34 citations · 64 across the 13 of their papers we have counts for
13 papers
MM-AU:Towards Multimodal Understanding of Advertisement Videos
Digbalay Bose, Rajat Hebbar, Tiantian Feng +3
Advertisement videos (ads) play an integral part in the domain of Internet e-commerce as they amplify the reach of particular products to a broad audience or can serve as a medium…
Robust Self Supervised Speech Embeddings for Child-Adult Classification in Interactions involving Children with Autism
Rimita Lahiri, Tiantian Feng, Rajat Hebbar +3
We address the problem of detecting who spoke when in child-inclusive spoken interactions i.e., automatic child-adult speaker classification. Interactions involving children are ri…
FedMultimodal: A Benchmark For Multimodal Federated Learning
Tiantian Feng, Digbalay Bose, Tuo Zhang +6
Over the past few years, Federated Learning (FL) has become an emerging machine learning technique to tackle data privacy challenges through collaborative training. In the Federate…
Understanding Spoken Language Development of Children with ASD Using Pre-trained Speech Embeddings
Anfeng Xu, Rajat Hebbar, Rimita Lahiri +5
Speech processing techniques are useful for analyzing speech and language development in children with Autism Spectrum Disorder (ASD), who are often varied and delayed in acquiring…
TrustSER: On the Trustworthiness of Fine-tuning Pre-trained Speech Embeddings For Speech Emotion Recognition
Tiantian Feng, Rajat Hebbar, Shrikanth Narayanan
Recent studies have explored the use of pre-trained embeddings for speech emotion recognition (SER), achieving comparable performance to conventional methods that rely on low-level…
Contextually-rich human affect perception using multimodal scene information
Digbalay Bose, Rajat Hebbar, Krishna Somandepalli +1
The process of human affect understanding involves the ability to infer person specific emotional states from various sources including images, speech, and language. Affect percept…
A dataset for Audio-Visual Sound Event Detection in Movies
Rajat Hebbar, Digbalay Bose, Krishna Somandepalli +2
Audio event detection is a widely studied audio processing task, with applications ranging from self-driving cars to healthcare. In-the-wild datasets such as Audioset have propelle…
A Review of Speech-centric Trustworthy Machine Learning: Privacy, Safety, and Fairness
Tiantian Feng, Rajat Hebbar, Nicholas Mehlman +3
Speech-centric machine learning systems have revolutionized many leading domains ranging from transportation and healthcare to education and defense, profoundly changing how people…
MovieCLIP: Visual Scene Recognition in Movies
Digbalay Bose, Rajat Hebbar, Krishna Somandepalli +5
Longform media such as movies have complex narrative structures, with events spanning a rich variety of ambient visual scenes. Domain specific challenges associated with visual sce…
Study of Feature Importance for Quantum Machine Learning Models
Aaron Baughman, Kavitha Yogaraj, Raja Hebbar +3
Predictor importance is a crucial part of data preprocessing pipelines in classical and quantum machine learning (QML). This work presents the first study of its kind in which feat…
Attribute Inference Attack of Speech Emotion Recognition in Federated Learning Settings
Tiantian Feng, Hanieh Hashemi, Rajat Hebbar +2
Speech emotion recognition (SER) processes speech signals to detect and characterize expressed perceived emotions. Many SER application systems often acquire and transmit speech da…
Large Scale Diverse Combinatorial Optimization: ESPN Fantasy Football Player Trades
Aaron Baughman, Daniel Bohm, Micah Forster +9
Even skilled fantasy football managers can be disappointed by their mid-season rosters as some players inevitably fall short of draft day expectations. Team managers can quickly di…
Robust Character Labeling in Movie Videos: Data Resources and Self-supervised Feature Adaptation
Krishna Somandepalli, Rajat Hebbar, Shrikanth Narayanan
Robust face clustering is a vital step in enabling computational understanding of visual character portrayal in media. Face clustering for long-form content is challenging because…