NIST MT 08 Tests Show AppTek’s Strong
Performance
MCLEAN, VA – June 10, 2008 – AppTek, a leader in human language
technology (HLT), was the top performer in NIST’s Meteor evaluation and
one of the top three performers in this year’s NIST MT evaluations. Both impartial evaluations cover the global
machine translation to evaluate technologies from industry, government, and
academia and measure their performance.
As in NIST MT 06, AppTek scored very high with the participation of more
than 30 MT organizations.
Using a truly hybrid machine translation system, combining a
complete statistical and a complete rule-based system, AppTek participated in
these evaluations and, again, proved the strength of its complete approach to
translation both structured and unstructured (a.k.a. noisy) textual data. The Hybrid Machine Translation system tested,
TranSphere HMT, uses its rich rule-based engine to augment & enhance its
statistical MT platform and elevates the state-of-the-art in machine
translation.
NIST has published the results on their
website (www.nist.gov). NIST conducts these evaluations in order to support
machine translation (MT) research and help advance the state of the art in MT
technology, rather than as a competition. As such, the results are not to be
construed or represented as endorsements of any participant's system or
commercial product, or taken as official findings on the part of NIST or the
ABOUT APPTEK
AppTek is a developer of human language technology products
with a complete suite for text and speech (voice) processing and recognition.
The Company also leads major research and development efforts to
further the advancement in the field of developing better methods and
technologies in the field of HLT. AppTek's product
offerings include machine translation (MT) and automatic speech
recognition (ASR) for a growing list of more than 23 languages;
multilingual information retrieval with query and topic search
capabilities; name-finding applications; and integrated suites providing
automatic speech recognition and machine translation in media monitoring of
broadcast and telephony speech as well as handheld and wearable
speech-to-speech translation devices.
CONTACT:
Mike Veronis
(703) 394-2317
