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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

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language and intelligence
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

language and intelligence2
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

language and intelligence3
Language and Intelligence
  • NCLT
    • National Centre for Language Technologies
    • computing.dcu.ie/nclt
  • World Wide Mind
    • w2mind.org
language research areas
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

language research areas5
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

language research areas6
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

language research areas7
Language Research Areas

Speaker Characterisation

Machine Translation

Separate Linguistic Data from Speaker Characteristics

Hello

New Language

Bonjour

School of Computer Applications

language research areas8
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

intelligence
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

intelligence10
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

language and intelligence11
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

language and intelligence12
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

language and intelligence13
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

language and intelligence14
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

language and intelligence15
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

language and intelligence16
Language and Intelligence

S. Harford: A Neural Network model of Melodic Memory

Output

Feedback

Learning, Feedforward

Input

Neural Networks

Processing

School of Computer Applications