Ramanagara, Karnataka, India
I am an undergraduate AIML-focused engineering student with hands-on experience in building end-to-end AI systems, with a strong focus on speech processing and applied machine learning. I have worked on a speech-to-speech translation system involving automatic speech recognition (ASR), language translation, and speech synthesis. My work includes audio preprocessing, transcription using deep learning–based ASR models, integration of translation pipelines, and generation of synthesized speech output. The system supports audio files, video inputs, microphone input, and URL-based sources, with real-time transcription status and caption-style transcript display. I work primarily with Python and have experience using machine learning and deep learning tools to build practical, system-level AI solutions rather than purely theoretical models. I am actively seeking AIML or Speech/AI internships and entry-level roles where I can contribute to real-world AI pipelines and continue developing scalable, production-oriented AI systems.
Successfully completed the Infosys Springboard Internship 6.0, focused on developing AI models for real-time Speech-to-Speech streaming in multiple languages. • Studied and implemented the architecture of modern speech AI systems including Automatic Speech Recognition (ASR), Neural Machine Translation (NMT), and Text-to-Speech (TTS). • Designed an end-to-end pipeline that converts spoken input into translated speech output for multilingual communication. • Worked on audio preprocessing, feature extraction, and model workflow optimization for speech processing tasks. • Explored real-time streaming approaches used in modern voice AI applications and multilingual communication platforms. • Strengthened practical understanding of Machine Learning, Deep Learning, Natural Language Processing, and Speech Processing through hands-on assignments and model experimentation. Focused on building intelligent AI systems for real-time voice intelligence and multilingual communication technologies.
• Worked on applied AI systems involving machine learning and data-driven model development. • Contributed to data preprocessing, feature handling, and model experimentation using Python. • Assisted in testing, refining, and validating ML components within a larger AI system. • Collaborated with team members to improve system reliability and output quality. • Tools used: Python, NumPy, Pandas, Scikit-learn.
Excited to share that I have successfully completed my at @EdiGlobe! Grateful for the opportunity to learn and grow, and a big thank you to my mentors and colleagues for their support. Looking forward to applying these skills in future opportunities! 🚀 #Internship #Learning #Growth