461 citations · 1.5k across the 14 of their papers we have counts for
4 papers · 1 filter
Flashlight: Enabling Innovation in Tools for Machine Learning
Jacob Kahn, Vineel Pratap, Tatiana Likhomanenko +11
As the computational requirements for machine learning systems and the size and complexity of machine learning frameworks increases, essential framework innovation has become chall…
Self-training and Pre-training are Complementary for Speech Recognition
Qiantong Xu, Alexei Baevski, Tatiana Likhomanenko +5
Self-training and unsupervised pre-training have emerged as effective approaches to improve speech recognition systems using unlabeled data. However, it is not clear whether they l…
Rethinking Evaluation in ASR: Are Our Models Robust Enough?
Tatiana Likhomanenko, Qiantong Xu, Vineel Pratap +5
Is pushing numbers on a single benchmark valuable in automatic speech recognition? Research results in acoustic modeling are typically evaluated based on performance on a single da…
An empirical study on evaluation metrics of generative adversarial networks
Qiantong Xu, Gao Huang, Yang Yuan +4
Evaluating generative adversarial networks (GANs) is inherently challenging. In this paper, we revisit several representative sample-based evaluation metrics for GANs, and address…