Revolutionizing Vehicle Autonomous Control: NLP-Powered Voice Command System
Disciplines
Artificial Intelligence and Robotics | Computer Sciences
Abstract (300 words maximum)
The fusion of Natural Language Processing (NLP) and voice control systems has revolutionized human-machine interactions. This project focuses on the system interpretation of the commands from drivers and passengers, enhancing safety and convenience. The process begins with a diverse voice dataset of vehicular commands. Data preprocessing, noise reduction, and feature extraction convert raw voice data into a trainable format. An Automatic Speech Recognition (ASR) model ensures precise voice recognition, while advanced NLP techniques decode the intent of voice commands. The system understands nuanced requests like “turn on the headlights” or “Change gear to D2.” This project uses pre-existing voice datasets, promising safer and more intuitive driving experiences. As the system matures, it paves the way to autonomous driving. Leveraging existing voice datasets, this innovative project enhances driving safety and convenience, laying the groundwork for the future of autonomous vehicles.
Academic department under which the project should be listed
CCSE - Computer Science
Primary Investigator (PI) Name
Md Abdullah Al Hafiz Khan
Revolutionizing Vehicle Autonomous Control: NLP-Powered Voice Command System
The fusion of Natural Language Processing (NLP) and voice control systems has revolutionized human-machine interactions. This project focuses on the system interpretation of the commands from drivers and passengers, enhancing safety and convenience. The process begins with a diverse voice dataset of vehicular commands. Data preprocessing, noise reduction, and feature extraction convert raw voice data into a trainable format. An Automatic Speech Recognition (ASR) model ensures precise voice recognition, while advanced NLP techniques decode the intent of voice commands. The system understands nuanced requests like “turn on the headlights” or “Change gear to D2.” This project uses pre-existing voice datasets, promising safer and more intuitive driving experiences. As the system matures, it paves the way to autonomous driving. Leveraging existing voice datasets, this innovative project enhances driving safety and convenience, laying the groundwork for the future of autonomous vehicles.