Set of Hidden Markov Models to recognize words communicated using the American Sign Language
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Updated
Apr 25, 2017 - HTML
Set of Hidden Markov Models to recognize words communicated using the American Sign Language
In this project, I built a system that can recognize words communicated using the American Sign Language (ASL). I was provided a preprocessed dataset of tracked hand and nose positions extracted from video. My goal was to train a set of Hidden Markov Models (HMMs) using part of this dataset to try and identify individual words from test sequences.
Machine Learning based Personal Voice Assisstant and text independent (Development phase)
Machine Learning based Personal Voice Assisstant and text independent (Development phase)
Udacity AI Nanodegree's Project for a Sign Language Recognizer. This project demonstrates the power of probabalistic models and employs hidden Markov models (HMM's) to analyze a series of measurements taken from videos of American Sign Language (ASL).
Algorithms used in Natural Language Processing
an artificial intelligence project to recognize american sign language
Sign Language Recognizer
Projects from Udacity's Artificial Intelligence Nanodegree (August 2017 cohort) - TERM 1.
American Sign Language Recognizer using Hidden Markov Model
A system that can recognize words communicated using the American Sign Language (ASL)
The overall goal of this project is to build a word recognizer for American Sign Language video sequences, demonstrating the power of probabilistic models.
Sign Language Recognition System based on Hidden Markov Models (HMM)
Build a sign language recognition system using Hidden Markov Models
Getting started with Data science Numerical Analysis and Scientific Computing
A demo for simple isolated Chinese speech word recognition using GMMHMM in Python
My solutions to the projects assigned for the Udacity Artificial Intelligence Nanodegree
Discrete Hidden Markov Model (HMM) Implementation in C++
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