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Seminars in artificial Intelligence and Robotics: Natural Language Processing

EXAMS

The exam for students who decided to present a paper is scheduled on FRIDAY 13th from 12:00 to 16:00, Aula 7. Students are kindly requested to send a mail with their name and selected paper. The following have been alreadi selected (30/3):

• Towards Conversational Human-Computer Interaction
• Spatial role labeling: Towards extraction of spatial relations from natural language
• Learning to Follow Navigational Directions

PROJECT NOTES

In this document class project you find a description of the project and who must do what.

The project proposed by Prof. Basili (with audio) is described in http://ai-nlp.info.uniroma2.it/basili/buffer/ProjectNLP2012_v1.0_conAudio.pdf

Timing is:

By may 2, corpus annotated.

End of May please contact me and report.

July, Friday 6 (tentative) Projects discussion

Course Syllabus

• Introduction to NLP
• Machine learning methods for NLP (Prof. R. Basili)
• Information Retrieval and Extraction
• Question Answering
• Dialogue systems

Course Material

• Introduction: Definition of NLP tasks, architecture and methods. An example: Hidden Markov Models and Viterbi algorithm for Part of Speech Tagging Lesson 1.
• Information Retrieval and Extraction Lesson 2.
• Question Answering Lesson 3.
• Discourse and Dialogue Lesson 4.
• Machine learning for Natural language Processing (Prof. Roberto Basili) Lesson 5.1,Lesson 5.2 .

Papers

Students can select one of the following papers for the final exam. Each student must present the content of the paper in a 15-20m presentation (ppt). Each student should also review another student's presentation and prepare questions during the presentation. Students are also invited to present a paper of their choice, but this must be agreed with the instructor via email.

• (Initial set of papers, to be enriched)

• Towards Conversational Human-Computer Interaction. James F. Allen, Donna K. Byron, Myroslava Dzikovska, George Ferguson, Lucian Galescu, Amanda Stent (AI magazine)
• Conversational robots: building blocks for grounding word meaning. Deb Roy, Kai-Yuh Hsiao and Nikolaos Mavridis
• Comparing objective and subjective measures of usability in a human-robot dialogue system. Mary Ellen Foster, Manuel Giuliani, Alois Knoll
• Spontaneous speech understanding for robust multi-modal human-robot communication. Sonja Hüwel, Britta Wrede
• Conversational gaze mechanisms for humanlike robots. Bilge Mutlu, Takayuki Kanda, Jodi Forlizzi, Jessica Hodgins, Hiroshi Ishiguro
• Spatial role labeling: Towards extraction of spatial relations from natural language. Parisa Kordjamshidi, Martijn Van Otterlo, Marie-Francine Moens
• Understanding Natural Language Commands for Robotic Navigation and Mobile Manipulation. Stefanie Tellex and Thomas Kollar and Steven Dickerson and Matthew R.Walter and Ashis Gopal Banerjee and Seth Teller and Nicholas Roy
• Learning to Follow Navigational Directions. Adam Vogel and Dan Jurafsky
• Toward Understanding Natural Language Directions. Thomas Kollar and Stefanie Tellex and Deb Roy and Nicholas Roy

Papers +projects

Project: Create a corpus of directions in a domotic environment semi-automatically pptx

NOTE: ALL students should contribute to annotate a fragment of the corpus NOTE: Students can coordinate their work joining the Google group NLP - AIRO 2012: http://groups.google.com/group/nlpairo2012?hl=it

Resources

* The Stanford parser (English, Arabic, Chinese) http://nlp.stanford.edu/software/lex-parser.shtml

* The Treetagger (POS tagger and Chunker for many languages including Estonian, Romenian, Latin, Swaili and more) http://www.ims.uni-stuttgart.de/projekte/corplex/TreeTagger/DecisionTreeTagger.html

* WordNet- http://wordnet.princeton.edu/

* FrameNet? - http://framenet.icsi.berkeley.edu/

* VerbNet? - http://verbs.colorado.edu/~mpalmer/projects/verbnet.html

* A Word Sense Disambiguation tool based on WordNet- http://lcl.uniroma1.it/ssi/

* Machine Translation: Google Translate - http://translate.google.com/#

* Multilingual electronic dictionary of football (soccer) language. It is based on FrameNet? http://www.kicktionary.de/

*Transcription of the IBL speech corpus (route directions in a University Campus) http://www.ltg.ed.ac.uk/ibl/ibl-transcription.txt NOTE: details on the IBL corpus are found on http://www.tech.plym.ac.uk/soc/staff/guidbugm/ibl/readme1.html It is a useful guide on how to build a corpus of expressions and words used by humans instructing an agent moving an artificial environment.

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