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Arabic Software  Desktop Publishing  Machine Translation  Document Management  NLP   OCR  ASR  TTS  MultimediA




PlainBabel – Simultaneous Machine Translation

Until now machine speech-to-speech translation  was merely a vision for the future that wasn’t realizable with adequate quality. Pooling the years of experience from researchers at the Apache University of Technology and AppTek, Inc in Mclean, VA has managed to combine intelligent individual modules for speech recognition, translation and synthesis to create a system that realizes this vision.

With PlainBabel they have created a dialogue driven speech-to-speech translation
system that allows for a bilingual natural dialogue between two parties that don’t speak
each others language. The system can be used with different types of output devices
from an ISDN telephone to a 3G mobile phone.

The experts from AppTek use intelligent systems based on statistical methods for
speech recognition and translation. Unlike classical speech recognition and translation
systems they do not rely on narrowly defined rules and vocabularies, but rather the
system is trained with bilingual materials from the domain for which it will be deployed.
Depending on the scope and specification of the training materials, the system can
deliver a level of quality that was unattainable with previous systems. The statistical
approach minimizes the increase of errors combining speech recognition and machine
translation, allowing a speaker independent dialogue between two parties within a
defined domain. Communication is supported and guided by a dialogue management
system developed specifically for this purpose.

Figure 1: PlainBabel Server

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