Search Results for author: Milind Rao

Found 12 papers, 2 papers with code

MTL-SLT: Multi-Task Learning for Spoken Language Tasks

no code implementations NLP4ConvAI (ACL) 2022 Zhiqi Huang, Milind Rao, Anirudh Raju, Zhe Zhang, Bach Bui, Chul Lee

The proposed framework benefits from three key aspects: 1) pre-trained sub-networks of ASR model and language model; 2) multi-task learning objective to exploit shared knowledge from different tasks; 3) end-to-end training of ASR and downstream NLP task based on sequence loss.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +5

Improving fairness for spoken language understanding in atypical speech with Text-to-Speech

1 code implementation16 Nov 2023 Helin Wang, Venkatesh Ravichandran, Milind Rao, Becky Lammers, Myra Sydnor, Nicholas Maragakis, Ankur A. Butala, Jayne Zhang, Lora Clawson, Victoria Chovaz, Laureano Moro-Velazquez

Spoken language understanding (SLU) systems often exhibit suboptimal performance in processing atypical speech, typically caused by neurological conditions and motor impairments.

Data Augmentation Fairness +2

Federated Self-Learning with Weak Supervision for Speech Recognition

no code implementations21 Jun 2023 Milind Rao, Gopinath Chennupati, Gautam Tiwari, Anit Kumar Sahu, Anirudh Raju, Ariya Rastrow, Jasha Droppo

Automatic speech recognition (ASR) models with low-footprint are increasingly being deployed on edge devices for conversational agents, which enhances privacy.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +4

Learning When to Trust Which Teacher for Weakly Supervised ASR

no code implementations21 Jun 2023 Aakriti Agrawal, Milind Rao, Anit Kumar Sahu, Gopinath Chennupati, Andreas Stolcke

We show the efficacy of our approach using LibriSpeech and LibriLight benchmarks and find an improvement of 4 to 25\% over baselines that uniformly weight all the experts, use a single expert model, or combine experts using ROVER.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

On joint training with interfaces for spoken language understanding

no code implementations30 Jun 2021 Anirudh Raju, Milind Rao, Gautam Tiwari, Pranav Dheram, Bryan Anderson, Zhe Zhang, Chul Lee, Bach Bui, Ariya Rastrow

Spoken language understanding (SLU) systems extract both text transcripts and semantics associated with intents and slots from input speech utterances.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

Do as I mean, not as I say: Sequence Loss Training for Spoken Language Understanding

no code implementations12 Feb 2021 Milind Rao, Pranav Dheram, Gautam Tiwari, Anirudh Raju, Jasha Droppo, Ariya Rastrow, Andreas Stolcke

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 systems.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

Speech To Semantics: Improve ASR and NLU Jointly via All-Neural Interfaces

no code implementations14 Aug 2020 Milind Rao, Anirudh Raju, Pranav Dheram, Bach Bui, Ariya Rastrow

Finally, we contrast these methods to a jointly trained end-to-end joint SLU model, consisting of ASR and NLU subsystems which are connected by a neural network based interface instead of text, that produces transcripts as well as NLU interpretation.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +4

Distributed Convex Optimization With Limited Communications

no code implementations29 Oct 2018 Milind Rao, Stefano Rini, Andrea Goldsmith

In this paper, a distributed convex optimization algorithm, termed \emph{distributed coordinate dual averaging} (DCDA) algorithm, is proposed.

Distributed Optimization valid

Deep Learning for Joint Source-Channel Coding of Text

1 code implementation19 Feb 2018 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.


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