no code implementations • 25 Oct 2024 • Abhay Kumar, Vigneshwaran Shankaran, Rajesh Sharma
In the recent years online social media platforms has been flooded with hateful remarks such as racism, sexism, homophobia etc.
no code implementations • 16 Oct 2024 • Orchid Chetia Phukan, Swarup Ranjan Behera, Girish, Mohd Mujtaba Akhtar, Arun Balaji Buduru, Rajesh Sharma
Despite being trained exclusively on speech data, speech foundation models (SFMs) like Whisper have shown impressive performance in non-speech tasks such as audio classification.
no code implementations • 16 Oct 2024 • Sarthak Jain, Orchid Chetia Phukan, Swarup Ranjan Behera, Arun Balaji Buduru, Rajesh Sharma
In this work, we introduce SeQuiFi, a novel approach for mitigating catastrophic forgetting (CF) in speech emotion recognition (SER).
no code implementations • 16 Oct 2024 • Orchid Chetia Phukan, Devyani Koshal, Swarup Ranjan Behera, Arun Balaji Buduru, Rajesh Sharma
However, most prior efforts have centered on building individual models for each task separately, despite the inherent similarities among these tasks.
no code implementations • 24 Sep 2024 • Orchid Chetia Phukan, Girish, Mohd Mujtaba Akhtar, Swarup Ranjan Behera, Nitin Choudhury, Arun Balaji Buduru, Rajesh Sharma, S. R Mahadeva Prasanna
We show that such random selection preserves more performance than the SOTA dimensionality reduction techniques while reducing model parameters and inference time by almost over half.
no code implementations • 22 Sep 2024 • Orchid Chetia Phukan, Swarup Ranjan Behera, Shubham Singh, Muskaan Singh, Vandana Rajan, Arun Balaji Buduru, Rajesh Sharma, S. R. Mahadeva Prasanna
In this work, we demonstrate that the amalgamation of NSFs results in complementary behavior, leading to enhanced depression detection performance.
no code implementations • 21 Sep 2024 • Orchid Chetia Phukan, Mohd Mujtaba Akhtar, Girish, Swarup Ranjan Behera, Sishir Kalita, Arun Balaji Buduru, Rajesh Sharma, S. R Mahadeva Prasanna
Through MATA coupled with the combination of MFMs: LanguageBind and ImageBind, we report the topmost performance with accuracies of 76. 47%, 77. 40%, 75. 12% and F1-scores of 70. 35%, 76. 19%, 74. 63% for ASVP-ESD, JNV, and VIVAE datasets against individual FMs and baseline fusion techniques and report SOTA on the benchmark datasets.
no code implementations • 21 Sep 2024 • Orchid Chetia Phukan, Sarthak Jain, Swarup Ranjan Behera, Arun Balaji Buduru, Rajesh Sharma, S. R Mahadeva Prasanna
In this study, for the first time, we extensively investigate whether music foundation models (MFMs) or speech foundation models (SFMs) work better for singing voice deepfake detection (SVDD), which has recently attracted attention in the research community.
1 code implementation • 11 Sep 2024 • Faiz Ali Shah, Ahmed Sabir, Rajesh Sharma
Given the volume of user reviews received daily, an automated mechanism to generate feature-level sentiment summaries of user reviews is needed.
no code implementations • 15 Jun 2024 • Sarthak Sharma, Orchid Chetia Phukan, Drishti Singh, Arun Balaji Buduru, Rajesh Sharma
In this work, we present, AVR application for audio-visual humor detection.
1 code implementation • 13 Jun 2024 • Orchid Chetia Phukan, Priyabrata Mallick, Swarup Ranjan Behera, Aalekhya Satya Narayani, Arun Balaji Buduru, Rajesh Sharma
In this paper, we work towards extending Audio-Visual Question Answering (AVQA) to multilingual settings.
