Learning words from sights and sounds: a computational model

Cognitive Science 26 (1):113-146 (2002)
  Copy   BIBTEX

Abstract

This paper presents an implemented computational model of word acquisition which learns directly from raw multimodal sensory input. Set in an information theoretic framework, the model acquires a lexicon by finding and statistically modeling consistent cross‐modal structure. The model has been implemented in a system using novel speech processing, computer vision, and machine learning algorithms. In evaluations the model successfully performed speech segmentation, word discovery and visual categorization from spontaneous infant‐directed speech paired with video images of single objects. These results demonstrate the possibility of using state‐of‐the‐art techniques from sensory pattern recognition and machine learning to implement cognitive models which can process raw sensor data without the need for human transcription or labeling.

Other Versions

No versions found

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 103,449

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Analytics

Added to PP
2013-11-21

Downloads
41 (#573,490)

6 months
4 (#864,415)

Historical graph of downloads
How can I increase my downloads?

References found in this work

Word and Object.Willard Van Orman Quine - 1960 - Les Etudes Philosophiques 17 (2):278-279.
Word and Object.Henry W. Johnstone - 1961 - Philosophy and Phenomenological Research 22 (1):115-116.
On the genesis of abstract ideas.M. I. Posner & S. W. Keele - 1968 - Journal of Experimental Psychology 77 (2p1):353-363.

View all 10 references / Add more references