activity
20142025
most citedDeep Speech 2: End-to-End Speech Recognition in English and Mandarin

2.2k citations · 3.7k across the 33 of their papers we have counts for

collaborators
Showing 2019Show all

7 papers · 1 filter

cs.LG2019★ 20 cited

Certified Data Removal from Machine Learning Models

Chuan Guo, Tom Goldstein, Awni Hannun +1

Good data stewardship requires removal of data at the request of the data's owner. This raises the question if and how a trained machine-learning model, which implicitly stores inf…

cs.CL2019

Lead2Gold: Towards exploiting the full potential of noisy transcriptions for speech recognition

Adrien Dufraux, Emmanuel Vincent, Awni Hannun +2

The transcriptions used to train an Automatic Speech Recognition (ASR) system may contain errors. Usually, either a quality control stage discards transcriptions with too many erro…

cs.LG2019★ 9 cited

Privacy-Preserving Multi-Party Contextual Bandits

Awni Hannun, Brian Knott, Shubho Sengupta +1

Contextual bandits are online learners that, given an input, select an arm and receive a reward for that arm. They use the reward as a learning signal and aim to maximize the total…

cs.CL2019★ 205 cited

Self-Training for End-to-End Speech Recognition

Jacob Kahn, Ann Lee, Awni Hannun

We revisit self-training in the context of end-to-end speech recognition. We demonstrate that training with pseudo-labels can substantially improve the accuracy of a baseline model…

cs.CL2019★ 1 cited

Word-level Speech Recognition with a Letter to Word Encoder

Ronan Collobert, Awni Hannun, Gabriel Synnaeve

We propose a direct-to-word sequence model which uses a word network to learn word embeddings from letters. The word network can be integrated seamlessly with arbitrary sequence mo…

cs.CL2019★ 4 cited

Sequence-to-Sequence Speech Recognition with Time-Depth Separable Convolutions

Awni Hannun, Ann Lee, Qiantong Xu +1

We propose a fully convolutional sequence-to-sequence encoder architecture with a simple and efficient decoder. Our model improves WER on LibriSpeech while being an order of magnit…

cs.CL2019★ 15 cited

A Fully Differentiable Beam Search Decoder

Ronan Collobert, Awni Hannun, Gabriel Synnaeve

We introduce a new beam search decoder that is fully differentiable, making it possible to optimize at training time through the inference procedure. Our decoder allows us to combi…