859 citations · 2.2k across the 80 of their papers we have counts for
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Resource-Efficient Transfer Learning From Speech Foundation Model Using Hierarchical Feature Fusion
Zhouyuan Huo, Khe Chai Sim, Bo Li +3
Self-supervised pre-training of a speech foundation model, followed by supervised fine-tuning, has shown impressive quality improvements on automatic speech recognition (ASR) tasks…
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Jonathan Shen, Patrick Nguyen, Yonghui Wu +88
Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models. Lingvo models a…
Learning Compact Recurrent Neural Networks
Zhiyun Lu, Vikas Sindhwani, Tara N. Sainath
Recurrent neural networks (RNNs), including long short-term memory (LSTM) RNNs, have produced state-of-the-art results on a variety of speech recognition tasks. However, these mode…
Accelerating Hessian-free optimization for deep neural networks by implicit preconditioning and sampling
Tara N. Sainath, Lior Horesh, Brian Kingsbury +2
Hessian-free training has become a popular parallel second or- der optimization technique for Deep Neural Network training. This study aims at speeding up Hessian-free training, bo…
Improvements to deep convolutional neural networks for LVCSR
Tara N. Sainath, Brian Kingsbury, Abdel-rahman Mohamed +6
Deep Convolutional Neural Networks (CNNs) are more powerful than Deep Neural Networks (DNN), as they are able to better reduce spectral variation in the input signal. This has also…