If you can measure it, consider it predicted
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Updated
Jun 20, 2024 - Jupyter Notebook
If you can measure it, consider it predicted
A demo for simple isolated Chinese speech word recognition using GMMHMM in Python
Discrete Hidden Markov Model (HMM) Implementation in C++
Set of Hidden Markov Models to recognize words communicated using the American Sign Language
The overall goal of this project is to build a word recognizer for American Sign Language video sequences, demonstrating the power of probabilistic models.
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.
Sign Language Recognition System based on Hidden Markov Models (HMM)
Machine Learning based Personal Voice Assisstant and text independent (Development phase)
Sign Language Recognizer
Projects from Udacity's Artificial Intelligence Nanodegree (August 2017 cohort) - TERM 1.
Machine Learning on Images and Audio
Build a sign language recognition system using Hidden Markov Models
Machine Learning based Personal Voice Assisstant and text independent (Development phase)
Getting started with Data science Numerical Analysis and Scientific Computing
Intelligent system for pattern recognition: image, signal and text processing with deep learning and generative learning models.
Code used to generate results for my thesis comparing Hidden Markov Models and Dynamic Time Warping as time series classification tools.
Algorithms used in Natural Language Processing
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