MATI 2009 Conference: CAT Tools

2009 MATI Annual Conference

2009 MATI
Annual Conference
Dierk Seeburg
IcoText

1 (CC) Creative Commons. Some Rights Reserved September 12, 2009


Computer-Assisted
Translation Tools

Dierk Seeburg
IcoText
(Presentation available at icotext.com in a few days)

(CC) Creative Commons. Some Rights Reserved September 12, 2009


Agenda
• Intro • PM, TMS, L18n
• History • Terminology
• ITEs • MT
• Questions • Questions
• Break



Purpose

•Intro
•Overview (incomplete)
•Decision Guide



Dierk Seeburg
IcoText



Marburg



Dierk Seeburg
IcoText



Phoenix



Dierk Seeburg
IcoText



Survey

•Are you a freelance translator?



Survey

•Are you a freelance interpreter?



Survey

•Do you work for an LSP?



Survey

•Do you work in-house?



Glossary
•
G11n = Globalization
• I18n = Internationalization
• L10n = Localization
• T9n = Translation
• ITE = Integrated Translation Environment
• TMS = Translation Management System
• MTS = Machine Translation System
• WCMS = Web Content Management System
• GMS = Globalization Management System


Translators and Technology
• Translators & • 300,000
interpreters
worldwide
• Translators regularly • 30-35,000
using Internet

• Translators using • 10-15,000
translation memory
technology
Source: Jeff Allen


History
"Disdain on the side of the professional translators for the
hilarious and stupid MT mistakes gave birth to a new
variant of MT called translation memory (TM). TM started
off as a lower-level feature of commercial MT systems
(...). But the success of TM came with dedicated products
such as IBM TM/2 and Trados. The marketing message was
tuned in to what the professional translation industry
wanted to hear: "Forget about MT; it doesn't work well.
Instead, use our TM product because it leaves you in full
control of the process."
Jaap van der Meer in MultiLingual 71 (2005)



History
"The message worked well, within a period of 10 to 15
years, TM products have found their way to the
workstations of more than 50,000 translators in the
world. But the message had also caused a "cognitive
disorder" in the translation industry, namely that TM is
good and MT is evil, foregoing the fact that TM is just a
new variant of MT (...). The damage is done, however, and
it will take years to convince the community of business
translators that post-editing fuzzy matches from TM
databases is, in fact, not different from post-editing fuzzy
matches from any other MT system."
Jaap van der Meer in MultiLingual 71 (2005)


Development
• Market demands
• Higher effciencies
• Evolutionary approach:
– Letter
– FAX
– PC
– Internet
– Translation memory technology
• Spiral goes up: what's next?


Survey

•Do you have more than 1 year
experience?



Survey

•Do you have more than 5 years
experience?



Survey

experience?



Translation Process
• Transfer
• Conversion
• Import
• Pretranslation
• Translation
• Editing
• QA
• Terminology Management
• Back-Conversion/-Transfer


CAT Tools
•Computer Assisted Translation tools:
– All tools that aid in the translation
process



CAT Tools – Tool Cat's
• Integrated Translation Environments (ITEs)
• Translation Management System (TMS): GlobalSight, LTC Organiser,
Translation Offce 3000, Vertimus, ]project-open[
• Term extraction tools: Xerox XTS, LogiTerm, TermExtract,
SDLPhraseFinder, Okapi
• Aligners: AlignFactory, NoBabel AutoAligner
• Term Management tools: Bitext2tmx, Olifant
• Concordancers: AntConc, WebCONC, Lucon
• Word count tools: PractiCount, AnyCount
• Localization tools: Catalyst, Sisulizer, Lingobit
• Machine translation programs: Apertium, Moses, OpenLogos
• Lookup tools: europeana.eu, perseus.tufts.edu, dict.leo.org, dict.cc


Survey

•Have you used CAT Tools in the past?



Survey

•Are you currently using a CAT Tool?



Survey

•Are you planning on using a CAT Tool
in the future?



