Introduction to Human Language Technology

• Teachers
• Weekly hours
• Competences
• Objectives
• Contents
• Activities
• Teaching methodology
• Evaluation methodology
• Bibliography
• Web links
• Previous capacities

Teachers

Person in charge

• Jordi Turmo Borrás ( )

Others

• Gerard Escudero Bakx ( )
• Salvador Medina Herrera ( )

Weekly hours

Competences

Generic Technical Competences

Generic

• CG1 - Capability to plan, design and implement products, processes, services and facilities in all areas of Artificial Intelligence.
• CG3 - Capacity for modeling, calculation, simulation, development and implementation in technology and company engineering centers, particularly in research, development and innovation in all areas related to Artificial Intelligence.

Technical Competences of each Specialization

Academic

• CEA5 - Capability to understand the basic operation principles of Natural Language Processing main techniques, and to know how to use in the environment of an intelligent system or service.

Professional

• CEP4 - Capability to design, write and report about computer science projects in the specific area of ??Artificial Intelligence.
• CEP6 - Capability to assimilate and integrate the changing economic, social and technological environment to the objectives and procedures of informatic work in intelligent systems.
• CEP7 - Capability to respect the legal rules and deontology in professional practice.

Transversal Competences

Teamwork

• CT3 - Ability to work as a member of an interdisciplinary team, as a normal member or performing direction tasks, in order to develop projects with pragmatism and sense of responsibility, making commitments taking into account the available resources.

Information literacy

• CT4 - Capacity for managing the acquisition, the structuring, analysis and visualization of data and information in the field of specialisation, and for critically assessing the results of this management.

Reasoning

• CT6 - Capability to evaluate and analyze on a reasoned and critical way about situations, projects, proposals, reports and scientific-technical surveys. Capability to argue the reasons that explain or justify such situations, proposals, etc..

Objectives

1. Understand the fundamental concepts of Natural Language Processing, most well-known techniques and theories as well as most relevant existing resources.
   Related competences: CEA5, CG1, CG3, CEP6, CT4, CT6,
2. Understand most relevant applications of NLP and the theories, tecniques and resources they use.
   Related competences: CEA5, CG1, CG3, CEP6, CT4, CT6,
3. Design and development of programs to solve specific problems in the NLP context, involving the selection of most appropiate techniques and resources as well as the use of existing resources. There would be one larger programs to be developed in groups of two students.
   Related competences: CEA5, CG1, CG3, CEP4, CEP6, CEP7, CT3, CT4, CT6,
4. Reason (ocassionally, in group) about several problems in the NLP context that imply considering different techniques and resources.
   Related competences: CEA5, CG1, CG3, CEP7, CT3, CT4, CT6,

Contents

1. Document Structure and Language
   Text selection, Tokenization, Sentence splitting, Language Identifiers
2. Words
   Morphology, Finite States Automata, Finite States Transducers.
   PoS tagging, Hidden Markov Models.
   Lexical semantics, Semantic resources.
   Word Sense Diambiguation.
3. Word sequences
   Recognition and classification of word sequences with meaning.
   BIO discriminative models. Conditional Random Fields (CRF).
   Named Entity Recognition and Classification (NERC).
   Noun-phrase Chunking.
4. Sentences
   Syntactic grammars, typology. Context free grammars. Probabilistic context free grammars. Chomsky normal form grammars.
   
   Syntactic parsers, properties and strategies. CKY and probabilistic CKY parsers.
5. Sentence sequences
   Coreference resolution. Mention detection. Types of techniques for the generation of coreferents chains. Mention-pair model. Entity-mention model. Rankers model.

Activities

Activity Evaluation act

Teaching methodology

Evaluation methodology

Bibliography

Basic:

• Speech and language processing: an introduction to natural language processing, computational linguistics, and speech recognition - Jurafsky, D.; Martin, J.H, Prentice-Hall, Inc., 2008. ISBN: 9332518416
  https://discovery.upc.edu/discovery/fulldisplay?docid=alma991003460299706711&context=L&vid=34CSUC_UPC:VU1&lang=ca
• Handbook of natural language processing - Dale, R.; Moisl, H.; Somers, H, Marcel Dekker, 2000. ISBN: 0824790006
  https://discovery.upc.edu/discovery/fulldisplay?docid=alma991002071619706711&context=L&vid=34CSUC_UPC:VU1&lang=ca
• Foundations of statistical natural language processing - Manning, C.D.; Schütze, H, MIT Press, 1999. ISBN: 0262133601
  https://discovery.upc.edu/discovery/fulldisplay?docid=alma991001994779706711&context=L&vid=34CSUC_UPC:VU1&lang=ca
• The Oxford handbook of computational linguistics - Mitkov, R. (ed.), Oxford University Press, 2003. ISBN: 0198238827
  https://discovery.upc.edu/discovery/fulldisplay?docid=alma991002689009706711&context=L&vid=34CSUC_UPC:VU1&lang=ca

Web links

• Time table of the course depending on the holidays http://www.cs.upc.edu/~turmo/IHLT.html

Previous capacities