Improving English-to-Indian Language Neural Machine Translation Systems
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Summary
This study builds English-to-Indian language Neural Machine Translation (NMT) systems using the state-of-the-art transformer architecture and performs a manual evaluation of the translation outputs and observes that the BLEU metric cannot always analyse the MT quality as well as humans.
- Type
- article
- Published
- 2022-05-11
- Cited by
- 26
- References
- 3
- Access
- Open access
- OpenAlex
- https://openalex.org/W4280571180
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:248726751
Keywords
Bengali, BLEU, Machine translation, Evaluation of machine translation, Computer science
References
- TER-Plus: paraphrase, semantic, and alignment enhancements to Translation Edit Rate
- Bleu: a Method for Automatic Evaluation of Machine Translation
- Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages
- Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
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- Bi-Lingual Machine Translation Approach using Long Short–Term Memory Model for Asian Languages
- Improving translation between English, Assamese bilingual pair with monolingual data, length penalty and model averaging
- A comparative analysis of lexical-based automatic evaluation metrics for different Indic language pairs
- Application of Convolution Neural Network Algorithm in English Translation
- A Survey on the MT Methods for Indian Languages: MT Challenges, Availability, and Production of Parallel Corpora, Government Policies and Research Directions
- Sanskrit to Hindi language translation using multimodal neural machine translation
- NEUROSYNTH: Enhancing Cognitive Computing using Deep Neural Networks
- Hearing Beyond Sight: Image Captioning and Translation with Speech Synthesis for the Visually Impaired
- Enhancing Medium-Sized Sentence Translation In English-Hindi NMT Using Clause-Based Approach
- Automatic Running Notes Generation from Audio Lecture using NLP for Comprehensive Learning
- UNIFIED COMMUNICATION: A SURVEY ON HARMONIZING REGIONAL LANGUAGE DIVERSITY
- Research on Low-Resource Neural Machine Translation Methods Based on Explicit Sparse Attention and Pre-trained Language Model
- Cognitive Computing with Deep Neural Networks
- Enhancing Cross Language for English-Telugu pairs through the Modified Transformer Model based Neural Machine Translation
- Design and Development of Efficient English Translation Framework Using Neural Machine Translation Techniques
- Exploring Translation Approaches Using Different Models
- Advancing English-Dogri Machine Translation: A Comparative Study of SMT and NMT Approaches
- Enhancing IndicTrans2 Model for Contextual English to Hindi Translation
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