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| [October 23, 2008] |
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AppTek Chief Scientist to Present at AMTA 2008 Conference
--(Business Wire)-- AppTek announces:
WHAT:
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During the Eighth Conference of the Association for Machine
Translation in the Americas (AMTA), AppTek Chief Scientist
Hassan Sawaf, Ph.D., will discuss best practices for
implementing Hybrid Machine Translation to improve media
monitoring translations in fluency, context and accuracy. His
presentation entitled, "Hybrid Machine Translation Applied to
Media Monitoring," will outline how a Hybrid Machine
Translation approach delivers better results than a pure rule-
based and a pure corpus-based approach for both written and
spoken input. This presentation will also demonstrate how to
increase language model quality for dialect language speech
recognition by using non-dialect, non-spontaneous language
resources.
WHO:
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Hassan Sawaf has over 10 years experience in the areas of
Natural Language Processing, Machine Translation and Speech
Recognition. He was project manager for Daimler Benz in
Germany, senior researcher at the University of Aachen, where
he did his graduate studies for his Diploma (1992-1998) and
Ph.D. (1998-2003), and currently heads Research & Development
for AppTek. Under his guidance as the head of R&D, AppTek
recently introduced the first hybrid machine translation
system that fully integrated two complete machine translation
systems (statistical and rule-based) into one system that
provides the performance and benefits of both approaches. His
group also led the development of numerous automated speech
recognition engines, which have been integrated into AppTek's
numerous media monitoring systems.
WHERE:
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Hilton Prince Kuhio Hotel
Waikiki, Hawaii
http://www.amtaweb.org/AMTA2008.html
WHEN:
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Friday, October 24, 2008
2:00 - 2:30pm
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. For more information please visit www.apptek.com.
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