6 citations · 8 across the 3 of their papers we have counts for
3 papers
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…
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…
Training end-to-end speech-to-text models on mobile phones
Zitha S, Raghavendra Rao Suresh, Pooja Rao +1
Training the state-of-the-art speech-to-text (STT) models in mobile devices is challenging due to its limited resources relative to a server environment. In addition, these models…