Parallel Composition of Weighted Finite-State Transducers

no code implementations • 6 Oct 2021 • Shubho Sengupta, Vineel Pratap, Awni Hannun

We benchmark our parallel algorithm on the composition of random graphs and the composition of graphs commonly used in speech recognition.

speech-recognition Speech Recognition

CrypTen: Secure Multi-Party Computation Meets Machine Learning

1 code implementation • NeurIPS 2021 • Brian Knott, Shobha Venkataraman, Awni Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten

To foster adoption of secure MPC in machine learning, we present CrypTen: a software framework that exposes popular secure MPC primitives via abstractions that are common in modern machine-learning frameworks, such as tensor computations, automatic differentiation, and modular neural networks.

BIG-bench Machine Learning Image Classification +4

Privacy-Preserving Multi-Party Contextual Bandits

no code implementations • 11 Oct 2019 • Awni Hannun, Brian Knott, Shubho Sengupta, Laurens van der Maaten

This paper considers a learning setting in which multiple parties aim to train a contextual bandit together in a private way: the parties aim to maximize the total reward but do not want to share any of the relevant information they possess with the other parties.

Multi-Armed Bandits Privacy Preserving

ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero

1 code implementation • 12 Feb 2019 • Yuandong Tian, Jerry Ma, Qucheng Gong, Shubho Sengupta, Zhuoyuan Chen, James Pinkerton, C. Lawrence Zitnick

The AlphaGo, AlphaGo Zero, and AlphaZero series of algorithms are remarkable demonstrations of deep reinforcement learning's capabilities, achieving superhuman performance in the complex game of Go with progressively increasing autonomy.

Game of Go

Exploring Sparsity in Recurrent Neural Networks

1 code implementation • 17 Apr 2017 • Sharan Narang, Erich Elsen, Gregory Diamos, Shubho Sengupta

Benchmarks show that using our technique model size can be reduced by 90% and speed-up is around 2x to 7x.

Deep Voice: Real-time Neural Text-to-Speech

3 code implementations • ICML 2017 • Sercan O. Arik, Mike Chrzanowski, Adam Coates, Gregory Diamos, Andrew Gibiansky, Yongguo Kang, Xi-An Li, John Miller, Andrew Ng, Jonathan Raiman, Shubho Sengupta, Mohammad Shoeybi

We present Deep Voice, a production-quality text-to-speech system constructed entirely from deep neural networks.

Audio Synthesis Boundary Detection +2

Deep Speech 2: End-to-End Speech Recognition in English and Mandarin

35 code implementations • 8 Dec 2015 • Dario Amodei, Rishita Anubhai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse Engel, Linxi Fan, Christopher Fougner, Tony Han, Awni Hannun, Billy Jun, Patrick LeGresley, Libby Lin, Sharan Narang, Andrew Ng, Sherjil Ozair, Ryan Prenger, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Yi Wang, Zhiqian Wang, Chong Wang, Bo Xiao, Dani Yogatama, Jun Zhan, Zhenyao Zhu

We show that an end-to-end deep learning approach can be used to recognize either English or Mandarin Chinese speech--two vastly different languages.

Accented Speech Recognition Noisy Speech Recognition

Deep Speech: Scaling up end-to-end speech recognition

24 code implementations • 17 Dec 2014 • Awni Hannun, Carl Case, Jared Casper, Bryan Catanzaro, Greg Diamos, Erich Elsen, Ryan Prenger, Sanjeev Satheesh, Shubho Sengupta, Adam Coates, Andrew Y. Ng

We present a state-of-the-art speech recognition system developed using end-to-end deep learning.

Accented Speech Recognition