21 |
INFODENS: An Open-source Framework for Learning Text Representations ...
|
|
|
|
BASE
|
|
Show details
|
|
22 |
Query Translation for Cross-lingual Search in the Academic Search Engine PubPsych ...
|
|
|
|
BASE
|
|
Show details
|
|
23 |
Query Translation for Cross-lingual Search in the Academic Search Engine PubPsych ...
|
|
|
|
BASE
|
|
Show details
|
|
24 |
A Hybrid Machine Translation Framework for an Improved Translation Workflow
|
|
Pal, Santanu. - : Saarländische Universitäts- und Landesbibliothek, 2018
|
|
BASE
|
|
Show details
|
|
30 |
Massively Multilingual Neural Grapheme-to-Phoneme Conversion ...
|
|
|
|
BASE
|
|
Show details
|
|
31 |
An Empirical Analysis of NMT-Derived Interlingual Embeddings and their Use in Parallel Sentence Identification ...
|
|
|
|
BASE
|
|
Show details
|
|
32 |
Predicting the Law Area and Decisions of French Supreme Court Cases ...
|
|
|
|
BASE
|
|
Show details
|
|
33 |
Pluricentric languages : automatic identification and linguistic variation ; Plurizentrische Sprachen : automatische Spracherkennung und linguistische Variation
|
|
|
|
BASE
|
|
Show details
|
|
34 |
Improving translation memory matching and retrieval using paraphrases
|
|
|
|
In: 30 ; 1 ; 19 ; 40 (2016)
|
|
BASE
|
|
Show details
|
|
35 |
A Minimally Supervised Approach for Synonym Extraction with Word Embeddings
|
|
|
|
In: Prague Bulletin of Mathematical Linguistics , Vol 105, Iss 1, Pp 111-142 (2016) (2016)
|
|
BASE
|
|
Show details
|
|
36 |
Statistical post-editing and quality estimation for machine translation systems
|
|
|
|
In: Béchara, Hanna (2014) Statistical post-editing and quality estimation for machine translation systems. Master of Science thesis, Dublin City University. (2014)
|
|
BASE
|
|
Show details
|
|
37 |
Predicting sentence translation quality using extrinsic and language independent features
|
|
|
|
In: Bicici, Ergun, Groves, Declan and van Genabith, Josef orcid:0000-0003-1322-7944 (2013) Predicting sentence translation quality using extrinsic and language independent features. Machine Translation, 27 (3-4). pp. 171-192. ISSN 0922-6567 (2013)
|
|
BASE
|
|
Show details
|
|
38 |
Working with a small dataset - semi-supervised dependency parsing for Irish
|
|
|
|
In: Lynn, Teresa, Foster, Jennifer orcid:0000-0002-7789-4853 , Dras, Mark orcid:0000-0001-9908-7182 and van Genabith, Josef orcid:0000-0003-1322-7944 (2013) Working with a small dataset - semi-supervised dependency parsing for Irish. In: Fourth Workshop on Statistical Parsing of Morphologically Rich Languages, 18 Oct 2013, Seattle, WA. USA. (2013)
|
|
BASE
|
|
Show details
|
|
39 |
Computer assisted (language) learning (CA(L)L) for the inclusive classroom
|
|
Greene, Cara N.. - : Dublin City University. Centre for Next Generation Localisation (CNGL), 2013. : Dublin City University. National Centre for Language Technology (NCLT), 2013. : Dublin City University. School of Computing, 2013
|
|
In: Greene, Cara N. (2013) Computer assisted (language) learning (CA(L)L) for the inclusive classroom. PhD thesis, Dublin City University. (2013)
|
|
BASE
|
|
Show details
|
|
40 |
Domain adaptation for statistical machine translation of corporate and user-generated content
|
|
|
|
In: Banerjee, Pratyush (2013) Domain adaptation for statistical machine translation of corporate and user-generated content. PhD thesis, Dublin City University. (2013)
|
|
Abstract:
The growing popularity of Statistical Machine Translation (SMT) techniques in recent years has led to the development of multiple domain-specic resources and adaptation scenarios. In this thesis we address two important and industrially relevant adaptation scenarios, each suited to different kinds of content. Initially focussing on professionally edited `enterprise-quality' corporate content, we address a specic scenario of data translation from a mixture of different domains where, for each of them domain-specific data is available. We utilise an automatic classifier to combine multiple domain-specific models and empirically show that such a configuration results in better translation quality compared to both traditional and state-of-the-art techniques for handling mixed domain translation. In the second phase of our research we shift our focus to the translation of possibly `noisy' user-generated content in web-forums created around products and services of a multinational company. Using professionally edited translation memory (TM) data for training, we use different normalisation and data selection techniques to adapt SMT models to noisy forum content. In this scenario, we also study the effect of mixture adaptation using a combination of in-domain and out-of-domain data at different component levels of an SMT system. Finally we focus on the task of optimal supplementary training data selection from out-of-domain corpora using a novel incremental model merging mechanism to adapt TM-based models to improve forum-content translation quality.
|
|
Keyword:
Computational linguistics; Machine learning; Machine translating; SMT; Statistical Machine Translation
|
|
URL: http://doras.dcu.ie/17722/
|
|
BASE
|
|
Hide details
|
|
|
|