Sparsh Sinha

OverviewAI-generated summary

Sparsh Sinha's research investigates advancements in machine learning, particularly focusing on meta-learning frameworks for tasks such as speaker verification, identification, and imposter detection. His work includes developing improved relation networks for end-to-end speaker recognition systems, aiming to enhance performance with unseen speakers. Sinha has also explored the application of meta-learning for end-to-end imposter identification in speaker recognition scenarios. His research interests extend to natural language processing, with publications on sign language to text classification using one-shot learning. Additionally, Sinha has examined the role of Large Language Models (LLMs) in organizational learning and explored theories related to multi-business supply chain organizations.

Metrics

• h-index: 2
• Publications: 8
• Citations: 11