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Language and Intelligence

Language and Intelligence

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Language and Intelligence

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  1. Language and Intelligence Natural Language Processing (NLP), Machine Translation (MT), Computer Assisted Language Learning (CALL), Speech Artificial Intelligence, World Wide Mind Language Intelligence Language & Intelligence Language Evolution, Semantics, 3D Worlds, Neural Networks, Speech and Multi-Modal Interfaces School of Computer Applications

  2. Language and Intelligence Staff Postgrad Students Dr D. Fitzpatrick A. Cahill, N. Gough, J. Hayes S. Harford, M. Hearne, Dr M. Humphrys M. Mc Carthy, C. O’Leary, J. Kelleher M. Tooher Dr J. Mc Kenna Prof J. Van Genabith Affiliated Researcher R. Walshe D. O’Connor M. Ward Dr A. Way

  3. Language and Intelligence • NCLT • National Centre for Language Technologies • computing.dcu.ie/nclt • World Wide Mind • w2mind.org

  4. Language Research Areas Example-Based Machine Translation (EBMT) People: Dr A. Way M. Hearne: Hybrid (Stats + rule-based) Machine Translation N. Gough: Web-Based Machine Translation Overview: We are currently investigating two approaches to MT which can broadly be described as EBMT: a) Marker-based EBMT b) DOT and LFG-DOT School of Computer Applications

  5. Language Research Areas Example Based Machine Translation Given: John went to school Jean est allé à l’école. The butcher’s is next to the baker’s La boucherie est à côté de la boulangerie. Isolate useful fragments: John went to Jean est allé à the baker’s la boulangerie We can now translate: John went to the baker’s as Jean est allé à la boulangerie. School of Computer Applications

  6. Language Research Areas Speaker Characterisation People: Dr J. McKenna M. Tooher: Machine Learning of Speaker Characteristic Speech Dynamics and Interactions Overview: Our research aims to separate the linguistic content of speech from that containing speaker-specific information. School of Computer Applications

  7. Language Research Areas Speaker Characterisation Machine Translation Separate Linguistic Data from Speaker Characteristics Hello New Language Bonjour School of Computer Applications

  8. Language Research Areas • CALL • use of XML technologies • specific requirements for Endangered Languages • e.g. computing.dcu.ie/~mward/nawat.html • interest from UNESCO, European Bureau of Lesser Used Languages • working with projects in Siberia and Togo/Benin • VOCALL (Vocationally oriented CALL) School of Computer Applications

  9. Intelligence World Wide Mind project People: Dr M. Humphrys, R. Walshe. C. O’Leary, D. O’Connor Overview: • This is a new idea for decentralising the work in AI by putting agent mind and worlds online as reusable servers • This work proposes that the construction of advanced artificial minds may be too difficult for any single lab • No easy system exists whereby a working mind can be made from the components of two or more labs • Our system aims to change this and accelerate the growth of AI School of Computer Applications

  10. Intelligence Society of Mind constructed from Multiple servers 1.client talks to: 1. MindM, which talks to: 1. Mind 2. MindM, which talks to: 1. Mind 3. MindAS, which talks to: 1. Mind 2. MindM, which talks to: 1. Mind 3. Mind 2. WorldW, which talks to: 1. World School of Computer Applications

  11. Language and Intelligence State Mind World Wide Mind Mind Server Mind Action Action State World (problem to solve) State Client (do some task) State Mind Action Action Uses World Wide Web and cgi-bin/perl for communication School of Computer Applications

  12. Language and Intelligence Dr D Fitzpatrick: Applications of Speech Technology and Multi-modal interfaces Force Feedback/ (Haptic) Device Information Analysis Map Purpose: to convey spatial information non-visually i.e. using sensors other than vision School of Computer Applications

  13. Language and Intelligence Go Left World R. Walshe: Evolution of Early Language State State of the world Grrraahhh = ??? Grrraahhh Action Action Agent (Speaker, Hearer, Learner) Reinforcement Learning Network (Neural Network) Agent (Speaker, Hearer, Learner) Reinforcement Learning Network (Neural Network) • Unique features: • No master • No prior language knowledge School of Computer Applications

  14. Language and Intelligence J. Kelleher: Natural Language interface to 3D world - Situated Language Interpreter Visual Context Natural Language Understanding Natural Language Interface School of Computer Applications

  15. Language and Intelligence Linguistic Level Compounding Cognitive Process Concept Combination J. Hayes : Semantics - computational modelling of nominal compounds ? Computer + Wizard Computer Wizard Generate an Interpretation (form a meaning) Interpretation School of Computer Applications

  16. Language and Intelligence S. Harford: A Neural Network model of Melodic Memory Output Feedback Learning, Feedforward Input Neural Networks Processing School of Computer Applications