Computing consensus translation from multiple machine translation systems

被引:0
|
作者
Bangalore, S [1 ]
Bordel, G [1 ]
Riccardi, G [1 ]
机构
[1] AT&T Labs Res, Florham Pk, NJ USA
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we address the problem of computing a consensus translation given the outputs from a set of Machine Translation (MT) systems. The translations from the MT systems are aligned with a multiple string alignment algorithm and the consensus translation is then computed. We describe the multiple string alignment algorithm and the consensus MT hypothesis computation. We report on the subjective and objective performance of the multilingual acquisition approach on a limited domain spoken language application. We evaluate five domain-independent off-the-shelf MT systems and show that the consensus-based translation performs equal or better than any of the given MT systems both in term of objective and subjective measures.
引用
收藏
页码:351 / 354
页数:4
相关论文
共 50 条
  • [31] Neural Machine Translation as a Novel Approach to Machine Translation
    Benkova, Lucia
    Benko, Lubomir
    DIVAI 2020: 13TH INTERNATIONAL SCIENTIFIC CONFERENCE ON DISTANCE LEARNING IN APPLIED INFORMATICS, 2020, : 499 - 508
  • [32] Diverse Machine Translation with Translation Memory
    Zhang, Yi
    Zhao, Jing
    Sun, Shiliang
    2022 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2022,
  • [33] Machine Translation Shortcomings and Teaching Translation
    Mirzoyeva, Leila
    REVISTA ROMANEASCA PENTRU EDUCATIE MULTIDIMENSIONALA, 2023, 15 (03): : 232 - 242
  • [34] Comparison of crowdsourcing translation with Machine Translation
    Anastasiou, Dimitra
    Gupta, Rajat
    JOURNAL OF INFORMATION SCIENCE, 2011, 37 (06) : 637 - 659
  • [35] HUMAN TRANSLATION, TRANSLATION MACHINE AND QUALITY
    Fiola, Marco A.
    HERMENEUS, 2014, (16): : 21 - 26
  • [36] Machine translation and human translation Using machine translation engines and corpora for teaching and research
    Maia, Belinda
    CURRENT TRENDS IN CONTRASTIVE LINGUISTICS: FUNCTIONAL AND COGNITIVE PERSPECTIVES, 2008, 60 : 123 - 145
  • [37] A Corpus of Machine Translation Errors Extracted from Translation Students Exercises
    Wisniewski, Guillaume
    Kuebler, Natalie
    Yvon, Francois
    LREC 2014 - NINTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 2014, : 3585 - 3588
  • [38] Functionality Evaluation Model for Machine Translation Systems
    Kostin, A. V.
    Smirnov, V. V.
    JOURNAL OF COMPUTER AND SYSTEMS SCIENCES INTERNATIONAL, 2018, 57 (01) : 157 - 169
  • [39] Word Reordering as a Preprocessor for Machine Translation Systems
    Devendrakumar, R. N.
    Praveena, A.
    PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON INVENTIVE SYSTEMS AND CONTROL (ICISC 2017), 2017, : 833 - 836
  • [40] Combining Machine Translation Systems with Quality Estimation
    Laki, Laszlo Janos
    Yang, Zijian Gyozo
    COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING, CICLING 2017, PT II, 2018, 10762 : 435 - 444