2 citations · 6 across the 9 of their papers we have counts for
9 papers
The Cost-Benefit of Interdisciplinarity in AI for Mental Health
Katerina Drakos, Eva Paraschou, Simay Toplu +4
Artificial intelligence has been introduced as a way to improve access to mental health support. However, most AI mental health chatbots rely on a limited range of disciplinary inp…
Evaluation of Stress Detection as Time Series Events -- A Novel Window-Based F1-Metric
Harald Vilhelm Skat-Rørdam, Sneha Das, Kathrine Sofie Rasmussen +2
Accurate evaluation of event detection in time series is essential for applications such as stress monitoring with wearable devices, where ground truth is typically annotated as si…
Applying Pre-Trained Deep-Learning Model on Wrist Angel Data -- An Analysis Plan
Harald Vilhelm Skat-Rørdam, Mia Hang Knudsen, Simon Nørby Knudsen +3
We aim to investigate if we can improve predictions of stress caused by OCD symptoms using pre-trained models, and present our statistical analysis plan in this paper. With the met…
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,…
Towards Interpretable and Transferable Speech Emotion Recognition: Latent Representation Based Analysis of Features, Methods and Corpora
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,…