Development of Neural Machine Translator for English-Assamese Language Pair
| Autor: | Surajeet Das, Basab Nath, Sunita Sarkar |
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| Rok vydání: | 2021 |
| Předmět: |
Vocabulary
Artificial neural network Machine translation Computer science business.industry media_common.quotation_subject Language barrier Rule-based system Translation (geometry) computer.software_genre language.human_language Assamese language Artificial intelligence Layer (object-oriented design) business computer Natural language processing media_common |
| Zdroj: | Advanced Techniques for IoT Applications ISBN: 9789811644344 |
| Popis: | Machine translation aims to minimize the language barrier between people of different linguistic backgrounds. Machine translation is an automatic translation technique between pairs of different languages. Machine translation using neural network or neural machine translation came into the picture due to several limitation associated with its predecessors which are rule based and statistical based models. For large data sets with a rich range of vocabulary, the neural network machine translation system provides fair translation accuracy. We have observed that there remain very few machine translators dedicated to Indian languages, especially those spoken in the North-East area. So our paper mainly focuses on implementing a neural machine translation system for the English-Assamese language. In this paper we used five different neural machine translation models for English-Assamese language pair using LSTMs and GRUs, along with an attention layer. We have made a comparison analysis based on the performance results of these models. We used BLEU Score to calculate the accuracy of these five models, thus achieving a BLEU score of 34.168%, which was the highest among the five models. |
| Databáze: | OpenAIRE |
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