SMT and Hybrid systems of the QTLeap project in the WMT16 IT-task

نویسندگان

  • Rosa Del Gaudio
  • Gorka Labaka
  • Eneko Agirre
  • Petya Osenova
  • Kiril Ivanov Simov
  • Martin Popel
  • Dieke Oele
  • Gertjan van Noord
  • Luís Gomes
  • João António Rodrigues
  • Steven Neale
  • João Ricardo Silva
  • Andreia Querido
  • Nuno Rendeiro
  • António Branco
چکیده

This paper presents the description of 12 systems submitted to the WMT16 IT-task, covering six different languages, namely Basque, Bulgarian, Dutch, Czech, Portuguese and Spanish. All these systems were developed under the scope of the QTLeap project, presenting a common strategy. For each language two different systems were submitted, namely a phrasebased MT system built using Moses, and a system exploiting deep language engineering approaches, that in all the languages but Bulgarian was implemented using TectoMT. For 4 of the 6 languages, the TectoMT-based system performs better than the Moses-based one.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Hybrid Machine Translation System Based on a Monotone Decoder

In this paper, a hybrid Machine Translation (MT) system is proposed by combining the result of a rule-based machine translation (RBMT) system with a statistical approach. The RBMT uses a set of linguistic rules for translation, which leads to better translation results in terms of word ordering and syntactic structure. On the other hand, SMT works better in lexical choice. Therefore, in our sys...

متن کامل

ParFDA for Instance Selection for Statistical Machine Translation

We build parallel feature decay algorithms (ParFDA) Moses statistical machine translation (SMT) systems for all language pairs in the translation task at the first conference on statistical machine translation (Bojar et al., 2016a) (WMT16). ParFDA obtains results close to the top constrained phrase-based SMT with an average of 2.52 BLEU points difference using significantly less computation for...

متن کامل

Results of the WMT16 Metrics Shared Task

This paper presents the results of the WMT16 Metrics Shared Task. We asked participants of this task to score the outputs of the MT systems involved in the WMT16 Shared Translation Task. We collected scores of 16 metrics from 9 research groups. In addition to that, we computed scores of 9 standard metrics (BLEU, SentBLEU, NIST, WER, PER, TER and CDER) as baselines. The collected scores were eva...

متن کامل

SHEF-Multimodal: Grounding Machine Translation on Images

This paper describes the University of Sheffield’s submission for the WMT16 Multimodal Machine Translation shared task, where we participated in Task 1 to develop German-to-English and Englishto-German statistical machine translation (SMT) systems in the domain of image descriptions. Our proposed systems are standard phrase-based SMT systems based on the Moses decoder, trained only on the provi...

متن کامل

Yandex School of Data Analysis approach to English-Turkish translation at WMT16 News Translation Task

We describe the English-Turkish and Turkish-English translation systems submitted by Yandex School of Data Analysis team to WMT16 news translation task. We successfully applied hand-crafted morphological (de-)segmentation of Turkish, syntax-based pre-ordering of English in English-Turkish and post-ordering of English in Turkish-English. We perform desegmentation using SMT and propose a simple y...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2016