66 citations · 108 across the 7 of their papers we have counts for
9 papers
Inferring Facing Direction from Voice Signals
Yu-Lin Wei, Rui Li, Abhinav Mehrotra +2
Consider a home or office where multiple devices are running voice assistants (e.g., TVs, lights, ovens, refrigerators, etc.). A human user turns to a particular device and gives a…
Smart at what cost? Characterising Mobile Deep Neural Networks in the wild
Mario Almeida, Stefanos Laskaridis, Abhinav Mehrotra +3
With smartphones' omnipresence in people's pockets, Machine Learning (ML) on mobile is gaining traction as devices become more powerful. With applications ranging from visual filte…
Zero-Cost Proxies for Lightweight NAS
Mohamed S. Abdelfattah, Abhinav Mehrotra, Łukasz Dudziak +1
Neural Architecture Search (NAS) is quickly becoming the standard methodology to design neural network models. However, NAS is typically compute-intensive because multiple models n…
Bunched LPCNet : Vocoder for Low-cost Neural Text-To-Speech Systems
Ravichander Vipperla, Sangjun Park, Kihyun Choo +6
LPCNet is an efficient vocoder that combines linear prediction and deep neural network modules to keep the computational complexity low. In this work, we present two techniques to…
Iterative Compression of End-to-End ASR Model using AutoML
Abhinav Mehrotra, Łukasz Dudziak, Jinsu Yeo +9
Increasing demand for on-device Automatic Speech Recognition (ASR) systems has resulted in renewed interests in developing automatic model compression techniques. Past research hav…
Graph Input Representations for Machine Learning Applications in Urban Network Analysis
Alessio Pagani, Abhinav Mehrotra, Mirco Musolesi
Understanding and learning the characteristics of network paths has been of particular interest for decades and has led to several successful applications. Such analysis becomes ch…