ITE Categories
•Tools with MS Word as their main
translation interface
•Tools with independent translation
interface
•Tools for translating online



Translation Memories
The 3 different technologies behind translation
memory:
•Reference-based matching on segment level
(Star Transit)
•Database-based matching on segment level
(most tools)
•Database-based matching on sub-segment
level (Multitrans, Logiterm, Find)


Obstacles: File Types
XLIFF, HTML/XHTML, XML, SGML, SVG, PDF, Plain Text,
OpenOffce, StarOffce, AbiWord, Corel WordPerfect,
CorelDraw, PO/POT (GNU Gettext), CSV, TSV, ASP,
PHP, Adobe FrameMaker (MIF), Adobe InDesign
(INX), Adobe PageMaker, Adobe Illustrator, Adobe
Photoshop, Interleaf /Quicksilver, XGate for
QuarkXPress, AutoCAD, DocBook, DITA, Java
Properties, JavaScript, RTF, Trados Tagged RTF,
Trados TTX, MS Offce 2003 XML, MS Offce 2007,
MS Visio, MS Publisher, ResX (Windows .NET
Resources), RC (Windows C/C++ Resources), TMX,
TBX, XLIFF, SRX, xml:tm, W3C ITS


Obstacles: Standards
• XLIFF • Orgs:
• TMX – ISO
• TBX – LISA
– OASIS
• SRX
– ATA
• xml:tm – FIT
• ITS – ITI



Obstacles: Other


Interoperability

User Interface

Integration



Strategies
•SWOT
•Six Questions
•See-Think-Draw
– Situation
– Goals
– Route



SWOT



SWOT
• Strengths: attributes of the organization that are
helpful to achieving the objective.
• Weaknesses: attributes of the organization that are
harmful to achieving the objective.
• Opportunities: external conditions that are helpful to
achieving the objective.
• Threats: external conditions which could do damage
to the business's performance.
Source: Wikipedia



Six Questions
•Who
•What
•Where
•When
•Why
•How



Tools with MS Word as their
main translation interface
• Anaphraseus (http://anaphraseus.sourceforge.net/)
• Anymem (http://www.anymem.com/)
• MetaTexis (http://www.metatexis.com)
• MultiTrans (http://www.multicorpora.com)
• Similis (http://www.lingua-et-machina.com)
• Snowball (http://www.trmem.com)
• TinyTM (http://tinytm.sourceforge.net/)
• Trados (http://www.trados.com)
• Wordfast (http://www.wordfast.net)
• WordFisher (http://www.wordfsher.com)



Anaphraseus



Anymem



MetaTexis



MultiTrans



Snowball



TinyTM



Trados



Wordfast



Wordfsher



Tools with independent
• Across (http://www.across.net)
• AppleTrans (http://www.apple.com/)
• Cafetran (http://www.cafetran.republika.pl/)
• Catalyst (http://www.alchemysoftware.ie/)
• Déjà Vu (http://www.atril.com/)
• Esperantilo (http://www.esperantilo.org/tm/index.html)
• ForeignDesk (http://www.foreigndesk.net/)
• Fusion (http://www.jivefusiontech.com/)
• Heartsome (http://www.heartsome.net/)
• Kbabel (http://kbabel.kde.org/)
• LogiTerm (http://www.terminotix.com/)


Across



AppleTrans



Cafetran



Catalyst



Déjà Vu



EsperantiloTM



ForeignDesk



Fusion



Heartsome



KBabel



LogiTerm



Tools with independent
• MemoQ (http://www.kilgray.com/)
• OmegaT (http://www.omegat.org/)
• Open Language Editor (http://open-language-tools.dev.java.net/)
• SDL Trados (http://www.sdlx.com/)
• Swordfsh (http://www.maxprograms.com/)
• Sisulizer (http://www.sisulizer.com/)
• Transit (http://www.star-transit.com/)
• Transolution (http://transolution.python-hosting.com/)
• Virtaal (http://translate.sourceforge.net/wiki/virtaal/index)
• WordForge (http://www.khmeros.info/drupal/?
q=en/download/Translation_Editor)


