566 citations · 1.6k across the 8 of their papers we have counts for
9 papers
DISGO: Automatic End-to-End Evaluation for Scene Text OCR
Mei-Yuh Hwang, Yangyang Shi, Ankit Ramchandani +6
This paper discusses the challenges of optical character recognition (OCR) on natural scenes, which is harder than OCR on documents due to the wild content and various image backgr…
Factorized Blank Thresholding for Improved Runtime Efficiency of Neural Transducers
Duc Le, Frank Seide, Yuhao Wang +4
We show how factoring the RNN-T's output distribution can significantly reduce the computation cost and power consumption for on-device ASR inference with no loss in accuracy. With…
Federated Domain Adaptation for ASR with Full Self-Supervision
Junteng Jia, Jay Mahadeokar, Weiyi Zheng +3
Cross-device federated learning (FL) protects user privacy by collaboratively training a model on user devices, therefore eliminating the need for collecting, storing, and manually…
An Investigation of Monotonic Transducers for Large-Scale Automatic Speech Recognition
Niko Moritz, Frank Seide, Duc Le +2
The two most popular loss functions for streaming end-to-end automatic speech recognition (ASR) are RNN-Transducer (RNN-T) and connectionist temporal classification (CTC). Between…
Marian: Fast Neural Machine Translation in C++
Marcin Junczys-Dowmunt, Roman Grundkiewicz, Tomasz Dwojak +9
We present Marian, an efficient and self-contained Neural Machine Translation framework with an integrated automatic differentiation engine based on dynamic computation graphs. Mar…
Achieving Human Parity on Automatic Chinese to English News Translation
Hany Hassan, Anthony Aue, Chang Chen +21
Machine translation has made rapid advances in recent years. Millions of people are using it today in online translation systems and mobile applications in order to communicate acr…
Achieving Human Parity in Conversational Speech Recognition
W. Xiong, J. Droppo, X. Huang +5
Conversational speech recognition has served as a flagship speech recognition task since the release of the Switchboard corpus in the 1990s. In this paper, we measure the human err…
The Microsoft 2016 Conversational Speech Recognition System
W. Xiong, J. Droppo, X. Huang +5
We describe Microsoft's conversational speech recognition system, in which we combine recent developments in neural-network-based acoustic and language modeling to advance the stat…
Feature Learning in Deep Neural Networks - Studies on Speech Recognition Tasks
Dong Yu, Michael L. Seltzer, Jinyu Li +2
Recent studies have shown that deep neural networks (DNNs) perform significantly better than shallow networks and Gaussian mixture models (GMMs) on large vocabulary speech recognit…