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Sign Language Recognizer

Part of the Artificial Intelligence Nanodegree Program.

Built a system that can recognize words communicated using the American Sign Language (ASL). Trained a set of Hidden Markov Models (HMMs) using part of a preprocessed dataset of tracked hand and nose positions extracted from video to try and identify individual words from test sequences. Experimented with model selection techniques including BIC, DIC, and K-fold Cross Validation.

  • Probabilistic Graphical Models
  • Model Selection

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