Transforming Indian Digital Landscapes: A Study on Generative AI-Powered Voice Assistants
Abhay Nath, Chintal Upendra Raval · 2024
This study presents the development and evaluation of a generative AI-powered voice assistant designed to transform India's digital landscape. Leveraging advanced AI technologies, the assistant enhances daily interactions and improves accessibility within India's diverse cultural and linguistic context. Key challenges addressed include the integration of accurate and ethical content filtering and the enhancement of system efficiency and responsiveness tailored to Indian users. The AI voice assistant was developed using deep learning and natural language processing techniques. The text-to-speech module utilized the 'pyttsx3' library, while the 'speech_recognition' module enabled robust speech-to-text capabilities. Convolutional and recurrent neural networks were employed for image analysis and sequential data processing. Data management was handled through JSON files, ensuring efficient storage and retrieval of command structures and responses. The Natural Language Toolkit (NLTK) was used for tasks such as tokenization and stemming. The AI model was trained using PyTorch, with a focus on optimizing parameters. The system achieved a 95% accuracy rate in user interactions, demonstrating significant advancements in task completion and user satisfaction. Testing was conducted on an NVIDIA DGX STATION A100. This study underscores the transformative potential of AI-powered voice assistants in reshaping India's digital landscape, promoting inclusivity and efficiency.