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Parallel Corpora Preparation for English-Amharic Machine Translation
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In: IWANN 2021 - International Work on Artificial Neural Networks, Conference Springer LNCS proceedings ; https://hal.inria.fr/hal-03272258 ; IWANN 2021 - International Work on Artificial Neural Networks, Conference Springer LNCS proceedings, Jun 2021, Online, Spain (2021)
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Использование метрики BLEU для оценки естественности текста лингвистических стегосистем ... : Use of the Bleu Metric to Assess the Naturality of the Text of Linguistic Stegosystems ...
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The Improvement of Machine Translation Quality with Help of Structural Analysis and Formal Methods-Based Text Processing ...
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Primerjava običajnih in faktorskih modelov pri statističnem strojnem prevajanju iz angleščine v slovenščino z orodjem Moses
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In: Slovenščina 2.0: Empirične, aplikativne in interdisciplinarne raziskave, Vol 5, Iss 1 (2018) (2018)
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Towards Optimizing MT for Post-Editing Effort: Can BLEU Still Be Useful?
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Benchmarking SMT performance for Farsi using the TEP++ Corpus
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In: Passban, Peyman, Way, Andy orcid:0000-0001-5736-5930 and Liu, Qun orcid:0000-0002-7000-1792 (2015) Benchmarking SMT performance for Farsi using the TEP++ Corpus. In: 18th Annual Conference of the European Association for Machine Translation, 11 - 13 May 2015., Antalya, Turkey. (2015)
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Abstract:
Statistical machine translation (SMT) suffers from various problems which are exacerbated where training data is in short supply. In this paper we address the data sparsity problem in the Farsi (Persian) language and introduce a new parallel corpus, TEP++. Compared to previous results the new dataset is more efficient for Farsi SMT engines and yields better output. In our experiments using TEP++ as bilingual training data and BLEU as a metric, we achieved improvements of +11.17 (60%) and +7.76 (63.92%) in the Farsi– English and English–Farsi directions, respectively. Furthermore we describe an engine (SF2FF) to translate between formal and informal Farsi which in terms of syntax and terminology can be seen as different languages. The SF2FF engine also works as an intelligent normalizer for Farsi texts. To demonstrate its use, SF2FF was used to clean the IWSLT–2013 dataset to produce normalized data, which gave improvements in translation quality over FBK’s Farsi engine when used as training data
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Keyword:
BLEU; FBK; Machine translating; SF2FF engine
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URL: http://doras.dcu.ie/23218/
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Hybrid Arabic–French machine translation using syntactic re-ordering and morphological pre-processing
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In: 32 ; 1 ; 135 ; 144 (2014)
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La ligne bleue des Vosges
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In: Mots. Les langages du politique, n 105, 2, 2014-09-24, pp.13-26 (2014)
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On automatic machine translation evaluation
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In: Slovenščina 2.0: Empirične, aplikativne in interdisciplinarne raziskave, Vol 1, Iss 1, Pp 111-133 (2013) (2013)
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O avtomatski evalvaciji strojnega prevajanja
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In: Slovenščina 2.0: Empirične, aplikativne in interdisciplinarne raziskave, Vol 1, Iss 1 (2013) (2013)
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Féron, Jean. Le philtre bleu
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In: Voix Plurielles; Vol 9 No 1 (2012); 148-149 ; Voix Plurielles; Vol. 9 No 1 (2012); 148-149 ; 1925-0614 (2012)
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Training Statistical Machine Translation with Multivariate Mutual Information
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In: 5th Language and Technology Conference ; https://hal.archives-ouvertes.fr/hal-01272104 ; 5th Language and Technology Conference, Nov 2011, Poznan, Poland (2011)
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Mining monolingual and bilingual corpora
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In: ISSN: 1088-467X ; Intelligent Data Analysis ; https://hal.inria.fr/inria-00545493 ; Intelligent Data Analysis, IOS Press, 2010, 14 (6), pp.663-682 (2010)
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Roman impassible : der subversive und undogmatische Umgang mit Narration, Sprache, Realität und Zeit in den Romanen Jean-Philippe Toussaints und Patrick Devilles
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BLLDB
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UB Frankfurt Linguistik
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BLEU Evaluation of Machine-Translated English-Croatian Legislation
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In: http://www.lrec-conf.org/proceedings/lrec2012/pdf/233_Paper.pdf
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Metrics for MT evaluation: Evaluating reordering
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In: http://homepages.inf.ed.ac.uk/miles/papers/mt09.pdf
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Hindi Generation from Interlingua (UNL)
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In: http://www.cse.iitb.ac.in/~damani/papers/MTSummit07.pdf
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