Shweta Tripathy

Indian Institute of Information Technology Allahabad

Papers

Total Citations

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About

Shweta Tripathy is a leading researcher in the field of Human-Robot Interaction (HRI) and speech processing, with a particular focus on developing intuitive communication systems for Hindi-speaking users. Her most influential work, "A MFCC based Hindi speech recognition technique using HTK Toolkit" (2013), has garnered 29 citations and established a foundational framework for enabling robots to understand and respond to Hindi speech commands. By leveraging Mel-Frequency Cepstral Coefficients (MFCC) and the Hidden Markov Model Toolkit (HTK), Tripathy created a robust speech recognition system that bridges the gap between human language and machine comprehension. This contribution is pivotal for advancing HRI in multilingual contexts, particularly in regions where Hindi is predominant. Her research addresses the critical challenge of making robots more accessible and user-friendly, emphasizing the importance of natural language interfaces in technology. Tripathy’s work continues to inspire further developments in speech-based interaction systems, highlighting her role in shaping the future of human-robot collaboration.