Pranav Barot
Papers
1
Total Citations
2
H-Index
1
About
Pranav Barot is a researcher at the forefront of human-robot interaction, specializing in binaural acoustic signal processing and auditory perception for humanoid robots. His work focuses on enabling robots to localize human speakers in real time, a critical capability for natural, human-like communication. In his most-cited paper, "Estimating speaker direction on a humanoid robot with binaural acoustic signals" (2024), Barot presents a novel method to optimize direction-of-arrival (DOA) estimation parameters, balancing accuracy with the computational constraints of real-time applications. This contribution addresses a fundamental challenge in social robotics: allowing machines to passively and efficiently track a talker’s location, much like humans do with two ears. While his citation count is still growing, Barot’s research is already recognized for its practical implications in developing more responsive, autonomous humanoid platforms. His work bridges signal processing, robotics, and cognitive science, offering a pathway toward robots that can engage in fluid, context-aware dialogue. For students and researchers, Barot’s approach exemplifies how targeted algorithmic optimization can solve real-world sensory integration problems, making him a rising voice in the field of embodied auditory perception.
Research Focus
Key Achievements
Top Papers
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