Search Results for author: S Ramaneswaran

Found 4 papers, 4 papers with code

DALE: Generative Data Augmentation for Low-Resource Legal NLP

1 code implementation • 24 Oct 2023 • Sreyan Ghosh, Chandra Kiran Evuru, Sonal Kumar, S Ramaneswaran, S Sakshi, Utkarsh Tyagi, Dinesh Manocha

We present DALE, a novel and effective generative Data Augmentation framework for low-resource LEgal NLP.

Data Augmentation Decoder +3

8

Paper
Code

ACLM: A Selective-Denoising based Generative Data Augmentation Approach for Low-Resource Complex NER

1 code implementation • 1 Jun 2023 • Sreyan Ghosh, Utkarsh Tyagi, Manan Suri, Sonal Kumar, S Ramaneswaran, Dinesh Manocha

In addition, we demonstrate the application of ACLM to other domains that suffer from data scarcity (e. g., biomedical).

Data Augmentation Denoising +5

16

Paper
Code

M-MELD: A Multilingual Multi-Party Dataset for Emotion Recognition in Conversations

1 code implementation • 31 Mar 2022 • Sreyan Ghosh, S Ramaneswaran, Utkarsh Tyagi, Harshvardhan Srivastava, Samden Lepcha, S Sakshi, Dinesh Manocha

Expression of emotions is a crucial part of daily human communication.

Emotion Recognition

3

Paper
Code

MMER: Multimodal Multi-task Learning for Speech Emotion Recognition

1 code implementation • 31 Mar 2022 • Sreyan Ghosh, Utkarsh Tyagi, S Ramaneswaran, Harshvardhan Srivastava, Dinesh Manocha

In this paper, we propose MMER, a novel Multimodal Multi-task learning approach for Speech Emotion Recognition.

Ranked #2 on Speech Emotion Recognition on IEMOCAP (using extra training data)

Multi-Task Learning Speech Emotion Recognition

53

Paper
Code

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