97 citations · 258 across the 12 of their papers we have counts for
13 papers
LanSER: Language-Model Supported Speech Emotion Recognition
Taesik Gong, Josh Belanich, Krishna Somandepalli +3
Speech emotion recognition (SER) models typically rely on costly human-labeled data for training, making scaling methods to large speech datasets and nuanced emotion taxonomies dif…
Multitask vocal burst modeling with ResNets and pre-trained paralinguistic Conformers
Josh Belanich, Krishna Somandepalli, Brian Eoff +1
This technical report presents the modeling approaches used in our submission to the ICML Expressive Vocalizations Workshop & Competition multitask track (ExVo-MultiTask). We first…
BasisNet: Two-stage Model Synthesis for Efficient Inference
Mingda Zhang, Chun-Te Chu, Andrey Zhmoginov +6
In this work, we present BasisNet which combines recent advancements in efficient neural network architectures, conditional computation, and early termination in a simple new form.…
DISSECT: Disentangled Simultaneous Explanations via Concept Traversals
Asma Ghandeharioun, Been Kim, Chun-Liang Li +3
Explaining deep learning model inferences is a promising venue for scientific understanding, improving safety, uncovering hidden biases, evaluating fairness, and beyond, as argued…
Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data Bias
Asma Ghandeharioun, Brian Eoff, Brendan Jou +1
Supporting model interpretability for complex phenomena where annotators can legitimately disagree, such as emotion recognition, is a challenging machine learning task. In this wor…
More cat than cute? Interpretable Prediction of Adjective-Noun Pairs
Delia Fernandez, Alejandro Woodward, Victor Campos +3
The increasing availability of affect-rich multimedia resources has bolstered interest in understanding sentiment and emotions in and from visual content. Adjective-noun pairs (ANP…