Communications of the ACM
Open Mind Common Sense: Knowledge Acquisition from the General Public
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
ConceptNet — A Practical Commonsense Reasoning Tool-Kit
BT Technology Journal
Designing an aural comprehension aid for interlingual communication
IWIC'07 Proceedings of the 1st international conference on Intercultural collaboration
Parallel-text based support system for intercultural communication at medical receptions
IWIC'07 Proceedings of the 1st international conference on Intercultural collaboration
Using common sense to generate culturally contextualized machine translation
YIWCALA '10 Proceedings of the NAACL HLT 2010 Young Investigators Workshop on Computational Approaches to Languages of the Americas
HCII'11 Proceedings of the 14th international conference on Human-computer interaction: interaction techniques and environments - Volume Part II
Voice interfaces for real-time translation of common tourist conversation
Proceedings of the 10th Brazilian Symposium on on Human Factors in Computing Systems and the 5th Latin American Conference on Human-Computer Interaction
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Our Translation Assistant applies common sense logic to the problem of translating speech in real time from one language to another. Using speech recognition combined with a software translator to do word-by-word translation is not feasible because speech recognition is notorious for poor results. Word-by-word translation requires grammatically correct input to translate accurately. Therefore, translation of speech that is potentially already fraught with errors is not expected to be good. Our Translation Assistant works around these problems by using the context of the conversation as a basis for translation. It takes the location and the speaker as input to establish the circumstances. Then it uses a common sense knowledge network to do topic-spotting using key words from the conversation. It only translates the most likely topics of conversation into the target language. This system does not require perfect speech recognition, yet enables end-users to have a sense of the conversation.