NEURAL MACHINE TRANSLATION USING ATTENTION MECHANISM
Vishwas Dhabhai
, Vatsal Joshi , Akash Jadhav
The development of Neural Machine Translation (NMT) has revolutionized the field of machine translation. This review paper provides a comprehensive overview of the recent advances in NMT, including its history, architecture, evaluation methods, and applications. The paper starts with a background on machine translation and a brief history of NMT. It then discusses the various NMT architectures, such as Encoder-Decoder, Transformer, and Hybrid models, and compares their strengths and weaknesses. The evaluation methods for NMT, including Bleu score, meteor score, and human evaluation, are also covered in detail. The paper concludes with a discussion of the various applications of NMT, including its use in multilingual communication, cross-lingual information retrieval, and machine-aided language learning. The paper provides insights into the current state-of-the-art NMT systems and identifies future research directions in this field.
"NEURAL MACHINE TRANSLATION USING ATTENTION MECHANISM", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.b778-b787, March-2023, Available :https://ijnrd.org/papers/IJNRD2303186.pdf
Volume 8
Issue 3,
March-2023
Pages : b778-b787
Paper Reg. ID: IJNRD_188775
Published Paper Id: IJNRD2303186
Downloads: 000118857
Research Area: Computer Science & Technology
Country: Udaipur, Rajasthan, India
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJNRD (IJ Publication) Janvi Wave
