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Project

Using Common-Sense Reasoning to Improve Voice Recognition

Current voice-recognition software relies on statistical techniques to determine which words a user has said. This project attempts to leverage the semantic context of what the user has said previously to improve future predictions. We are using OMCSNet, a semantic network created from the Open Mind Common Sense knowledge base, to disambiguate phonetically similar words and improve overall recognition accuracy.