6 citations · 12 across the 7 of their papers we have counts for
7 papers
RoboTwin: A Robotic Teleoperation Framework Using Digital Twins
Harsha Yelchuri, Diwakar Kumar Singh, Nithish Krishnabharathi Gnani +2
Robotic surgery imposes a significant cognitive burden on the surgeon. This cognitive burden increases in the case of remote robotic surgeries due to latency between entities and t…
SeMaScore : a new evaluation metric for automatic speech recognition tasks
Zitha Sasindran, Harsha Yelchuri, T. V. Prabhakar
In this study, we present SeMaScore, generated using a segment-wise mapping and scoring algorithm that serves as an evaluation metric for automatic speech recognition tasks. SeMaSc…
Ed-Fed: A generic federated learning framework with resource-aware client selection for edge devices
Zitha Sasindran, Harsha Yelchuri, T. V. Prabhakar
Federated learning (FL) has evolved as a prominent method for edge devices to cooperatively create a unified prediction model while securing their sensitive training data local to…
MobileASR: A resource-aware on-device learning framework for user voice personalization applications on mobile phones
Zitha Sasindran, Harsha Yelchuri, Pooja Rao +1
We describe a comprehensive methodology for developing user-voice personalized automatic speech recognition (ASR) models by effectively training models on mobile phones, allowing u…
PreMa: Predictive Maintenance of Solenoid Valve in Real-Time at Embedded Edge-Level
Prajwal BN, Harsha Yelchuri, Vishwanath Shastry +1
In industrial process automation, sensors (pressure, temperature, etc.), controllers, and actuators (solenoid valves, electro-mechanical relays, circuit breakers, motors, etc.) mak…
A review of TinyML
Harsha Yelchuri, Rashmi R
In this current technological world, the application of machine learning is becoming ubiquitous. Incorporating machine learning algorithms on extremely low-power and inexpensive em…
H_eval: A new hybrid evaluation metric for automatic speech recognition tasks
Zitha Sasindran, Harsha Yelchuri, T. V. Prabhakar +1
Many studies have examined the shortcomings of word error rate (WER) as an evaluation metric for automatic speech recognition (ASR) systems. Since WER considers only literal word-l…