15 citations · 53 across the 48 of their papers we have counts for
12 papers · 1 filter
FusDom: Combining In-Domain and Out-of-Domain Knowledge for Continuous Self-Supervised Learning
Ashish Seth, Sreyan Ghosh, S. Umesh +1
Continued pre-training (CP) offers multiple advantages, like target domain adaptation and the potential to exploit the continuous stream of unlabeled data available online. However…
Stable Distillation: Regularizing Continued Pre-training for Low-Resource Automatic Speech Recognition
Ashish Seth, Sreyan Ghosh, S. Umesh +1
Continued self-supervised (SSL) pre-training for adapting existing SSL models to the target domain has shown to be extremely effective for low-resource Automatic Speech Recognition…
AV-RIR: Audio-Visual Room Impulse Response Estimation
Anton Ratnarajah, Sreyan Ghosh, Sonal Kumar +2
Accurate estimation of Room Impulse Response (RIR), which captures an environment's acoustic properties, is important for speech processing and AR/VR applications. We propose AV-RI…
DALE: Generative Data Augmentation for Low-Resource Legal NLP
Sreyan Ghosh, Chandra Kiran Evuru, Sonal Kumar +4
We present DALE, a novel and effective generative Data Augmentation framework for low-resource LEgal NLP. DALE addresses the challenges existing frameworks pose in generating effec…
CompA: Addressing the Gap in Compositional Reasoning in Audio-Language Models
Sreyan Ghosh, Ashish Seth, Sonal Kumar +7
A fundamental characteristic of audio is its compositional nature. Audio-language models (ALMs) trained using a contrastive approach (e.g., CLAP) that learns a shared representatio…
RECAP: Retrieval-Augmented Audio Captioning
Sreyan Ghosh, Sonal Kumar, Chandra Kiran Reddy Evuru +2
We present RECAP (REtrieval-Augmented Audio CAPtioning), a novel and effective audio captioning system that generates captions conditioned on an input audio and other captions simi…
AdVerb: Visually Guided Audio Dereverberation
Sanjoy Chowdhury, Sreyan Ghosh, Subhrajyoti Dasgupta +3
We present AdVerb, a novel audio-visual dereverberation framework that uses visual cues in addition to the reverberant sound to estimate clean audio. Although audio-only dereverber…
ASPIRE: Language-Guided Data Augmentation for Improving Robustness Against Spurious Correlations
Sreyan Ghosh, Chandra Kiran Reddy Evuru, Sonal Kumar +4
Neural image classifiers can often learn to make predictions by overly relying on non-predictive features that are spuriously correlated with the class labels in the training data.…
ACLM: A Selective-Denoising based Generative Data Augmentation Approach for Low-Resource Complex NER
Sreyan Ghosh, Utkarsh Tyagi, Manan Suri +3
Complex Named Entity Recognition (NER) is the task of detecting linguistically complex named entities in low-context text. In this paper, we present ACLM Attention-map aware keywor…
BioAug: Conditional Generation based Data Augmentation for Low-Resource Biomedical NER
Sreyan Ghosh, Utkarsh Tyagi, Sonal Kumar +1
Biomedical Named Entity Recognition (BioNER) is the fundamental task of identifying named entities from biomedical text. However, BioNER suffers from severe data scarcity and lacks…
UNFUSED: UNsupervised Finetuning Using SElf supervised Distillation
Ashish Seth, Sreyan Ghosh, S. Umesh +1
In this paper, we introduce UnFuSeD, a novel approach to leverage self-supervised learning and reduce the need for large amounts of labeled data for audio classification. Unlike pr…
CoSyn: Detecting Implicit Hate Speech in Online Conversations Using a Context Synergized Hyperbolic Network
Sreyan Ghosh, Manan Suri, Purva Chiniya +3
The tremendous growth of social media users interacting in online conversations has led to significant growth in hate speech, affecting people from various demographics. Most of th…