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Found 8 papers, 0 papers with code
SeMaScore : a new evaluation metric for automatic speech recognition tasks
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.
Ed-Fed: A generic federated learning framework with resource-aware client selection for edge devices
Our evaluation has shown that the proposed approach significantly optimises waiting time in FL compared to conventional random client selection methods.
MobileASR: A resource-aware on-device learning framework for user voice personalization applications on mobile phones
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
PreMa: Predictive Maintenance of Solenoid Valve in Real-Time at Embedded Edge-Level
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).
H_eval: A new hybrid evaluation metric for automatic speech recognition tasks
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
Training end-to-end speech-to-text models on mobile phones
We evaluated the framework on various mobile phones from different brands and reported the results.
PUTWorkbench: Analysing Privacy in AI-intensive Systems
AI intensive systems that operate upon user data face the challenge of balancing data utility with privacy concerns.
Animation and Chirplet-Based Development of a PIR Sensor Array for Intruder Classification in an Outdoor Environment
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.
