About

Shivam Soni is a Senior Technical Lead at HCLTech ERS with a passion for Audio AI research engineering. He holds an M.Tech degree in Signal Processing from IIT Bhubaneswar and has over 4 years of relevant experience. Shivam has hands-on experience in various areas such as digital signal processing, speech processing, audio processing, speech analytics, automatic speech recognition, speech emotion detection, and more. Currently, Shivam is working on Speech and Audio AI domain at the HCL Technologies R&D lab. His key responsibilities include audio/speech engine architecture designing, innovating novel audio algorithms, proposing innovative machine learning solutions, identifying key research questions, defining data requirements, data collection, data preparation for AI models, project documentation, ASR training on Kaldi speech engine, performance tuning, acceptance testing, analyzing results, deploying solutions, reading current research papers, publishing the result (White paper and research paper writing), and mentoring junior members. His recent work includes Audio event classification, Educational Videos Summarization, Sentiment Analysis, Cough Classification, Japanese Slurred Voice Assistant for Elderly people, Limited Vocab Indian English Voice Assistant for Touchfree Elevator, Speech-based Emotion Recognition, Medical Vocab US accent ASR, and more. Before joining HCL, Shivam worked as a Teaching Assistant at IIT Bhubaneswar, where he taught Digital Signal Processing and Signal & System. He holds a B.Tech degree in Electronics and Communications Engineering from Dr. A.P.J. Abdul Kalam Technical University and completed his Intermediate and High School from Noor Mohammad Inter College and NMIC College Zaidpur, respectively. Shivam's technical skills include Software Engineering, AI, LLM, Deep Learning, NLP, Research Scientist, Data Scientist, BERT, Sentiment Analysis, Senior Software Engineer, GPT, and ML. He is a dedicated and passionate individual who is always looking for ways to improve his skills and knowledge in the field of Audio AI research engineering.