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Deep Learning Approach to English-Tamil and Hindi-Tamil Verb Phrase Translations

D. Thenmozhi, B. Senthil Kumar, Chandrabose Aravindan
2018 Forum for Information Retrieval Evaluation  
In this paper, we present a deep learning methodology for English-Tamil and Hindi-Tamil VP translations.  ...  Verb phrase (VP) translation focuses on translating all forms of verbs that helps in Machine translation (MT) task.  ...  Proposed Methodology A Sequence to Sequence (Seq2Seq) [11, 2] deep neural network is used in our approach for English-Tamil and Hindi-Tamil verb phrase translations.  ... 
dblp:conf/fire/ThenmozhiKA18c fatcat:oypniwnvqncqtghf4vsbtpe2bq

Overview of Verb Phrase Translation in Machine Translation: English to Tamil and Hindi to Tamil

R. Vijay Sundar Ram, Sobha Lalitha Devi
2018 Forum for Information Retrieval Evaluation  
We present an overview of verb phrase translation in machine translation from English to Tamil and Hindi to Tamil track, where English, Hindi and Tamil belong to three different language families, namely  ...  There were three submissions for English to Tamil Verb phrase translation and two submissions for Hindi to Tamil verb phrase translation.  ...  Thenmozhi-SSN has adopted Neural Machine Translation model for this task. They have used a deep learning approach based on Seq2Seq model for English-Tamil and Hindi-Tamil VP translations.  ... 
dblp:conf/fire/RamD18 fatcat:lx6iitzysfcibc46mfawxujxde

NMT based Tamil Translation

Aditya Kumar Pathak, Himanshu Choudhary, Rajiv Ratn Shah
2018 Forum for Information Retrieval Evaluation  
We got the 26.97% Precision,37.98% Recall for English to Tamil and 25.18% Precision and 27.24% Recall for Tamil to Hindi respectively.  ...  In this paper, we apply NMT for English-Tamil and Hindi-Tamil language pair.  ...  Especially, we work on English-Tamil and Tamil-Hindi language pair as these are the most difficult language pair [2] to translate due to morphologically richness of Tamil and Hindi language.  ... 
dblp:conf/fire/PathakCS18 fatcat:q6nwwy3355bzjbskcdc6yx3xki

Machine Translation Approaches and Survey for Indian Languages

P. J. Antony
2013 International Journal of Computational Linguistics and Chinese Language Processing  
Even though there has been effort towards building English to Indian language and Indian language to Indian language translation system, unfortunately, we do not have an efficient translation system as  ...  The literature shows that there have been many attempts in MT for English to Indian languages and Indian languages to Indian languages.  ...  English to (Hindi, Kannada, Tamil) and Kannada to Tamil language-pair EBMT system (2006) An example-based English to Hindi, Kannada, and Tamil, as well as Kannada to Tamil (Dwivedi et al., 2010) , MT  ... 
dblp:journals/ijclclp/Antony13 fatcat:qdvuimruancyzfdjl6qu3zemya

A comprehensive survey on Indian regional language processing

B. S. Harish, R. Kasturi Rangan
2020 SN Applied Sciences  
The tasks like machine translation, Named Entity Recognition, Sentiment Analysis and Parts-Of-Speech tagging are reviewed with respect to Rule, Statistical and Neural based approaches.  ...  In this survey, the various approaches and techniques contributed by the researchers for Indian regional language processing are reviewed.  ...  [25] worked on English to Hindi MT using Interlingua. Rule based sentence simplification technique is proposed by [65] for English to Tamil translation task.  ... 
doi:10.1007/s42452-020-2983-x fatcat:e3u5r5qo7ngapj5mbiwit7qlwi

HiPHET: A Hybrid Approach to Translate Code Mixed Language (Hinglish) to Pure Languages (Hindi and English)

Shree Harsh Attri, T.V. Prasad, G. Ramakrishna
2020 Computer Science  
The tool translated in three ways, namely, Hinglish to Pure Hindi and Pure English, Pure Hindi to Pure English and vice versa.  ...  As a result of this need the tool named Hinglish to Pure Hindi and English Translator was developed.  ...  In this sentence, HiPHET identified the phrase "as soon as possible" as English and translated it in the direction of English to Hindi to the phrase "yathA shIghra".  ... 
doi:10.7494/csci.2020.21.3.3624 fatcat:qn4vppzdgzdg5glzsjli6h6a2m

Neural Machine Translation System for English to Indian Language Translation Using MTIL Parallel Corpus: Special Issue on Natural Language Processing

B. Premjith, M. Anand Kumar, K.P. Soman
2019 Journal of Intelligent Systems  
In this paper, we propose a neural machine translation (NMT) system for four language pairs: English–Malayalam, EnglishHindi, EnglishTamil, and English–Punjabi.  ...  Analysis of the results showed the presence of lengthy sentences in English–Malayalam, and the EnglishHindi corpus affected the translation.  ...  [37] , AnglaHindi (IIT, Kanpur, India) used an example-based approach to translate frequently occurring noun and verb phrases.  ... 
doi:10.1515/jisys-2019-2510 fatcat:izu7zhjhbrexxpvwg4tae4ah4y

