117 citations · 174 across the 10 of their papers we have counts for
11 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…
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…
Listen with Intent: Improving Speech Recognition with Audio-to-Intent Front-End
Swayambhu Nath Ray, Minhua Wu, Anirudh Raju +7
Comprehending the overall intent of an utterance helps a listener recognize the individual words spoken. Inspired by this fact, we perform a novel study of the impact of explicitly…
On joint training with interfaces for spoken language understanding
Anirudh Raju, Milind Rao, Gautam Tiwari +6
Spoken language understanding (SLU) systems extract both text transcripts and semantics associated with intents and slots from input speech utterances. SLU systems usually consist…
Do as I mean, not as I say: Sequence Loss Training for Spoken Language Understanding
Milind Rao, Pranav Dheram, Gautam Tiwari +4
Spoken language understanding (SLU) systems extract transcriptions, as well as semantics of intent or named entities from speech, and are essential components of voice activated sy…
Decentralized optimization over noisy, rate-constrained networks: Achieving consensus by communicating differences
Rajarshi Saha, Stefano Rini, Milind Rao +1
In decentralized optimization, multiple nodes in a network collaborate to minimize the sum of their local loss functions. The information exchange between nodes required for this t…
Speech To Semantics: Improve ASR and NLU Jointly via All-Neural Interfaces
Milind Rao, Anirudh Raju, Pranav Dheram +2
We consider the problem of spoken language understanding (SLU) of extracting natural language intents and associated slot arguments or named entities from speech that is primarily…
Distributed Convex Optimization With Limited Communications
Milind Rao, Stefano Rini, Andrea Goldsmith
In this paper, a distributed convex optimization algorithm, termed \emph{distributed coordinate dual averaging} (DCDA) algorithm, is proposed. The DCDA algorithm addresses the scen…
Deep Learning for Joint Source-Channel Coding of Text
Nariman Farsad, Milind Rao, Andrea Goldsmith
We consider the problem of joint source and channel coding of structured data such as natural language over a noisy channel. The typical approach to this problem in both theory and…
MGF Approach to the Analysis of Generalized Two-Ray Fading Models
Milind Rao, F. Javier Lopez-Martinez, Mohamed-Slim Alouini +1
We analyze a class of Generalized Two-Ray (GTR) fading channels that consist of two line of sight (LOS) components with random phase plus a diffuse component. We derive a closed fo…