An Overview of the Shared Task on Machine Translation in Indian Languages (MTIL) – 2017

In recent years, the multilingual content over the internet has grown exponentially together with the evolution of the internet. The usage of multilingual content is excluded from the regional language users because of the language barrier. So, machine translation between languages is the only possi...

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Main Authors: Kumar M. Anand, Premjith B., Singh Shivkaran, Rajendran S., Soman K. P.
Format: Article
Language:English
Published: De Gruyter 2019-07-01
Series:Journal of Intelligent Systems
Subjects:
Online Access:https://doi.org/10.1515/jisys-2018-0024
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author Kumar M. Anand
Premjith B.
Singh Shivkaran
Rajendran S.
Soman K. P.
author_facet Kumar M. Anand
Premjith B.
Singh Shivkaran
Rajendran S.
Soman K. P.
author_sort Kumar M. Anand
collection DOAJ
description In recent years, the multilingual content over the internet has grown exponentially together with the evolution of the internet. The usage of multilingual content is excluded from the regional language users because of the language barrier. So, machine translation between languages is the only possible solution to make these contents available for regional language users. Machine translation is the process of translating a text from one language to another. The machine translation system has been investigated well already in English and other European languages. However, it is still a nascent stage for Indian languages. This paper presents an overview of the Machine Translation in Indian Languages shared task conducted on September 7–8, 2017, at Amrita Vishwa Vidyapeetham, Coimbatore, India. This machine translation shared task in Indian languages is mainly focused on the development of English-Tamil, English-Hindi, English-Malayalam and English-Punjabi language pairs. This shared task aims at the following objectives: (a) to examine the state-of-the-art machine translation systems when translating from English to Indian languages; (b) to investigate the challenges faced in translating between English to Indian languages; (c) to create an open-source parallel corpus for Indian languages, which is lacking. Evaluating machine translation output is another challenging task especially for Indian languages. In this shared task, we have evaluated the participant’s outputs with the help of human annotators. As far as we know, this is the first shared task which depends completely on the human evaluation.
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spelling doaj.art-0e2919b3adb848f0b5dc48cccc57aa162022-12-21T21:59:48ZengDe GruyterJournal of Intelligent Systems0334-18602191-026X2019-07-0128345546410.1515/jisys-2018-0024An Overview of the Shared Task on Machine Translation in Indian Languages (MTIL) – 2017Kumar M. Anand0Premjith B.1Singh Shivkaran2Rajendran S.3Soman K. P.4Department of Information Technology, National Institute of Technology Karnataka, Surathkal, Mangalore 575025, IndiaCenter for Computational Engineering and Networking (CEN), Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, IndiaCenter for Computational Engineering and Networking (CEN), Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, IndiaCenter for Computational Engineering and Networking (CEN), Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, IndiaCenter for Computational Engineering and Networking (CEN), Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, IndiaIn recent years, the multilingual content over the internet has grown exponentially together with the evolution of the internet. The usage of multilingual content is excluded from the regional language users because of the language barrier. So, machine translation between languages is the only possible solution to make these contents available for regional language users. Machine translation is the process of translating a text from one language to another. The machine translation system has been investigated well already in English and other European languages. However, it is still a nascent stage for Indian languages. This paper presents an overview of the Machine Translation in Indian Languages shared task conducted on September 7–8, 2017, at Amrita Vishwa Vidyapeetham, Coimbatore, India. This machine translation shared task in Indian languages is mainly focused on the development of English-Tamil, English-Hindi, English-Malayalam and English-Punjabi language pairs. This shared task aims at the following objectives: (a) to examine the state-of-the-art machine translation systems when translating from English to Indian languages; (b) to investigate the challenges faced in translating between English to Indian languages; (c) to create an open-source parallel corpus for Indian languages, which is lacking. Evaluating machine translation output is another challenging task especially for Indian languages. In this shared task, we have evaluated the participant’s outputs with the help of human annotators. As far as we know, this is the first shared task which depends completely on the human evaluation.https://doi.org/10.1515/jisys-2018-0024machine translationindian languageshuman evaluationmtil
spellingShingle Kumar M. Anand
Premjith B.
Singh Shivkaran
Rajendran S.
Soman K. P.
An Overview of the Shared Task on Machine Translation in Indian Languages (MTIL) – 2017
Journal of Intelligent Systems
machine translation
indian languages
human evaluation
mtil
title An Overview of the Shared Task on Machine Translation in Indian Languages (MTIL) – 2017
title_full An Overview of the Shared Task on Machine Translation in Indian Languages (MTIL) – 2017
title_fullStr An Overview of the Shared Task on Machine Translation in Indian Languages (MTIL) – 2017
title_full_unstemmed An Overview of the Shared Task on Machine Translation in Indian Languages (MTIL) – 2017
title_short An Overview of the Shared Task on Machine Translation in Indian Languages (MTIL) – 2017
title_sort overview of the shared task on machine translation in indian languages mtil 2017
topic machine translation
indian languages
human evaluation
mtil
url https://doi.org/10.1515/jisys-2018-0024
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