MemoQ



OmegaT



Open Language Tools



SDL Trados



Swordfsh



Transolution



Virtaal



Tools for translating online
•Lingotek (http://www.lingotek.com/)
•Logoport (http://www.lionbridge.com/)
•Pootle
(http://translate.sourceforge.net/wiki/po
otle/)



Break



ITE Features
•Leveraging translated content
•Building and maintaining terminology
databases
•Work in complex fle formats
•Methods for analysis
•Quality assurance
•Project management capabilities


ITEs – The Similarities
• Freely confgurable terminology component
• Unicode and TMX support (with caveats)
• Alignment features, e.g.
– AlignFactory
– NoBabel AutoAligner
• Similar range of supported fle formats (s. Wikipedia)
• Concordance searches
• Analysis features



ITEs – Differentiators
• Batch vs. individual fle processing
• Terminology handling
• Support for competing formats / TMs / termbases
• Support for co-workers
• Quality assurance
• Remote connectivity
• Code handling
• Support and Training



•Batch vs. individual fle processing

•Déjà Vu vs. Trados



•Terminology handling

•Transit vs. Déjà Vu vs. Wordfast



•Quality assurance

•Trados vs. MemoQ



•Remote connectivity

•Wordfast vs. Lingotek



•Support and Training

•Purchase = frst step only

•Compare to car maintenance



•Support and Training
– Tool Vendor Contract
– Consultant
– College classes
– ATA seminars
– Jost's Translators Toolkit
– Websites: translatorstraining.com,
proz.com, translatorscafe.com


Terminology – Prejudices
• TM tool = emphasis is on the translation memory ?
• More immediate gain: perfect and fuzzy matches
• TMs = easily built up by aligning existing translated
fle pairs/texts and/or automatically by translating
new texts
• Construction of terminology databases = tedious



Terminology – The Reality
• The terminology database = investment
– defning words and phrases
• Grammatically
• Contextually
• by contrast
• "Living dictionaries" for each segment translated
• Term entries contain meta data relevance
• Consistency throughout workgroups



Translation and Technology:
Machine Translation
•Statistically-based machine translation (SBMT)
•Rules-based machine translation (RBMT)
•Example-based machine translation (EBMT)
•Human-assisted machine translation (HAMT)
•Hybrid machine translation (HMT)



Translation and Technology:
Machine Translation
• Statistically-based machine translation works (sort of)
• Rules-based approach does not work on its own
• Translation can only be evaluated by its effectiveness, not by
some elusive goal of "perfection"
• Amount of relevant data can not be translated by humans
• Microsoft
• Symantec
• Systran
• AppTek
• Promt
• Google


Survey

•Are you planning on using an ITE in
the future?



Survey

•Are you planning on using a TMS in
the future?



Survey

•Are you planning on using a GMS in
the future?



Survey

•Are you planning on using an MTS in
the future?



Trends
• Consolidation
• Machine Translation (SMT, RBMT, EBMT, HAMT)
• Standards (XLIFF, TMX, TBX, SRX)
• Translation Management (CMS, GMS)
• Groups (Yahoo, Google, LinkedIn)
• Blogs (LTD, ThoughtsOnT9n, Masked T9r)
• Translators Sites (ProZ, Translators Cafe, Aquarius)
• Social Sites (Ning, Facebook, Twitter)
• Instant Messaging (SMS, Skype, GTalk)


Trends
• Desktop to Server
• Server to Web
• Web to Mobile
• Pretranslation
• Sub-sentence Fuzzy Matching
• UX = User Experience
• Integration
• Collaboration
• Open Source


Survey

•Have you attended the ATA
Translation Tools Forum in the past?



Survey

•Are you planning on attending the
ATA Translation Tools Forum in the
future?



Take-Home

•Don't buy a golden hammer
•Subscribe to LTD News



Take-Home



Acknowledgements

Jost Zetzsche, Rosalie Wells
Di Wu & MATI
ATA Prof'l. Dev. Committee
ATA LT Division
ATA staff, volunteers
You


Thank you!
See you in New York in October!
Download slides at <icotext.com>.



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