| 1. |
- Caprotti, Olga, 1964, et al.
(författare)
-
High-quality translation: Molto tools and applications
- 2012
-
Ingår i: The fourth Swedish Language Technology Conference (SLTC).
-
Konferensbidrag (refereegranskat)abstract
- MOLTO (Multilingual On Line Translation, FP7-ICT-247914, www.molto-project.eu) is a European project focusing on translation on the web. MOLTO targets translation that has production quality, that is, usable for quick and reliable dissemination of information. MOLTO’s main focus is to increase the productivity of such translation systems, building on the technology of GF (Grammatical Framework) and its Resource Grammar Library. But MOLTO also develops hybrid methods which increase the quality of Statistical Machine Translation (SMT) by adding linguistic information, or bootstrap grammatical models from statistical models. This paper gives a brief overview of MOLTO’s latest achievements, many of which are more thoroughly described in separate papers and available as web-based demos and as open-source software.
|
|
| 2. |
- Prasad, K V S, 1952, et al.
(författare)
-
Computational evidence that Hindi and Urdu share a grammar but not the lexicon
- 2012
-
Ingår i: 3rd Workshop on South and Southeast Asian Natural Language Processing (SANLP)", collocated with COLING 12.
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Hindi and Urdu share a grammar and a basic vocabulary, but are often mutually unintelligible because they use different words in higher registers and sometimes even in quite ordinary situations. We report computational translation evidence of this unusual relationship (it differs from the usual pattern, that related languages share the advanced vocabulary and differ in the basics). We took a GF resource grammar for Urdu and adapted it mechanically for Hindi, changing essentially only the script (Urdu is written in Perso-Arabic, and Hindi in Devanagari) and the lexicon where needed. In evaluation, the Urdu grammar and its Hindi twin either both correctly translated an English sentence, or failed in exactly the same grammatical way, thus confirming computationally that Hindi andUrdu share a grammar. But the evaluation also found that the Hindi and Urdu lexicons differed in 18% of the basic words, in 31% of tourist phrases, and in 92% of school mathematics terms.
|
|
| 3. |
- Virk, Shafqat, 1979, et al.
(författare)
-
Developing an interlingual translation lexicon using WordNets and Grammatical Framework
- 2014
-
Ingår i: Proceedings of the Fifth Workshop on South and Southeast Asian Natural Language Processing. - 9781873769416
-
Konferensbidrag (refereegranskat)abstract
- The Grammatical Framework (GF) offers perfect translation between controlled subsets of natural languages. E.g., an abstract syntax for a set of sentences in school mathematics is the interlingua between the corresponding sentences in English and Hindi, say. GF “resource grammars” specify how to say something in English or Hindi; these are reused with “application grammars” that specify what can be said (mathematics, tourist phrases, etc.). More recent robust parsing and parse-tree disambiguation allow GF to parse arbitrary English text. We report here an experiment to linearise the resulting tree directly to other languages (e.g. Hindi, German, etc.), i.e., we use a language independent resource grammar as the interlingua. We focus particularly on the last part of the translation system, the interlingual lexicon and word sense disambiguation (WSD). We improved the quality of the wide coverage interlingual translation lexicon by using the Princeton and Universal WordNet data. We then integrated an existing WSD tool and replaced the usual GF style lexicons, which give one target word per source word, by the WordNet based lexicons. These new lexicons and WSD improve the quality of translation in most cases, as we show by examples. Both WordNets and WSD in general are well known, but this is the first use of these tools with GF.
|
|
