activity
20152022
most citedConformer: Convolution-augmented Transformer for Speech Recognition

387 citations · 630 across the 10 of their papers we have counts for

collaborators
Showing 2020Show all

6 papers · 1 filter

eess.AS2020

FastEmit: Low-latency Streaming ASR with Sequence-level Emission Regularization

Jiahui Yu, Chung-Cheng Chiu, Bo Li +8

Streaming automatic speech recognition (ASR) aims to emit each hypothesized word as quickly and accurately as possible. However, emitting fast without degrading quality, as measure…

eess.AS2020387 cited

Conformer: Convolution-augmented Transformer for Speech Recognition

Anmol Gulati, James Qin, Chung-Cheng Chiu +8

Recently Transformer and Convolution neural network (CNN) based models have shown promising results in Automatic Speech Recognition (ASR), outperforming Recurrent neural networks (…

eess.AS202072 cited

ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global Context

Wei Han, Zhengdong Zhang, Yu Zhang +6

Convolutional neural networks (CNN) have shown promising results for end-to-end speech recognition, albeit still behind other state-of-the-art methods in performance. In this paper…

cs.CV20206 cited

Streaming Object Detection for 3-D Point Clouds

Wei Han, Zhengdong Zhang, Benjamin Caine +7

Autonomous vehicles operate in a dynamic environment, where the speed with which a vehicle can perceive and react impacts the safety and efficacy of the system. LiDAR provides a pr…

eess.AS2020

Improved Noisy Student Training for Automatic Speech Recognition

Daniel S. Park, Yu Zhang, Ye Jia +5

Recently, a semi-supervised learning method known as "noisy student training" has been shown to improve image classification performance of deep networks significantly. Noisy stude…

eess.AS2020

RNN-T Models Fail to Generalize to Out-of-Domain Audio: Causes and Solutions

Chung-Cheng Chiu, Arun Narayanan, Wei Han +8

In recent years, all-neural end-to-end approaches have obtained state-of-the-art results on several challenging automatic speech recognition (ASR) tasks. However, most existing wor…