Audio-visual Question Answering Audio-Visual Question Answering (AVQA) +3
no code implementations • 10 Jun 2024 • Orchid Chetia Phukan, Sarthak Jain, Shubham Singh, Muskaan Singh, Arun Balaji Buduru, Rajesh Sharma
To address this, in this paper, we introduce ComFeAT, an application that employs a CNN model trained on a combination of features extracted from PTMs, a. k. a.
no code implementations • 10 Jun 2024 • Devyani Koshal, Orchid Chetia Phukan, Sarthak Jain, Arun Balaji Buduru, Rajesh Sharma
Emotion Recognition (ER), Gender Recognition (GR), and Age Estimation (AE) constitute paralinguistic tasks that rely not on the spoken content but primarily on speech characteristics such as pitch and tone.
no code implementations • 10 Jun 2024 • Sarthak Jain, Orchid Chetia Phukan, Arun Balaji Buduru, Rajesh Sharma
In this paper, we focus on audio violence detection (AVD).
no code implementations • 5 Jun 2024 • Orchid Chetia Phukan, Yashasvi Chaurasia, Arun Balaji Buduru, Rajesh Sharma
In this study, we investigate representations from paralingual Pre-Trained model (PTM) for Audio Abuse Detection (AAD), which has not been explored for AAD.
no code implementations • 11 Apr 2024 • Vigneshwaran Shankaran, Rajesh Sharma
This anonymity has also made social media prone to harmful content, which requires moderation to ensure responsible and productive use.
no code implementations • 31 Mar 2024 • Orchid Chetia Phukan, Ankita Das, Arun Balaji Buduru, Rajesh Sharma
Stress recognition through physiological signals such as Electrocardiogram (ECG) signals has garnered significant attention.
1 code implementation • 31 Mar 2024 • Orchid Chetia Phukan, Gautam Siddharth Kashyap, Arun Balaji Buduru, Rajesh Sharma
To validate our hypothesis, we extract representations from state-of-the-art (SOTA) PTMs including monolingual, multilingual as well as PTMs trained for speaker and emotion recognition, and evaluated them on ASVSpoof 2019 (ASV), In-the-Wild (ITW), and DECRO benchmark databases.
1 code implementation • 18 Mar 2024 • Aditya Narayan Sankaran, Vigneshwaran Shankaran, Sampath Lonka, Rajesh Sharma
To summarize, this work highlights the pervasive nature of gender stereotypes in literary works and reveals the potential of LLMs to rectify gender stereotypes.
no code implementations • 2 Feb 2024 • Orchid Chetia Phukan, Gautam Siddharth Kashyap, Arun Balaji Buduru, Rajesh Sharma
However, such paralinguistic PTM representations haven't been evaluated for SER in linguistic environments other than English.
no code implementations • 15 Nov 2023 • Swapnil Mane, Suman Kundu, Rajesh Sharma
Recognizing the societal risks associated with unchecked aggressive content, this paper delves into the field of Aggression Content Detection and Behavioral Analysis of Aggressive Users, aiming to bridge the gap between disparate studies.
no code implementations • 29 Oct 2023 • Shakshi Sharma, Anwitaman Datta, Rajesh Sharma
While the ideas herein can be generalized and reapplied in the broader context of misinformation mitigation using a multitude of information sources and catering to the spectrum of social media platforms, this work serves as a proof of concept, and as such, it is confined in its scope to only rebuttal of tweets, and in the specific context of misinformation regarding COVID-19.
no code implementations • 11 Oct 2023 • Gustav Nikopensius, Mohit Mayank, Orchid Chetia Phukan, Rajesh Sharma
Extensive experiments on FB15K-277 and NELL-995 datasets reveal that reasoning over a KG is an effective way of producing human-readable explanations in the form of paths and classifications for fact claims.
no code implementations • 25 Aug 2023 • Shakshi Sharma, Anwitaman Datta, Vigneshwaran Shankaran, Rajesh Sharma
We demonstrate the Misinformation Concierge, a proof-of-concept that provides actionable intelligence on misinformation prevalent in social media.
