184 citations · 868 across the 60 of their papers we have counts for
6 papers · 1 filter
No Need for a Lexicon? Evaluating the Value of the Pronunciation Lexica in End-to-End Models
Tara N. Sainath, Rohit Prabhavalkar, Shankar Kumar +9
For decades, context-dependent phonemes have been the dominant sub-word unit for conventional acoustic modeling systems. This status quo has begun to be challenged recently by end-…
Multi-Dialect Speech Recognition With A Single Sequence-To-Sequence Model
Bo Li, Tara N. Sainath, Khe Chai Sim +6
Sequence-to-sequence models provide a simple and elegant solution for building speech recognition systems by folding separate components of a typical system, namely acoustic (AM),…
State-of-the-art Speech Recognition With Sequence-to-Sequence Models
Chung-Cheng Chiu, Tara N. Sainath, Yonghui Wu +11
Attention-based encoder-decoder architectures such as Listen, Attend, and Spell (LAS), subsume the acoustic, pronunciation and language model components of a traditional automatic…
Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition
Chris Donahue, Bo Li, Rohit Prabhavalkar
We investigate the effectiveness of generative adversarial networks (GANs) for speech enhancement, in the context of improving noise robustness of automatic speech recognition (ASR…
Multilingual Speech Recognition With A Single End-To-End Model
Shubham Toshniwal, Tara N. Sainath, Ron J. Weiss +4
Training a conventional automatic speech recognition (ASR) system to support multiple languages is challenging because the sub-word unit, lexicon and word inventories are typically…
Projection Based Weight Normalization for Deep Neural Networks
Lei Huang, Xianglong Liu, Bo Lang +1
Optimizing deep neural networks (DNNs) often suffers from the ill-conditioned problem. We observe that the scaling-based weight space symmetry property in rectified nonlinear netwo…