532 citations · 2.6k across the 41 of their papers we have counts for
9 papers · 1 filter
Co-training Transformer with Videos and Images Improves Action Recognition
Bowen Zhang, Jiahui Yu, Christopher Fifty +4
In learning action recognition, models are typically pre-trained on object recognition with images, such as ImageNet, and later fine-tuned on target action recognition with videos.…
Vector-quantized Image Modeling with Improved VQGAN
Jiahui Yu, Xin Li, Jing Yu Koh +7
Pretraining language models with next-token prediction on massive text corpora has delivered phenomenal zero-shot, few-shot, transfer learning and multi-tasking capabilities on bot…
W2v-BERT: Combining Contrastive Learning and Masked Language Modeling for Self-Supervised Speech Pre-Training
Yu-An Chung, Yu Zhang, Wei Han +4
Motivated by the success of masked language modeling~(MLM) in pre-training natural language processing models, we propose w2v-BERT that explores MLM for self-supervised speech repr…
BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition
Yu Zhang, Daniel S. Park, Wei Han +23
We summarize the results of a host of efforts using giant automatic speech recognition (ASR) models pre-trained using large, diverse unlabeled datasets containing approximately a m…
GSPMD: General and Scalable Parallelization for ML Computation Graphs
Yuanzhong Xu, HyoukJoong Lee, Dehao Chen +13
We present GSPMD, an automatic, compiler-based parallelization system for common machine learning computations. It allows users to write programs in the same way as for a single de…
Bridging the gap between streaming and non-streaming ASR systems bydistilling ensembles of CTC and RNN-T models
Thibault Doutre, Wei Han, Chung-Cheng Chiu +3
Streaming end-to-end automatic speech recognition (ASR) systems are widely used in everyday applications that require transcribing speech to text in real-time. Their minimal latenc…
Scaling End-to-End Models for Large-Scale Multilingual ASR
Bo Li, Ruoming Pang, Tara N. Sainath +7
Building ASR models across many languages is a challenging multi-task learning problem due to large variations and heavily unbalanced data. Existing work has shown positive transfe…
Searching for Fast Model Families on Datacenter Accelerators
Sheng Li, Mingxing Tan, Ruoming Pang +4
Neural Architecture Search (NAS), together with model scaling, has shown remarkable progress in designing high accuracy and fast convolutional architecture families. However, as ne…
Transformer Based Deliberation for Two-Pass Speech Recognition
Ke Hu, Ruoming Pang, Tara N. Sainath +1
Interactive speech recognition systems must generate words quickly while also producing accurate results. Two-pass models excel at these requirements by employing a first-pass deco…