A review of detection techniques for depression and bipolar disorder
D Highland, G Zhou - Smart Health, 2022 - Elsevier
Depression and bipolar disorder are mood disorders affecting millions of people worldwide
that can have severe impacts on one's quality of life. Our ability to detect these illnesses is …
that can have severe impacts on one's quality of life. Our ability to detect these illnesses is …
An engineering view on emotions and speech: From analysis and predictive models to responsible human-centered applications
The substantial growth of Internet-of-Things technology and the ubiquity of smartphone
devices has increased the public and industry focus on speech emotion recognition (SER) …
devices has increased the public and industry focus on speech emotion recognition (SER) …
AVEC 2018 workshop and challenge: Bipolar disorder and cross-cultural affect recognition
The Audio/Visual Emotion Challenge and Workshop (AVEC 2018)" Bipolar disorder, and
cross-cultural affect recognition''is the eighth competition event aimed at the comparison of …
cross-cultural affect recognition''is the eighth competition event aimed at the comparison of …
Improving cross-corpus speech emotion recognition with adversarial discriminative domain generalization (ADDoG)
Automatic speech emotion recognition provides computers with critical context to enable
user understanding. While methods trained and tested within the same dataset have been …
user understanding. While methods trained and tested within the same dataset have been …
Detecting unipolar and bipolar depressive disorders from elicited speech responses using latent affective structure model
Mood disorders, including unipolar depression (UD) and bipolar disorder (BD)[1], are
reported to be one of the most common mental illnesses in recent years. In diagnostic …
reported to be one of the most common mental illnesses in recent years. In diagnostic …
The priori emotion dataset: Linking mood to emotion detected in-the-wild
Bipolar Disorder is a chronic psychiatric illness characterized by pathological mood swings
associated with severe disruptions in emotion regulation. Clinical monitoring of mood is key …
associated with severe disruptions in emotion regulation. Clinical monitoring of mood is key …
A multi-modal stacked ensemble model for bipolar disorder classification
N AbaeiKoupaei, H Al Osman - IEEE Transactions on Affective …, 2020 - ieeexplore.ieee.org
We propose an automatic ternary classification model for Bipolar Disorder (BD) states. As
input information, the model uses speech signals from patients' audio-visual recordings of …
input information, the model uses speech signals from patients' audio-visual recordings of …
Automatic speech-based longitudinal emotion and mood recognition for mental health treatment
(57) ABSTRACT A method of predicting a mood state of a user may include recording an
audio sample via a microphone of a mobile computing device of the user based on the …
audio sample via a microphone of a mobile computing device of the user based on the …
Into the wild: Transitioning from recognizing mood in clinical interactions to personal conversations for individuals with bipolar disorder
Bipolar Disorder, a mood disorder with recurrent mania and depression, requires ongoing
monitoring and specialty management. Current monitoring strategies are clinically-based …
monitoring and specialty management. Current monitoring strategies are clinically-based …
Speech variability: A cross-language study on acoustic variations of speaking versus untrained singing
JHL Hansen, M Bokshi… - The Journal of the …, 2020 - pmc.ncbi.nlm.nih.gov
Speech production variability introduces significant challenges for existing speech
technologies such as speaker identification (SID), speaker diarization, speech recognition …
technologies such as speaker identification (SID), speaker diarization, speech recognition …