A Connectionist Approach to Learn Marathi Language
| Autor: | B.V. Pawar, Satish R. Kolhe |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Artificial neural network
Grammar Computer science business.industry media_common.quotation_subject Inductive reasoning computer.software_genre language.human_language Recurrent neural network Rule-based machine translation Connectionism Neurolinguistics language Artificial intelligence Marathi business computer Natural language processing media_common |
| Zdroj: | ICETET |
| DOI: | 10.1109/icetet.2008.15 |
| Popis: | In this paper, we have investigated the inductive inference of complex grammar of subset of Marathi (Indian) language and results are reported. We have investigated Elman recurrent networks (ERNs), Jordon recurrent networks (JRNs), time lagged recurrent networks (TLRNs) and recurrent neural networks (RNNs). In this empirical study, we consider the task of classifying Marathi language sentences as grammatical or ungrammatical as well as modeled the problem as a prediction problem. We have also analyzed the operation of the networks by investing rule approximation. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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