Results 21 to 30 of about 162 (83)
Some Properties of Generalized Gegenbauer Matrix Polynomials
International Journal of Analysis, Volume 2014, Issue 1, 2014., 2014 Various new generalized forms of the Gegenbauer matrix polynomials are introduced using the integral representation method, which allows us to express them in terms of Hermite matrix polynomials. Certain properties for these new generalized Gegenbauer matrix polynomials such as recurrence relations and expansion in terms of Hermite matrix polynomials ...
Ghazala Yasmin, Sivaguru Sritharan
wiley +1 more source
Robot reads ads: Data of the listening test and acoustic analysis
, 2022 Likability scores on a 7-point Likert scale 1 = not likable at all … 7 = very likable Format of the audio file F1/F2/M1/M2_00/01/02/03_original/calm/energetic F1 and F2 - female voices M1 and M2 - male voices Texts in Estonian for synthesis 00 - Olen ...
Indrek Kiissel (14057506) +3 more
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Distinct Prosodic Correlates for Nine Dimensions of Mental Health Symptoms [PDF]
, 2019 People’s lived experience of mental illness often includes symptoms associated with several different conditions. The Brief Symptom Inventory (BSI) is a well validated tool for collecting symptom self-reports that covers nine dimensions: depression ...
Wolters, Maria +2 more
core +2 more sources
Silent Suffering: Using Machine Learning to Measure CEO Depression
Journal of Accounting Research, Volume 63, Issue 2, Page 689-767, May 2025.ABSTRACT We introduce a novel measure of CEO depression by applying machine learning models that analyze vocal acoustic features from CEOs' conference call recordings. Our research was preregistered via the Journal of Accounting Research's registration‐based editorial process. In this study, we validate this measure and examine associated factors.
SUNG‐YUAN (MARK) CHENG +1 more
wiley +1 more source
High‐resolution spectral data predict taxonomic diversity in low diversity grasslands
Ecological Solutions and Evidence, Volume 5, Issue 3, July–September 2024.We tested the spectral variance hypothesis (SVH) in a heterogeneous, species‐rich system using high‐resolution hyperspectral imagery. Our findings indicate that the correlation between spectral and taxonomic diversity varies with spatial resolution and is context‐dependent, particularly in recently burned areas dominated by C3 grasses.
Meghan T. Hayden +5 more
wiley +1 more source
International Journal of Intelligent Systems, Volume 2024, Issue 1, 2024.Background and Objective. Currently, depression is a widespread global issue that imposes a significant burden and disability on individuals, families, and society. Deep learning (DL) has emerged as a valuable approach for automatically detecting depression by extracting cues from audiovisual data and making a diagnosis. PHQ‐8 is considered a validated
Yifu Li +7 more
wiley +1 more source
Clinically Interpretable Acoustic Meta-Features for Characterising the Effect of Mental Illness on Speech and Voice [PDF]
, 2017 A person’s mental health can be reflected in their speech. Recent studies have used machine learning to detect signs of mental illness from hundreds of acoustic features. However, the resulting algorithms can be hard to interpret clinically.
Wolters, Maria +2 more
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Unsupervised Speech Feature Learning Using Autoencoder-Based Neural Network Architectures
, 2018 Nenadzirano učenje značajki i nižedimenzionalnih reprezentacija podataka nalazi primjene u strojnom učenju, kompresiji s gubitkom i sl. Postojeće metode poput analize osnovnih komponenata (PCA) se često baziraju na linearnim transformacijama podataka ...
Murn, Luka
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Feel the Space: Pioneering Emotional Intelligence in Architecture
Our research at the University of Genoa, in collaboration with Accademia Mercantile di Genova, explores the synergy between neuroarchitecture and emotion recognition technologies.
Mario Ivan Zignego +3 more
core +1 more source
Emotion recognition in multimedia content [PDF]
Emotion Recognition (ER) has become crucial in Human-Computer Interaction (HCI), with applications ranging from mental health support to adaptive learning.
Condesso, Sofia Fernandes
core