23 citations · 39 across the 13 of their papers we have counts for
7 papers · 1 filter
Interpretability by design using computer vision for behavioral sensing in child and adolescent psychiatry
Flavia D. Frumosu, Nicole N. Lønfeldt, A. -R. Cecilie Mora-Jensen +4
Observation is an essential tool for understanding and studying human behavior and mental states. However, coding human behavior is a time-consuming, expensive task, in which relia…
Computational behavior recognition in child and adolescent psychiatry: A statistical and machine learning analysis plan
Nicole N. Lønfeldt, Flavia D. Frumosu, A. -R. Cecilie Mora-Jensen +4
Motivation: Behavioral observations are an important resource in the study and evaluation of psychological phenomena, but it is costly, time-consuming, and susceptible to bias. Thu…
Speech Detection For Child-Clinician Conversations In Danish For Low-Resource In-The-Wild Conditions: A Case Study
Sneha Das, Nicole Nadine Lønfeldt, Anne Katrine Pagsberg +1
Use of speech models for automatic speech processing tasks can improve efficiency in the screening, analysis, diagnosis and treatment in medicine and psychiatry. However, the perfo…
Continuous Metric Learning For Transferable Speech Emotion Recognition and Embedding Across Low-resource Languages
Sneha Das, Nicklas Leander Lund, Nicole Nadine Lønfeldt +2
Speech emotion recognition~(SER) refers to the technique of inferring the emotional state of an individual from speech signals. SERs continue to garner interest due to their wide a…
Towards Transferable Speech Emotion Representation: On loss functions for cross-lingual latent representations
Sneha Das, Nicole Nadine Lønfeldt, Anne Katrine Pagsberg +1
In recent years, speech emotion recognition (SER) has been used in wide ranging applications, from healthcare to the commercial sector. In addition to signal processing approaches,…
Compressing CNN Kernels for Videos Using Tucker Decompositions: Towards Lightweight CNN Applications
Tobias Engelhardt Rasmussen, Line H Clemmensen, Andreas Baum
Convolutional Neural Networks (CNN) are the state-of-the-art in the field of visual computing. However, a major problem with CNNs is the large number of floating point operations (…