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Using Commonsense Reasoning to Improve Voice Recognition

Integrating Microsoft Speech API with ConceptNet, our prototype aims to enhance voice recognition by disambiguating similar words, improving error correction, and boosting overall accuracy. The system intelligently analyzes context to refine recognition.

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Using Commonsense Reasoning to Improve Voice Recognition

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  1. Using Commonsense Reasoning to Improve Voice Recognition

  2. Speech Recognition By integrating the Microsoft Speech API and ConceptNet, we hope to: • Disambiguate phonetically similar words • Improve errorcorrection interfaces • Improve overall recognition accuracy

  3. Speech Recognition Here is how our prototype is going to work: I was at the school the other day. I walked up to the (text being dictated appears here)

  4. principal Speech Recognition User Speaks: I was at the school the other day. I walked up to the

  5. Voice recognition engine suggestions Speech Recognition Speech is Processed: I was at the school the other day. I walked up to the principle principal the principle of of the principal

  6. Words in ConceptNet for “school” Speech Recognition The Context is analyzed using ConceptNet I was at the school the other day. I walked up to the principle principal the principle of of the principal chalkboard textbook teacher principal

  7. The voice recognition input is intelligently sorted by how much each word makes sense, contextually Speech Recognition Options are calculated and ranked: I was at the school the other day. I walked up to the principal principal principle the principle of of the principal principle principal the principle of of the principal chalkboard textbook teacher principal

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