12 citations · 23 across the 8 of their papers we have counts for
8 papers
An empirical analysis of information encoded in disentangled neural speaker representations
Raghuveer Peri, Haoqi Li, Krishna Somandepalli +2
The primary characteristic of robust speaker representations is that they are invariant to factors of variability not related to speaker identity. Disentanglement of speaker repres…
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…
Speaker-invariant Affective Representation Learning via Adversarial Training
Haoqi Li, Ming Tu, Jing Huang +2
Representation learning for speech emotion recognition is challenging due to labeled data sparsity issue and lack of gold standard references. In addition, there is much variabilit…
Linking emotions to behaviors through deep transfer learning
Haoqi Li, Brian Baucom, Panayiotis Georgiou
Human behavior refers to the way humans act and interact. Understanding human behavior is a cornerstone of observational practice, especially in psychotherapy. An important cue of…
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…
Learning from Past Mistakes: Improving Automatic Speech Recognition Output via Noisy-Clean Phrase Context Modeling
Prashanth Gurunath Shivakumar, Haoqi Li, Kevin Knight +1
Automatic speech recognition (ASR) systems often make unrecoverable errors due to subsystem pruning (acoustic, language and pronunciation models); for example pruning words due to…
Unsupervised Latent Behavior Manifold Learning from Acoustic Features: audio2behavior
Haoqi Li, Brian Baucom, Panayiotis Georgiou
Behavioral annotation using signal processing and machine learning is highly dependent on training data and manual annotations of behavioral labels. Previous studies have shown tha…
Sparsely Connected and Disjointly Trained Deep Neural Networks for Low Resource Behavioral Annotation: Acoustic Classification in Couples' Therapy
Haoqi Li, Brian Baucom, Panayiotis Georgiou
Observational studies are based on accurate assessment of human state. A behavior recognition system that models interlocutors' state in real-time can significantly aid the mental…