122 citations · 258 across the 19 of their papers we have counts for
6 papers · 1 filter
Detecting expressions with multimodal transformers
Srinivas Parthasarathy, Shiva Sundaram
Developing machine learning algorithms to understand person-to-person engagement can result in natural user experiences for communal devices such as Amazon Alexa. Among other cues…
Training Strategies to Handle Missing Modalities for Audio-Visual Expression Recognition
Srinivas Parthasarathy, Shiva Sundaram
Automatic audio-visual expression recognition can play an important role in communication services such as tele-health, VOIP calls and human-machine interaction. Accuracy of audio-…
Self-Supervised learning with cross-modal transformers for emotion recognition
Aparna Khare, Srinivas Parthasarathy, Shiva Sundaram
Emotion recognition is a challenging task due to limited availability of in-the-wild labeled datasets. Self-supervised learning has shown improvements on tasks with limited labeled…
Multi-modal embeddings using multi-task learning for emotion recognition
Aparna Khare, Srinivas Parthasarathy, Shiva Sundaram
General embeddings like word2vec, GloVe and ELMo have shown a lot of success in natural language tasks. The embeddings are typically extracted from models that are built on general…
Multiresolution and Multimodal Speech Recognition with Transformers
Georgios Paraskevopoulos, Srinivas Parthasarathy, Aparna Khare +1
This paper presents an audio visual automatic speech recognition (AV-ASR) system using a Transformer-based architecture. We particularly focus on the scene context provided by the…
M2: Mixed Models with Preferences, Popularities and Transitions for Next-Basket Recommendation
Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy +1
Next-basket recommendation considers the problem of recommending a set of items into the next basket that users will purchase as a whole. In this paper, we develop a novel mixed mo…