
12. May 5-9. Evaluation of Machie Translation systems
13. May 12-16. Friday 16th Submission deadline for Report B
14. May 29-23. Evaluation of search and content retrieval engines on internet.
    How much linguistic information do search engines use?
    Reference material
    • Browsing the Web (table of contents)
    • Internet Search Engines (caché)
    • Documentación informativa en la Web y cómo buscarla, por Eva Méndez
    • Sistemas de búsqueda y recuperación en Internet (caché)
    • Translingual Search Engine
    • Evaluation of Internet Searching and Search Engines
    • Cybermetrics. International Journal of Scientometrics, Informetrics and Bibliometrics
    • Search Engine Watch, by Danny Sullivan
    Select one of the following exersices:
    1. Imagine you are translating a text from English with the following terms:
       • European Monitoring Centre for Drugs and Drug Addiction
       • European Council of Justice and Home Affairs
       • European Foundation for the Improvement of Living and Working Conditions
       • Employment, Social Policy, Health and Consumer Affairs
       • Public Register of the Council of the European Union
       Search the web to find the proper Spanish equivalent and, when you find it, explain your procedure. You may use Google and Eurodicautom as main Internet services.
    2. Imagine you want to enrole in a Human Language Technology postgraduate course. How would you select one from the information available on Internet?
15. May 26-30. Friday 30th Submission deadline for Report C