5 citations · 5 across the 2 of their papers we have counts for
6 papers
CALM: Contrastive Aligned Audio-Language Multirate and Multimodal Representations
Vin Sachidananda, Shao-Yen Tseng, Erik Marchi +2
Deriving multimodal representations of audio and lexical inputs is a central problem in Natural Language Understanding (NLU). In this paper, we present Contrastive Aligned Audio-La…
Automatic prediction of suicidal risk in military couples using multimodal interaction cues from couples conversations
Sandeep Nallan Chakravarthula, Md Nasir, Shao-Yen Tseng +6
Suicide is a major societal challenge globally, with a wide range of risk factors, from individual health, psychological and behavioral elements to socio-economic aspects. Military…
Multimodal Embeddings from Language Models
Shao-Yen Tseng, Panayiotis Georgiou, Shrikanth Narayanan
Word embeddings such as ELMo have recently been shown to model word semantics with greater efficacy through contextualized learning on large-scale language corpora, resulting in si…
Behavior Gated Language Models
Prashanth Gurunath Shivakumar, Shao-Yen Tseng, Panayiotis Georgiou +1
Most current language modeling techniques only exploit co-occurrence, semantic and syntactic information from the sequence of words. However, a range of information such as the sta…
Predicting Behavior in Cancer-Afflicted Patient and Spouse Interactions using Speech and Language
Sandeep Nallan Chakravarthula, Haoqi Li, Shao-Yen Tseng +2
Cancer impacts the quality of life of those diagnosed as well as their spouse caregivers, in addition to potentially influencing their day-to-day behaviors. There is evidence that…
Unsupervised Online Multitask Learning of Behavioral Sentence Embeddings
Shao-Yen Tseng, Brian Baucom, Panayiotis Georgiou
Unsupervised learning has been an attractive method for easily deriving meaningful data representations from vast amounts of unlabeled data. These representations, or embeddings, o…