TAILIEUCHUNG - Báo cáo khoa học: "Modelling Early Language Acquisition Skills: Towards a General Statistical Learning Mechanism"

This paper reports the on-going research of a thesis project investigating a computational model of early language acquisition. The model discovers word-like units from crossmodal input data and builds continuously evolving internal representations within a cognitive model of memory. Current cognitive theories suggest that young infants employ general statistical mechanisms that exploit the statistical regularities within their environment to acquire language skills. | Modelling Early Language Acquisition Skills Towards a General Statistical Learning Mechanism Guillaume Aimetti University of Sheffield Sheffield UK Abstract This paper reports the on-going research of a thesis project investigating a computational model of early language acquisition. The model discovers word-like units from cross-modal input data and builds continuously evolving internal representations within a cognitive model of memory. Current cognitive theories suggest that young infants employ general statistical mechanisms that exploit the statistical regularities within their environment to acquire language skills. The discovery of lexical units is modelled on this behaviour as the system detects repeating patterns from the speech signal and associates them to discrete abstract semantic tags. In its current state the algorithm is a novel approach for segmenting speech directly from the acoustic signal in an unsupervised manner therefore liberating it from a pre-defined lexicon. By the end of the project it is planned to have an architecture that is capable of acquiring language and communicative skills in an online manner and carry out robust speech recognition. Preliminary results already show that this method is capable of segmenting and building accurate internal representations of important lexical units as emergent properties from cross-modal data. 1 Introduction Conventional Automatic Speech Recognition ASR systems can achieve very accurate recognition results particularly when used in their optimal acoustic environment on examples within their stored vocabularies. However when taken out of their comfort zone accuracy significantly deteriorates and does not come anywhere near human speech processing abilities for even the simplest of tasks. This project investigates novel computational language acquisition techniques that attempt to model current cognitive theories in order to achieve a more robust speech recognition system. .

• Báo cáo khoa học
• Modelling Early Language Acquisition Skills
• Towards a General Statistical Learning Mechanism
• Guillaume Aimetti
• scientific reports
• model language
• process natural language
• Dialog Control
• Natural Language System
• Dialog Control in a Natural Language System
• Expanding the Horizons
• Natural Language Interfaces
• Phil Hayes
• PROSPECTS OR PRACTICAL
• NATURAL LANGUAGE SYSTEMS
• Workshops
• NATURAL LANGUAGE
• INTERACTION WITH MACHINES
• Long Papers
• COMPUTER INTEBFACE DESIGN MURRAY TUROFF DEPARTMENT OF COMPUTER
• IiVFORMATION SCIENCE IIEW JERSEY INSTITUTE OF TECHNOLOGY
• EVALUATION OF NATURAL LANGUAGE
• INTERFACES TO DATABASE SYSTEMS
• A PANEL DISCUSSION
• database query system
• J
• Norwood Crout
• INTERFACES TO DATA BASE SYSTEMS
• Bozena Henisz
• INTERPRETING NATURAL LANGUAGE
• DATABASE UPDATES
• S
• Jermld Kaplan Jim David
• TRANSPORTABLE NATURAL LANGUAGE
• INTERFACES TO DATABASES
• Gary G
• Hendrlx and William H
• Lewis
• DATABASES THEORETICAL
• TECHNICAL ISSUES
• TRANSPORTABLE NATURAL LANGUAGE INTERFACES
• PROBLEMS AND TECHNIQUES
• Barbara J
• Grosz
• THEORETICAL TECHNICAL ISSUES
• NATURAL LANGUAGE ACCESS TO DATABASES
• R
• Petrick
• Domain Independent
• Database Access Systems
• ISSUES IN NATURAL LANGUAGE
• ACCESS TO DATABASES
• A LOGIC PROGRAMMING PERSPECTIVE
• Sharon C
• Salveter David Maier
• PLANNING NATURAL LANGUAGE
• EXPRESSIONS REFERRING
• Douglas E
• Appelt
• THE TEXT SYSTEM
• NATURAL LANGUAGE GENERATION
• Kathleen R
• M
• MENTING A DATABASE
• KNOWLEDGE REPRESENTATION
• THE KEY TO THE SELECTION PROBLEM
• E
• Jeffrey Conklin David D
• McDonald
• A KNOWLEDGE ENGINEERING
• NATURAL LANGUAGE UNDERSTANDING
• Stuart C
• Shapiro
• NATURAL LANGUAGE TEXTS
• NECESSARILY GRAMMATICAL
• EVEN COMPLETE
• UNGRAMHATICALITY
• EXTRA GRAMMATICALITY
• NATURAL LANGUAGE UNDERSTANDING SYSTEMS
• Taxonomy
• Descriptions
• Individuals in Natural
• Language Understanding
• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln