ResearchTrend.AI
Practical Conformer: Optimizing size, speed and flops of Conformer for on-Device and cloud ASR

Practical Conformer: Optimizing size, speed and flops of Conformer for on-Device and cloud ASR

Rami Botros
Anmol Gulati
Tara N. Sainath
K. Choromanski
Ruoming Pang
Trevor Strohman
Weiran Wang
Jiahui Yu
    MQ
ArXiv (abs)PDFHTML

Papers citing "Practical Conformer: Optimizing size, speed and flops of Conformer for on-Device and cloud ASR"

3 / 3 papers shown
Title
On the compression of shallow non-causal ASR models using knowledge distillation and tied-and-reduced decoder for low-latency on-device speech recognition
On the compression of shallow non-causal ASR models using knowledge distillation and tied-and-reduced decoder for low-latency on-device speech recognition
Nagaraj Adiga
Jinhwan Park
Chintigari Shiva Kumar
Shatrughan Singh
Kyungmin Lee
Chanwoo Kim
Dhananjaya N. Gowda
64
1
0
15 Dec 2023
Enabling Differentially Private Federated Learning for Speech Recognition: Benchmarks, Adaptive Optimizers and Gradient Clipping
Enabling Differentially Private Federated Learning for Speech Recognition: Benchmarks, Adaptive Optimizers and Gradient Clipping
Martin Pelikan
Sheikh Shams Azam
Vitaly Feldman
Jan Honza Silovsky
Kunal Talwar
Christopher G. Brinton
Tatiana Likhomanenko
127
8
0
29 Sep 2023
Fast Transformer Decoding: One Write-Head is All You Need
Fast Transformer Decoding: One Write-Head is All You Need
Noam M. Shazeer
188
479
0
06 Nov 2019

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.