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    <titleInfo>
        <title>Punjabi to Urdu Machine Translation System</title>
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    <name type="personal">
        <namePart type="given">Nitin</namePart>
        <namePart type="family">Bansal</namePart>
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            <title>Proceedings of the 17th International Conference on Natural Language Processing (ICON): System Demonstrations</title>
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        <name type="personal">
            <namePart type="given">Vishal</namePart>
            <namePart type="family">Goyal</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Asif</namePart>
            <namePart type="family">Ekbal</namePart>
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    <abstract>Development of Machine Translation System (MTS) for any language pair is a challenging task for several reasons. Lack of lexical resources for any language is one of the major issue arise while developing MTS using that language. For example, during the development of Punjabi to Urdu MTS, many issues were recognized while preparing lexical resources for both the language. Since there is no machine readable dictionary is available for Punjabi to Urdu which can be directly used for translation; however various dictionaries are available to explain the meaning of word. Along with this, handling of OOV (out of vocabulary words), handling of multiple sense Punjabi word in Urdu, identification of proper nouns, identification of collocations in the source sentence i.e. Punjabi sentence in our case, are the issues which we are facing during development of this system. Since MTSs are in great demand from the last one decade and are being widely used in applications such as in case of smart phones. Therefore, development of such a system becomes more demanding and more users friendly. There usage is mainly in large scale translations, automated translations; act as an instrument to bridge a digital divide.</abstract>
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        <url>https://aclanthology.org/2020.icon-demos.13</url>
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            <start>32</start>
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%0 Conference Proceedings
%T Punjabi to Urdu Machine Translation System
%A Bansal, Nitin
%A Kumar, Ajit
%Y Goyal, Vishal
%Y Ekbal, Asif
%S Proceedings of the 17th International Conference on Natural Language Processing (ICON): System Demonstrations
%D 2020
%8 December
%I NLP Association of India (NLPAI)
%C Patna, India
%F bansal-kumar-2020-punjabi
%X Development of Machine Translation System (MTS) for any language pair is a challenging task for several reasons. Lack of lexical resources for any language is one of the major issue arise while developing MTS using that language. For example, during the development of Punjabi to Urdu MTS, many issues were recognized while preparing lexical resources for both the language. Since there is no machine readable dictionary is available for Punjabi to Urdu which can be directly used for translation; however various dictionaries are available to explain the meaning of word. Along with this, handling of OOV (out of vocabulary words), handling of multiple sense Punjabi word in Urdu, identification of proper nouns, identification of collocations in the source sentence i.e. Punjabi sentence in our case, are the issues which we are facing during development of this system. Since MTSs are in great demand from the last one decade and are being widely used in applications such as in case of smart phones. Therefore, development of such a system becomes more demanding and more users friendly. There usage is mainly in large scale translations, automated translations; act as an instrument to bridge a digital divide.
%U https://aclanthology.org/2020.icon-demos.13
%P 32-34

Markdown (Informal)

[Punjabi to Urdu Machine Translation System](https://aclanthology.org/2020.icon-demos.13) (Bansal & Kumar, ICON 2020)

• Punjabi to Urdu Machine Translation System (Bansal & Kumar, ICON 2020)

ACL

• Nitin Bansal and Ajit Kumar. 2020. Punjabi to Urdu Machine Translation System. In Proceedings of the 17th International Conference on Natural Language Processing (ICON): System Demonstrations, pages 32–34, Patna, India. NLP Association of India (NLPAI).