no code implementations • 15 Jan 2024 • 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.
no code implementations • 14 Jul 2023 • Zitha Sasindran, Harsha Yelchuri, T. V. Prabhakar
Our evaluation has shown that the proposed approach significantly optimises waiting time in FL compared to conventional random client selection methods.
no code implementations • 15 Jun 2023 • Zitha Sasindran, Harsha Yelchuri, Pooja Rao, T. V. Prabhakar
We describe a comprehensive methodology for developing user-voice personalized automatic speech recognition (ASR) models by effectively training models on mobile phones, allowing user data and models to be stored and used locally.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 21 Nov 2022 • Prajwal BN, Harsha Yelchuri, Vishwanath Shastry, T. V. Prabhakar
In this work, we describe the construction of a smart and real-time edge-based electronic product called PreMa, which is basically a sensor for monitoring the health of a Solenoid Valve (SV).
no code implementations • 3 Nov 2022 • Zitha Sasindran, Harsha Yelchuri, T. V. Prabhakar, Supreeth Rao
We propose H_eval, a new hybrid evaluation metric for ASR systems that considers both semantic correctness and error rate and performs significantly well in scenarios where WER and SD perform poorly.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +8
no code implementations • 7 Dec 2021 • Zitha S, Raghavendra Rao Suresh, Pooja Rao, T. V. Prabhakar
We evaluated the framework on various mobile phones from different brands and reported the results.
no code implementations • 5 Feb 2019 • Saurabh Srivastava, Vinay P. Namboodiri, T. V. Prabhakar
AI intensive systems that operate upon user data face the challenge of balancing data utility with privacy concerns.
no code implementations • 13 Apr 2016 • Raviteja Upadrashta, Tarun Choubisa, A. Praneeth, Tony G., Aswath V. S., P. Vijay Kumar, Sripad Kowshik, Hari Prasad Gokul R, T. V. Prabhakar
This paper presents the development of a passive infra-red sensor tower platform along with a classification algorithm to distinguish between human intrusion, animal intrusion and clutter arising from wind-blown vegetative movement in an outdoor environment.