539 research outputs found
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MSTperl parser
No full textMSTperl is a Perl reimplementation of the MST parser of Ryan McDonald, with several additional advanced functions, such as support for parallel features
Depfix, a Tool for Automatic Rule-based Post-editing of SMT
No full textWe present Depfix, an open-source system for automatic post-editing of phrase-based machine translation outputs. Depfix employs a range of natural language processing tools to obtain analyses of the input sentences, and uses a set of rules to correct common or serious errors in machine translation outputs. Depfix is currently implemented only for English-to-Czech translation direction, but extending it to other languages is planned
Parsing under-resourced languages: Cross-lingual transfer strategies for Indian languages
No full textKey to fast adaptation of language technologies for any language hinges on the availability of fundamental tools and resources such as monolingual/parallel corpora, annotated corpora, part-of-speech (POS) taggers, parsers and so on. The languages which lack those fundamental resources are often referred as under-resourced
languages.
In this thesis, we address the problem of cross-lingual dependency parsing of under-resourced languages. We apply three methodologies to induce dependency structures: (i) projecting dependencies from a resource-rich language to under-resourced languages via parallel corpus word alignment links (ii) parsing under-
resourced languages using parsers whose models are trained on treebanks of other
languages, and do not look at actual word forms, but only on POS categories. Here
we address the problem of incompatibilities in annotation styles between source side parsers and target side evaluation treebanks by harmonizing annotations to a common standard; and finally (iii) we add a new under-resourced scenario in which we use machine translated parallel corpora instead of human translated corpora for
projecting dependencies to under-resourced languages.
We apply the aforementioned methodologies to five Indian languages (ILs): Hindi, Urdu, Telugu, Bengali and Tamil (in the order of high to low availability of treebank data). To make the evaluation possible for Tamil, we develop a depen
dency treebank resource for Tamil from scratch and we use the created data in
evaluation and as a source in parsing other ILs. Finally, we list out strategies that
can be used to obtain dependency structures for target languages under different
resource-poor scenarios
A corpus-based finite-state morphological toolkit for contemporary Arabic
No full textWe develop an open-source large-scale finite-state morphological processing toolkit (AraComLex) for Modern StandardArabic (MSA) distributed under the GPLv3 license (http://aracomlex.sourceforge.net). The morphological transducer is based on a lexical database specifically constructed for this purpose. In contrast to previous resources, the database is tuned to MSA, eliminating lexical entries no longer attested in contemporary use. The database is built using a corpus of 1,089,111,204 word tokens, a pre-annotation tool, machine learning techniques and knowledge-based pattern matching to automatically acquire lexical knowledge. Our morphological transducer is evaluated and compared to LDC’s SAMA(StandardArabic Morphological Analyser). We also develop a finite-state morphological guesser as part of a methodology for extracting unknown word forms, lemmatizing them, and giving them a priority weight for inclusion in the lexicon
Khresmoi - multilingual semantic search of medical text and images
No full textThe Khresmoi project is developing a multilingual multimodal search and access system for medical and health information and documents. This scientific demonstration presents the current state of the Khresmoi integrated system, which includes components for text and image annotation, semantic search, search by image similarity and machine translation. The flexibility in adapting the system to varying requirements for different types of medical information search is demonstrated through two instantiations of the system, one aimed at medical professionals in general and the second aimed at radiologists. The key innovations of the Khresmoi system are the integration of multiple software components in a flexible scalable medical search system, the use of annotation cycles including manual correction to improve semantic search, and the possibility to do large scale visual similarity search on 2D and 3D (CT, MR) medical images
MTMonkey 1.0
No full textMTMonkey is a web service which handles and distributes JSON-encoded HTTP requests for machine translation (MT) among multiple machines running an MT system, including text pre- and post processing.
It consists of an application server and remote workers which handle text processing and communicate translation requests to MT systems. The communication between the application server and the workers is based on the XML-RPC protocol
Jak překladač z Matfyzu porazil Google
No full textA popularizing description of Chimera, our MT system, for HNFuture, the scientific supplement of the online journal iHNed
Scratching the Surface of Possible Translations
No full textOne of the key obstacles in automatic evaluation of machine translation systems is the reliance on a few (typically just one) human-made reference translations to which the system output is compared. We propose a method of capturing millions of possible translations and implement a tool for translators to specify them using a compact representation. We evaluate this new type of reference set by edit distance and correlation to human judgements of translation quality
TamilTB - Tamil Dependency Treebank 1.0
No full textTamilTB 1.0 improves over the very first release of the Tamil dependency treebank (TamilTB v0.1). The current version introduces many improvements over the orthography and morphological tagset of the data. Now, the primary data representation of the treebank uses UTF-8 encoding
Results of the WMT13 Metrics Shared Task
Get PDFThis paper presents the results of the WMT13 Metrics Shared Task. We asked participants of this task to score the outputs of the MT systems involved in WMT13 Shared Translation Task. We collected scores of 16 metrics from 8 research groups. In addition to that we computed scores of 5 standard metrics such as BLEU, WER, PER as baselines. Collected scores were evaluated in terms of system level correlation (how well each metric’s scores correlate with WMT13 official human scores) and in terms of segment level correlation (how often a metric agrees with humans in comparing two translations of a particular sentence)