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    <titleInfo>
        <title>Machine Translation Revisited: An Operational Reality Check</title>
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    <name type="personal">
        <namePart type="given">Kathleen</namePart>
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        <dateIssued>2012-oct 28-nov 1</dateIssued>
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        <titleInfo>
            <title>Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Government MT User Program</title>
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            <publisher>Association for Machine Translation in the Americas</publisher>
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                <placeTerm type="text">San Diego, California, USA</placeTerm>
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    <abstract>The government and the research community have strived for the past few decades to develop machine translation capabilities. Historically, DARPA took the lead in the grand challenge aiming at surpassing human translation quality. While we have made strides from rule based, to statistical and hybrid machine translation engines, we cannot rely solely on machine translation to overcome the language barrier and accomplish the mission. Machine Translation is often misunderstood or misplaced in the operational settings as expectations are unrealistic and optimization not achieved. With the increase in volume, variety and velocity of data, new paradigms are needed when choosing machine translation software and embedding it into a business process so as to achieve the operational goals. The talk will focus on the operational requirements and frame where, when and how to use machine translation. We will also outline some gaps and suggest new areas for research, development, and implementation.</abstract>
    <identifier type="citekey">egan-2012-machine</identifier>
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        <url>https://aclanthology.org/2012.amta-government.5</url>
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%0 Conference Proceedings
%T Machine Translation Revisited: An Operational Reality Check
%A Egan, Kathleen
%S Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Government MT User Program
%D 2012
%8 oct 28 nov 1
%I Association for Machine Translation in the Americas
%C San Diego, California, USA
%F egan-2012-machine
%X The government and the research community have strived for the past few decades to develop machine translation capabilities. Historically, DARPA took the lead in the grand challenge aiming at surpassing human translation quality. While we have made strides from rule based, to statistical and hybrid machine translation engines, we cannot rely solely on machine translation to overcome the language barrier and accomplish the mission. Machine Translation is often misunderstood or misplaced in the operational settings as expectations are unrealistic and optimization not achieved. With the increase in volume, variety and velocity of data, new paradigms are needed when choosing machine translation software and embedding it into a business process so as to achieve the operational goals. The talk will focus on the operational requirements and frame where, when and how to use machine translation. We will also outline some gaps and suggest new areas for research, development, and implementation.
%U https://aclanthology.org/2012.amta-government.5

Markdown (Informal)

[Machine Translation Revisited: An Operational Reality Check](https://aclanthology.org/2012.amta-government.5) (Egan, AMTA 2012)

• Machine Translation Revisited: An Operational Reality Check (Egan, AMTA 2012)

ACL

• Kathleen Egan. 2012. Machine Translation Revisited: An Operational Reality Check. In Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Government MT User Program, San Diego, California, USA. Association for Machine Translation in the Americas.