activity
20182021
most citedDo as I mean, not as I say: Sequence Loss Training for Spoken Language Understanding

2 citations · 2 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CL20212 cited

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…

math.OC2020

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…

cs.CL2020

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…

cs.DC2018

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…

cs.IT2018

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…