I am an Undergraduate Computer Science student, interested in Machine Learning and Artificial Intelligence. My expertise lies in Speech Analytics, where I have honed my skills using advanced machine learning techniques. I am passionate about Generative AI and have hands-on experience with large language models, particularly utilizing the Intel® OpenVINO™ toolkit for optimization and deployment.
- Completed under the Intel Unnati Industrial Training Program
- Developed and optimized models for running GenAI applications on Intel AI Laptops
- Implemented simple LLM inference on CPU and fine-tuned LLM models using Intel® OpenVINO™
- Utilized the Tinyllama Model for efficient processing
- Completed as a College Mini Project
- Developed a Voice Biometrics website for user authentication based on voice recognition
- Leveraged the Google Web Speech API and Gaussian Mixture Models (GMM) for accurate voice authentication
Currently, I am engaged in an impactful research project titled "Analyze the Perception and Production of Prosody in Depressed vs. Non-Depressed Individuals" which aims to provide deep insights into mental health through speech analysis.