480 citations · 1.5k across the 24 of their papers we have counts for
28 papers
Federated Representation Learning for Automatic Speech Recognition
Guruprasad V Ramesh, Gopinath Chennupati, Milind Rao +3
Federated Learning (FL) is a privacy-preserving paradigm, allowing edge devices to learn collaboratively without sharing data. Edge devices like Alexa and Siri are prospective sour…
Federated Self-Learning with Weak Supervision for Speech Recognition
Milind Rao, Gopinath Chennupati, Gautam Tiwari +4
Automatic speech recognition (ASR) models with low-footprint are increasingly being deployed on edge devices for conversational agents, which enhances privacy. We study the problem…
Stutter-TTS: Controlled Synthesis and Improved Recognition of Stuttered Speech
Xin Zhang, Iván Vallés-Pérez, Andreas Stolcke +5
Stuttering is a speech disorder where the natural flow of speech is interrupted by blocks, repetitions or prolongations of syllables, words and phrases. The majority of existing au…
Guided contrastive self-supervised pre-training for automatic speech recognition
Aparna Khare, Minhua Wu, Saurabhchand Bhati +2
Contrastive Predictive Coding (CPC) is a representation learning method that maximizes the mutual information between intermediate latent representations and the output of a given…
ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale
Gopinath Chennupati, Milind Rao, Gurpreet Chadha +11
Incremental learning is one paradigm to enable model building and updating at scale with streaming data. For end-to-end automatic speech recognition (ASR) tasks, the absence of hum…
Reducing Geographic Disparities in Automatic Speech Recognition via Elastic Weight Consolidation
Viet Anh Trinh, Pegah Ghahremani, Brian King +3
We present an approach to reduce the performance disparity between geographic regions without degrading performance on the overall user population for ASR. A popular approach is to…