SpeechNet: Weakly Supervised, End-to-End Speech Recognition at Industrial Scale

no code implementations • 21 Nov 2022 • Raphael Tang, Karun Kumar, Gefei Yang, Akshat Pandey, Yajie Mao, Vladislav Belyaev, Madhuri Emmadi, Craig Murray, Ferhan Ture, Jimmy Lin

In this paper, we explore training and deploying an ASR system in the label-scarce, compute-limited setting.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

What the DAAM: Interpreting Stable Diffusion Using Cross Attention

1 code implementation • 10 Oct 2022 • Raphael Tang, Linqing Liu, Akshat Pandey, Zhiying Jiang, Gefei Yang, Karun Kumar, Pontus Stenetorp, Jimmy Lin, Ferhan Ture

Large-scale diffusion neural networks represent a substantial milestone in text-to-image generation, but they remain poorly understood, lacking interpretability analyses.

Denoising Descriptive +3

Disparate Impact of Artificial Intelligence Bias in Ridehailing Economy's Price Discrimination Algorithms

no code implementations • 8 Jun 2020 • Akshat Pandey, Aylin Caliskan

An analysis of 100 million ridehailing samples from the city of Chicago indicates a significant disparate impact in fare pricing of neighborhoods due to AI bias learned from ridehailing utilization patterns associated with demographic attributes.

Decision Making Fairness

Automatically Characterizing Targeted Information Operations Through Biases Present in Discourse on Twitter

1 code implementation • 18 Apr 2020 • Autumn Toney, Akshat Pandey, Wei Guo, David Broniatowski, Aylin Caliskan

This paper considers the problem of automatically characterizing overall attitudes and biases that may be associated with emerging information operations via artificial intelligence.