Self-Organizing Maps
Discrete Time Processing of Speech Signals
Discrete Time Processing of Speech Signals
Early lexical development in a self-organizing neural network
Neural Networks - 2004 Special issue: New developments in self-organizing systems
Modeling the Bilingual Lexicon of an Individual Subject
WSOM '09 Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps
Neural network models for language acquisition: a brief survey
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Clustering of the self-organizing map
IEEE Transactions on Neural Networks
| Hi-index | 0.00 |
In this paper the SOM is used in an exploratory analysis of transfer phenomena from first language (L1) to the second language (L2) related to word/lexical stress. The basic hypothesis tested is whether the parameterization of the speech signal of the learner's utterances by standard signal processing techniques, such as Linear Predictive Coding (LPC), used to encode the input of the network results in efficient categorization of speakers by the SOM. Preliminary results indicates that the combination LPC+SOM is indeed able to produce well-defined clusters of speakers that possess similarities regarding the transfer of stress patterns among Brazilian students in learning English as a foreign language.