Free/Open-Source Machine Translation: a three-day tutorial ... - CNGL

(a) Description
• Background (interNOSTRUM, Universia)
• Rationale
• Apertium as a shallow-transfer machine translation platform:
engine, data, tools (Armentano et al. 2006).
• Language-pair data
• Funding
• The Apertium community as an example of FOSS development
(repositories: the trunk, the incubator; roles).
• Apertium tools: apertium-dixtools, apertium-transfertools,
apertium-tagger-training-tools.
• Apertium-based applications (Tinylex, Wordpress plugin,
Pidgin plugin, OpenOffice.org plugins, etc.)
• Apertium as a research platform (Sánchez-Martínez and
Forcada 2007, Sánchez-Martínez et al. 2008).
(b) Laboratory: installing and modifying Apertium
• Installing Apertium from the latest sources on a virtual
Linux machine.
• Changing the data for a language pair: vocabularies and,
optionally, transfer rules.
4. Corpus-based FOSMT: Moses (*)
(a) Statistical machine translation
• Statistical MT (SMT)
• The data: sentence-aligned corpora.
• Training: the statistical models
• The SMT engine or “decoder”
(b) Description of Moses and related software:
• Training: Giza++
• Language models: irstlm
• Tuning: MERT
• Decoding: Moses
(c) Laboratory: installing and running Moses.
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