most citedUnderstanding Spoken Language Development of Children with ASD Using Pre-trained Speech Embeddings

2 citations · 7 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20231 cited

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…

eess.AS20231 cited

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…

eess.AS20232 cited

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…

cs.SD20232 cited

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…

cs.CV2023

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…

eess.AS20231 cited

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…