81 citations · 101 across the 7 of their papers we have counts for
9 papers
SummaryMixing: A Linear-Complexity Alternative to Self-Attention for Speech Recognition and Understanding
Titouan Parcollet, Rogier van Dalen, Shucong Zhang +1
Modern speech processing systems rely on self-attention. Unfortunately, token mixing with self-attention takes quadratic time in the length of the speech utterance, slowing down in…
Cross-Attention is all you need: Real-Time Streaming Transformers for Personalised Speech Enhancement
Shucong Zhang, Malcolm Chadwick, Alberto Gil C. P. Ramos +1
Personalised speech enhancement (PSE), which extracts only the speech of a target user and removes everything else from a recorded audio clip, can potentially improve users' experi…
Defensive Tensorization
Adrian Bulat, Jean Kossaifi, Sourav Bhattacharya +5
We propose defensive tensorization, an adversarial defence technique that leverages a latent high-order factorization of the network. The layers of a network are first expressed as…
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…
MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors
Royson Lee, Stylianos I. Venieris, Łukasz Dudziak +2
In recent years, convolutional networks have demonstrated unprecedented performance in the image restoration task of super-resolution (SR). SR entails the upscaling of a single low…