Machine Translation Approaches and Survey for Indian Languages [article]

Nadeem Jadoon Khan, Waqas Anwar, Nadir Durrani
2017 arXiv   pre-print
We report the performance of baseline systems translating from Indian languages (Bengali, Guajarati, Hindi, Malayalam, Punjabi, Tamil, Telugu and Urdu) into English with average 10% accurate results for  ...  Such data is necessary to reliably estimate translation probabilities.  ...  ., 2012) presented a Phrase based model approach to English-Hindi translation.  ... 
arXiv:1701.04290v1 fatcat:awsv2wioljduzofvkinejcl3wu

Machine Translation Systems for Indian Languages

Latha R.Nair, David Peter S.
2012 International Journal of Computer Applications  
Syntactic structure transfer for verbs from Tamil to Hindi is discussed in [5] .  ...  An English to Hindi MT system which combines RBMT and phrase-based SMT approach was developed at IIIT Hyderabad in 2010.  ... 
doi:10.5120/4785-7014 fatcat:cnsprg7cyzaodn3wq5z6vhoolu

HIT: A Hierarchically Fused Deep Attention Network for Robust Code-mixed Language Representation [article]

Ayan Sengupta, Sourabh Kumar Bhattacharjee, Tanmoy Chakraborty, Md Shad Akhtar
2021 arXiv   pre-print
Our evaluation of HIT on one European (Spanish) and five Indic (Hindi, Bengali, Tamil, Telugu, and Malayalam) languages across four NLP tasks on eleven datasets suggests significant performance improvement  ...  We further show the adaptability of learned representation across tasks in a transfer learning setup (with and without fine-tuning).  ...  Acknowledgement The work was partially supported by the Ramanujan Fellowship (SERB) and the Infosys Centre for AI, IIITD.  ... 
arXiv:2105.14600v1 fatcat:bqtnemsqmvb5zitwnz6rjdl3n4

Survey on Publicly Available Sinhala Natural Language Processing Tools and Research [article]

Nisansa de Silva
2022 arXiv   pre-print
However, due to various reasons, these attempts seem to lack coordination and awareness of each other.  ...  drive its cousin English has nor the sheer push of the law of numbers a language such as Chinese has.  ...  Similarly, the authors would also like to thank Shravan Kale for checking the examples we have provided in Hindi for their accuracy.  ... 
arXiv:1906.02358v13 fatcat:c522aedklbbhraw4fthg3yvweu

Entity Projection via Machine Translation for Cross-Lingual NER

Alankar Jain, Bhargavi Paranjape, Zachary C. Lipton
2019 Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)  
Motivated by this fact, we leverage machine translation to improve annotationprojection approaches to cross-lingual named entity recognition.  ...  We propose a system that improves over prior entity-projection methods by: (a) leveraging machine translation systems twice: first for translating sentences and subsequently for translating entities; (  ...  Owing to the dependence of stateof-the-art deep learning approaches on massive amounts of data, creating suitable datasets can be prohibitively expensive.  ... 
doi:10.18653/v1/d19-1100 dblp:conf/emnlp/JainPL19 fatcat:v5ioafwvizb7fginwsl3zkerga

Context-based Machine Translation of English-Hindi using CE-Encoder

Mani Bansal, D. K. Lobiyal
2021 Journal of Computer Science  
We conduct experiments on the datasets from ILCC and CFILT for the English-Hindi language pair.  ...  Our Neural Machine Translation (NMT) approach focuses on the encoder to apprehend the meaning of source sentences for improved translation.  ...  We are also thankful to Department of Science and Technology (DST) for support through PURSE Grant. We also acknowledge the support from C-DAC for providing ILCC data set.  ... 
doi:10.3844/jcssp.2021.825.843 fatcat:2gl4bxfg6veppcczyyblsokp5q

Multilingual Multiword Expressions [article]

Lahari Poddar
2016 arXiv   pre-print
The project aims to provide a semi-supervised approach to identify Multiword Expressions in a multilingual context consisting of English and most of the major Indian languages.  ...  To automatically extract multiword expressions from a corpus, an extraction pipeline have been constructed which consist of a combination of rule based and statistical approaches.  ...  extraction engine on English side of the corpora and studied the Hindi translation equivalents of English 'collocations'.  ... 
arXiv:1612.00246v1 fatcat:4rs33ntycnadvnn6e3atd3ixra

Entity Projection via Machine Translation for Cross-Lingual NER [article]

Alankar Jain, Bhargavi Paranjape, Zachary C. Lipton
2019 arXiv   pre-print
Motivated by this fact, we leverage machine translation to improve annotation-projection approaches to cross-lingual named entity recognition.  ...  We propose a system that improves over prior entity-projection methods by: (a) leveraging machine translation systems twice: first for translating sentences and subsequently for translating entities; (  ...  Owing to the dependence of stateof-the-art deep learning approaches on massive amounts of data, creating suitable datasets can be prohibitively expensive.  ... 
arXiv:1909.05356v2 fatcat:rxqsigubgve6fgfx7v4tnzab2q
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