Search Results for author: Dushyant Sharma

Found 6 papers, 0 papers with code

XANE Background Acoustic Embeddings: Ablation and Clustering Analysis

no code implementations8 Jul 2024 Dushyant Sharma, James Fosburgh, Sri Harsha Dumpala, Chandramouli Shama Sastri, Stanislav Yu. Kruchinin, Patrick A. Naylor

The XANE embeddings are used to estimate specific parameters related to the background acoustic properties of the signal which allows the embeddings to be explainable in terms of those parameters.

Clustering

XANE: eXplainable Acoustic Neural Embeddings

no code implementations7 Jun 2024 Sri Harsha Dumpala, Dushyant Sharma, Chandramouli Shama Sastri, Stanislav Kruchinin, James Fosburgh, Patrick A. Naylor

We present a novel method for extracting neural embeddings that model the background acoustics of a speech signal.

Auxiliary Network-Enabled Attack Detection and Resilient Control of Islanded AC Microgrid

no code implementations30 Dec 2023 Vaibhav Vaishnav, Anoop Jain, Dushyant Sharma

It is shown that the in situ presence of a concealed auxiliary layer not only guarantees resilience against stealthy bounded attacks on both frequency and power-sharing but also facilitates a network-enabled attack identification mechanism.

Spatial Processing Front-End For Distant ASR Exploiting Self-Attention Channel Combinator

no code implementations25 Mar 2022 Dushyant Sharma, Rong Gong, James Fosburgh, Stanislav Yu. Kruchinin, Patrick A. Naylor, Ljubomir Milanovic

We present a novel multi-channel front-end based on channel shortening with theWeighted Prediction Error (WPE) method followed by a fixed MVDR beamformer used in combination with a recently proposed self-attention-based channel combination (SACC) scheme, for tackling the distant ASR problem.

ChannelAugment: Improving generalization of multi-channel ASR by training with input channel randomization

no code implementations23 Sep 2021 Marco Gaudesi, Felix Weninger, Dushyant Sharma, Puming Zhan

End-to-end (E2E) multi-channel ASR systems show state-of-the-art performance in far-field ASR tasks by joint training of a multi-channel front-end along with the ASR model.

Data Augmentation

Self-Attention Channel Combinator Frontend for End-to-End Multichannel Far-field Speech Recognition

no code implementations10 Sep 2021 Rong Gong, Carl Quillen, Dushyant Sharma, Andrew Goderre, José Laínez, Ljubomir Milanović

When a sufficiently large far-field training data is presented, jointly optimizing a multichannel frontend and an end-to-end (E2E) Automatic Speech Recognition (ASR) backend shows promising results.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

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