no code implementations • 29 May 2023 • Animesh Chaturvedi, Rajesh Sharma
For a given set of Hate Terms lists (HTs-lists) and Hate Speech data (HS-data), it is challenging to understand which hate term contributes the most for hate speech classification.
no code implementations • 29 May 2023 • Orchid Chetia Phukan, Arun Balaji Buduru, Rajesh Sharma
Speech emotion recognition (SER) is a field that has drawn a lot of attention due to its applications in diverse fields.
no code implementations • 22 Apr 2023 • Orchid Chetia Phukan, Arun Balaji Buduru, Rajesh Sharma
In this work, we exploit this research gap and perform a comparative analysis of embeddings extracted from eight speech and audio PTMs (wav2vec 2. 0, data2vec, wavLM, UniSpeech-SAT, wav2clip, YAMNet, x-vector, ECAPA).
no code implementations • 15 Jan 2023 • Rahul Goel, Angelo Furno, Rajesh Sharma
Nonetheless, alternative data sources, such as call data records (CDR) and mobile app usage, can serve as cost-effective and up-to-date sources for identifying socio-economic indicators.
1 code implementation • 25 Feb 2022 • Mudit Dhawan, Shakshi Sharma, Aditya Kadam, Rajesh Sharma, Ponnurangam Kumaraguru
A plethora of previous multimodal-based work has tried to address the problem of modeling heterogeneous modalities in identifying fake content.
no code implementations • 25 Jan 2022 • Rahul Goel, Modar Sulaiman, Kimia Noorbakhsh, Mahdi Sharifi, Rajesh Sharma, Pooyan Jamshidi, Kallol Roy
The pretrained transformer of GPT-2 is trained to generate text and then fine-tuned to classify facial images.
no code implementations • 9 Nov 2021 • Sabur Butt, Shakshi Sharma, Rajesh Sharma, Grigori Sidorov, Alexander Gelbukh
In the descriptive line of works, where researchers have tried to analyse rumours using NLP approaches, there isnt much emphasis on psycho-linguistics analyses of social media text.
1 code implementation • 16 Aug 2021 • Shakshi Sharma, Rajesh Sharma, Anwitaman Datta
We build on this to study and contrast the characteristics of tweets in the corpus that are misleading in nature against non-misleading ones.
no code implementations • 4 Jul 2021 • Mohit Mayank, Shakshi Sharma, Rajesh Sharma
Our approach is a combination of the NLP -- where we encode the news content, and the GNN technique -- where we encode the Knowledge Graph (KG).
1 code implementation • 2 Jul 2021 • Raj Jagtap, Abhinav Kumar, Rahul Goel, Shakshi Sharma, Rajesh Sharma, Clint P. George
Using caption dataset, the proposed models can classify videos among three classes (Misinformation, Debunking Misinformation, and Neutral) with 0. 85 to 0. 90 F1-score.
no code implementations • 11 Apr 2021 • Abdul Wahid, Rajesh Sharma, Chandra Sekhara Rao Annavarapu
Scientific publications play a vital role in the career of a researcher.
no code implementations • 13 Nov 2020 • Rahul Goel, Lucas Javier Ford, Maksym Obrizan, Rajesh Sharma
COVID-19 has had a much larger impact on the financial markets compared to previous epidemics because the news information is transferred over the social networks at a speed of light.
2 code implementations • 15 Oct 2020 • Shakshi Sharma, Rajesh Sharma
Thus, it is important to detect and control the misinformation in such platforms before it spreads to the masses.
no code implementations • 29 Apr 2020 • Ivan Slobozhan, Peter Ormosi, Rajesh Sharma
We also investigate the influence of the intensity of the lobbying activity on how discernible a lobbied bill is from one that was not subject to lobbying.
no code implementations • 18 Apr 2020 • Navedanjum Ansari, Rajesh Sharma
Three out of four proposed architectures outperformed the accuracy from previous machine learning and deep learning research work, two out of four models outperformed accuracy from previous deep learning study on Quora's question pair dataset, and our best model achieved accuracy of 85. 82% which is close to Quora state of the art accuracy.