JJEM: Special Edition 2 (December 2024)
JJEM: Special Edition 2 (December 2024)
2024-12-08
"Efficient technique for Gesture speak using AI to break through communication barrier's".
Pavithra TV , Sampath Kumar.
The increasing demand for enabling devices significantly improving the everyday living people with mobility impairments has led to major advances in gesture recognize operation. Paralysis patients is condition over completely or partially lost. The individual has condition find it difficult to move somewhere and perform an any actions. In this paper to use a popular method for helping disabilities persons. they using camera for capturing the images or using an existing dataset. These systems use machine learning technology to interpret actions and transform into voice commands, allowing users to effectively control devices. Generate data before processing, including noise filtering, signal segmentation, and feature extraction to capture the properties of signals, features are extract- ed using various machine learning techniques including support vector machine (SVM), random forests, convolutional neural networks (CNN), and long-term memory networks (LSTM), to build powerful classifiers that can learn about movements. This investigates a new non- invasive way to measure movement in stroke patients using computer vision and machine learning without the need for physical sensors.
Image Processing, Hand gesture, Training, Testing, Machine learning, Convolutional Neural network (CNN), Text to voice, Human computer interaction interface, Artificial intelligence.