Translation Memory systems
Technology in the service of the translation professional
Elina Lagoudaki
Mark Shuttleworth
Imperial College London

Translation Memory (TM) system: a definition
Computer application that allows the
user to store previous translations along
with their originals in a database (or
index) and to re-use them in new
translation projects, when similar source
text is encountered

How does it work?
• Initially, the program splits the pair of texts (original +
translation) into segments (=units, e.g. sentences, phrases or
words) and then it aligns them (a pair of aligned segments is
what we often call a ‘translation unit’)
• It then stores and indexes the translation units in a database (or
index) in an organised way with a variety of information attached
• When the user starts a new translation which has some source
segments identical or similar to the ones existing in the database,
the system recognises them and retrieves the past translation for
those segments and suggests them to the user

Types of matching
• Exact (100%) match
Example of a source segment: “Every employee is expected to act in
accordance with the Business Principles.”
TU that exists in the database: EN(UK) “Every employee is expected to act in
accordance with the Business Principles” - IT (IT) “Ogni dipendente è tenuto
ad agire in conformità ai Principi commerciali”
• Fuzzy match
Example of a source segment: “Key milestones in the development of our
company can be found in the following section.”
TU that exists in the database: EN (UK) “Key milestones in the development
of Intracom can be found in the following sections.” IT (IT) “I punti salienti
della storia di Intracom sono delineati nelle seguenti sezioni.”

Context of use
• Scenario 1: new translation projects bearing
similarities (in terms and/or expressions) with
previous translations - texts with a great amount of
terminology repeating throughout the document
• Scenario 2: large project done simultaneously by
several translators (problem with terminology
consistency)
• Scenario 3: updated (revised) documents
• Scenario 4: translation of websites, desktop publishing
files and software (localisation)

Ideal text type candidates for TM use

Ideal text type candidates for TM use
✓ Repetitive text: technical (e.g. manuals, technical documentation),
financial, legal

Ideal text type candidates for TM use
✓ Repetitive text: technical (e.g. manuals, technical documentation),
financial, legal
✓ Websites (HTML, XML files)

Ideal text type candidates for TM use
✓ Repetitive text: technical (e.g. manuals, technical documentation),
financial, legal
✓ Websites (HTML, XML files)
✓ Software (Java properties, Windows resource files, etc.)

Ideal text type candidates for TM use
✓ Repetitive text: technical (e.g. manuals, technical documentation),
financial, legal
✓ Websites (HTML, XML files)
✓ Software (Java properties, Windows resource files, etc.)
✓ Text contained in complex formats (such as DTP files: FrameMaker,
Illustrator, Interleaf, Pagemaker, etc.)

Ideal text type candidates for TM use
✓ Repetitive text: technical (e.g. manuals, technical documentation),
financial, legal
✓ Websites (HTML, XML files)
✓ Software (Java properties, Windows resource files, etc.)
✓ Text contained in complex formats (such as DTP files: FrameMaker,
Illustrator, Interleaf, Pagemaker, etc.)
NOT SUITABLE for:

Ideal text type candidates for TM use
✓ Repetitive text: technical (e.g. manuals, technical documentation),
financial, legal
✓ Websites (HTML, XML files)
✓ Software (Java properties, Windows resource files, etc.)
✓ Text contained in complex formats (such as DTP files: FrameMaker,
Illustrator, Interleaf, Pagemaker, etc.)
NOT SUITABLE for:
• Literary texts

Ideal text type candidates for TM use
✓ Repetitive text: technical (e.g. manuals, technical documentation),
financial, legal
✓ Websites (HTML, XML files)
✓ Software (Java properties, Windows resource files, etc.)
✓ Text contained in complex formats (such as DTP files: FrameMaker,
Illustrator, Interleaf, Pagemaker, etc.)
NOT SUITABLE for:
• Literary texts
• Short texts (one paragraph document, slogans, etc.)

Ideal text type candidates for TM use
✓ Repetitive text: technical (e.g. manuals, technical documentation),
financial, legal
✓ Websites (HTML, XML files)
✓ Software (Java properties, Windows resource files, etc.)
✓ Text contained in complex formats (such as DTP files: FrameMaker,
Illustrator, Interleaf, Pagemaker, etc.)
NOT SUITABLE for:
• Literary texts
• Short texts (one paragraph document, slogans, etc.)
• One-off projects / small volume of translation work

Benefits deriving from the use of TM systems
enjoy increased productivity
★
access and reuse ideas from previous translations
★
never translate the same sentence twice (time and
★
effort savings)
consistency in terminology
★
uniformity in style
★
improvement in the quality of translation
★

TM systems: Facts & Misconceptions
✓ Stores/references each segment with its translation (translation units) in
the TM database/index.
✓ Looks up each new segment to find a matching one and offers
translations made for the same or similar segments.
✓ Connects to a terminology database for automatic term look-up.
✓ The bigger the TM database gets the more valuable it becomes.
• TM systems differ from Machine Translation (MT) systems. TMs do not
replace the translator.
• The TM database is initially empty, the translators have to fill it
themselves.
• TM systems are not limited to a specific language pair like MT systems, a
Translation Memory can be used for any pair of languages.

