Awni Hannun

Awni is a research scientist at the Facebook AI Research (FAIR) lab, focusing on low-resource machine learning, speech recognition, and privacy. He earned a Ph.D. in computer science from Stanford University. Prior to Facebook, he worked as a research scientist in Baidu's Silicon Valley AI Lab, where he co-led the Deep Speech projects.

Awni's Publications



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

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 magnitude more efficient than a strong RNN baseline. Key to our…

Awni Hannun, Ann Lee, Qiantong Xu, Ronan Collobert,



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

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 errors, or the noisy transcriptions are used as is. We introduce…

Adrien Dufraux, Emmanuel Dupoux, Awni Hannun, Armelle Brun, Matthijs Douze,



Scaling up online speech recognition using ConvNets

We design an online end-to-end speech recognition system based on Time-Depth Separable (TDS) convolutions and Connectionist Temporal Classification (CTC). The system has almost three times the throughput of a well tuned hybrid ASR baseline…

Vineel Pratap, Qiantong Xu, Jacob Kahn, Gilad Avidov, Tatiana Likhomanenko, Awni Hannun, Vitaliy Liptchinsky, Gabriel Synnaeve, Ronan Collobert,