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NIST 2012 open machine translation (OpenMT) progress test five language source.
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İsim NIST 2012 open machine translation (OpenMT) progress test five language source.
İsim Orijinal /
Basım Tarihi: 2014
Basım Yeri - [Philadelphia, PA] : Linguistic Data Consortium, ©2014.
Konu Machine translating. Arabic language -- Translating into English -- Databases. Chinese language -- Translating into English -- Databases. Dari language -- Translating into English -- Databases. Korean language -- Translating into English -- Databases. Persian language -- Translating into English -- Databases. Arabic language -- Translating into English. Chinese language -- Translating into English. Korean language -- Translating into English. Machine translating. Databases.
Tür Diğer
Dil ara,eng,fas,kor,zho
Dijital Evet
Yazma Hayır
Fiziksel Boyutlar |
Kütüphane: Chicago Üniversitesi
Kayıt Numarası 9982466
Tarih 2014
Notlar Title from disc label.Author: NIST Multimodal Information Group.Data type: Text.Data sources: Web collection, newswire.Application: Machine translation.Dari, Korean, Persian, English, Mandarin Chinese, Arabic, Iranian Persian, Chinese.. 1 CD-ROM ; 4 3/4 in.. "NIST 2012 Open Machine Translation (OpenMT) Progress Test Five Language Source was developed by NIST Multimodal Information Group. This release contains the evaluation sets (source data and human reference translations), DTD, scoring software, and evaluation plan for the OpenMT 2012 test for Arabic, Chinese, Dari, Farsi, and Korean to English on a parallel data set. The objective of the OpenMT evaluation series is to support research in, and help advance the state of the art of, machine translation (MT) technologies -- technologies that translate text between human languages. Input may include all forms of text. The goal is for the output to be an adequate and fluent translation of the original. The 2012 task included the evaluation of five language pairs: Arabic-to-English, Chinese-to-English, Dari-to-English, Farsi-to-English and Korean-to-English in two source data styles." -- LDC online catalogue.
Diğer yazarlar / katkıda bulunanlar NIST Multimodal Information Group. National Institute of Standards and Technology (U.S.) Linguistic Data Consortium.
ISBN 15856366819781585636686
Kaynağa git Chicago Üniversitesi University of Chicago
University of Chicago Chicago Üniversitesi
Kaynağa git

NIST 2012 open machine translation (OpenMT) progress test five language source.

(/)
Basım Tarihi 2014
Basım Yeri - [Philadelphia, PA] : Linguistic Data Consortium, ©2014.
Konu Machine translating. Arabic language -- Translating into English -- Databases. Chinese language -- Translating into English -- Databases. Dari language -- Translating into English -- Databases. Korean language -- Translating into English -- Databases. Persian language -- Translating into English -- Databases. Arabic language -- Translating into English. Chinese language -- Translating into English. Korean language -- Translating into English. Machine translating. Databases.
Tür Diğer
Dil ara,eng,fas,kor,zho
Dijital Evet
Yazma Hayır
Fiziksel Boyutlar |
Kütüphane Chicago Üniversitesi
Kayıt Numarası 9982466
Tarih 2014
Notlar Title from disc label.Author: NIST Multimodal Information Group.Data type: Text.Data sources: Web collection, newswire.Application: Machine translation.Dari, Korean, Persian, English, Mandarin Chinese, Arabic, Iranian Persian, Chinese.. 1 CD-ROM ; 4 3/4 in.. "NIST 2012 Open Machine Translation (OpenMT) Progress Test Five Language Source was developed by NIST Multimodal Information Group. This release contains the evaluation sets (source data and human reference translations), DTD, scoring software, and evaluation plan for the OpenMT 2012 test for Arabic, Chinese, Dari, Farsi, and Korean to English on a parallel data set. The objective of the OpenMT evaluation series is to support research in, and help advance the state of the art of, machine translation (MT) technologies -- technologies that translate text between human languages. Input may include all forms of text. The goal is for the output to be an adequate and fluent translation of the original. The 2012 task included the evaluation of five language pairs: Arabic-to-English, Chinese-to-English, Dari-to-English, Farsi-to-English and Korean-to-English in two source data styles." -- LDC online catalogue.
Diğer yazarlar / katkıda bulunanlar NIST Multimodal Information Group. National Institute of Standards and Technology (U.S.) Linguistic Data Consortium.
ISBN 15856366819781585636686
University of Chicago
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