Overview of TM systems
Approx. 30 different TM systems currently available on the market!
Some of them are:
• Déjà Vu
• WordFast
• SDL TRADOS
• MultiTrans
• Omega-T
• TrAID

Differences between TM systems
In terms of design (user interface):
• some TM tools are integrated into MS Word (as add-
ins)
• others offer their own text processing environment
(usually in a tabular way)

TRADOS

Heartsome Translation Suite: XLIFF Translation Editor

Differences between TM systems
In terms of technology implemented:
• granularity of segmentation (at sentence, phrase, or
word level)
• indexing method (indexing of segments vs. full-text
indexing)
• match retrieval techniques (structure-based vs. content
based)

Importance of TM systems

Importance of TM systems
• New socio-economic conditions instigated by globalisation
• high demand for multilingual documentation
• growing demand for translations from the life sciences industry
• the translation industry is required to cope with larger volumes of
translation work, faster turnaround, and a great variety of text
formats
• The deployment of technology seems to be the only way to address the
new challenges
• Growing interest and investment in the development of new tools and
the improvement of existing ones

Focus of current research
• User-friendlier TM tools
• Expansion of the scope of use of a TM tool
• Functionality expansion
• Enhancement of access to linguistic resources via a unified TM
platform
• Optimised leveraging of previously translated content –
improved fuzzy matching
• Standardisation & efficient exchange of TM resources

Latest developments in TM research 1/4
• Challenge: ability to have some context
for the proposed match
• Solution provided by the full-text
approach and the alignment of source
and target documents at the paragraph
level (examples: MultiTrans, LogiTrans,
Lingotek)

Latest developments in TM research 2/4
• Challenge: improve match recall (find
ALL matches available in the TM for our
source segment)
• Solution developed: structure-based
technique which uses character string
matching algorithms to look for a match
not only in segments but also in sub-
parts of the segments (example: DéjàVu
X)

Latest developments in TM research 3/4
• Challenge: improve match precision (find the
CORRECT match for our source segment)
• Solution developed: content-based matching
techniques - each segment is annotated with
grammatical information and constitutes a ‘translation
pattern’ - matches are sought by a deep-structure
pattern recognition method which looks beyond the
surface appearance of segments (Masterin)

Latest developments in TM research 4/4
• Challenge: What can the system offer if it cannot find any exact or fuzzy
match in its database?
• Solution developed: implementation of Machine Translation techniques
• if, for a source segment, the system finds two sub-segments that exist
in two different segments stored in the TM database, it uses Example-
Based Machine Translation techniques to put together the two sub-
segments to form a new suggested match (DéjàVu X)
• the system constructs and suggests a fuzzy match from the available
resources in the database (such as a lexicon) by applying translation
heuristics (Masterin)

Current trends in TM research
Functionality optimization & expansion
• Optimizing interoperability (pressure to adopt the TMX and SRX
standards to facilitate the exchange of resources between different TM
systems)
• Expanding the scope of use: assist in the translation of general texts as
well as technical texts (a system that relies less on repetition and more on
the linguistic resources it contains)
• Integrating TM modules into Content Management Systems

Future directions in TM research
Enhanced access to linguistic resources & deployment
• Provision of tools which integrate linguistic resources (such as bilingual
corpora - parallel or aligned, glossaries, dictionaries - online or on CD-
ROMs) in the TM database efficiently, easily, quickly and on a large scale
• Development of language resources (glossaries, dictionaries) as add-ins
that will be sold along with the TM application
• Optimization of the deployment of acquired resources (improve
algorithms for search and retrieval of matches => more relevant results,
quicker + with useful linguistic information)
• Exploitation of the Web as a source of bilingual (or monolingual) corpora

Technology should not lead us!
Translators shouldn’t be afraid of
technology, but keep an open mind and
seek to be informed about these systems;
there are solutions available that can
take care of the grunt work and, thus, let
the translator focus on the creative part
of translation.