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Smartphone Application for the Analysis of Prosodic Features in Running Speech with a Focus on Bipolar Disorders: System Performance Evaluation and Case Study
9 references·0 citing·41 second hop
Smartphone Application for the Analysis of Prosodic Features in Running Speech with a Focus on Bipolar Disorders: System Performance Evaluation and Case Study (2015)Smartphone Application for the Analysis o…A review of depression and suicide risk assessment using speech analysis (2015)A review of depression and su…Ecologically valid long-term mood monitoring of individuals with bipolar disorder using speech (2014)Ecologically valid long-term …Speech analysis for mood state characterization in bipolar patients (2012)Speech analysis for mood stat…Personal Health Systems for Mental Health: The European Projects (2011)Personal Health Systems for M…Online Predictive Tools for Intervention in Mental Illness: The OPTIMI Project (2011)Online Predictive Tools for I…Detection of Clinical Depression in Adolescents’ Speech During Family Interactions (2010)Detection of Clinical Depress…Critical Analysis of the Impact of Glottal Features in the Classification of Clinical Depression in Speech (2007)Critical Analysis of the Impa…Voice acoustical measurement of the severity of major depression (2004)Voice acoustical measurement …Investigation of Vocal Jitter and Glottal Flow Spectrum as Possible Cues for Depression and Near-Term Suicidal Risk (2004)Investigation of Vocal Jitter…A RATING SCALE FOR DEPRESSION (1960)Detecting Depression using Vocal, Facial and Semantic Communication Cues (2016)Dynamic Multimodal Measurement of Depression Severity Using Deep Autoencoding (2017)Flexible voices: Identity perception from variable vocal signals (2018)The PHQ-9 (2001)Diagnostic and Statistical Manual of Mental Disorders (2013)Diagnostic and Statistical Manual of Mental Disorders (2013)AVEC 2017 (2017)AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition (2019)Automated assessment of psychiatric disorders using speech: A systematic review (2020)Acoustical properties of speech as indicators of depression and suicidal risk (2000)Voice acoustic measures of depression severity and treatment response collected via interactive voice response (IVR) technology (2006)Praat script to detect syllable nuclei and measure speech rate automatically (2009)Assessing Bipolar Episodes Using Speech Cues Derived from Phone Calls (2014)Detection of major depressive disorder using vocal acoustic analysis and machine learning—an exploratory study (2020)Detection of major depressive disorder, bipolar disorder, schizophrenia and generalized anxiety disorder using vocal acoustic analysis and machine learning: an exploratory study (2022)The Hamilton Rating Scale for Depression (1986)Detecting depression from facial actions and vocal prosody (2009)Using regional saliency for speech emotion recognition (2017)Giving Voice to Vulnerable Children: Machine Learning Analysis of Speech Detects Anxiety and Depression in Early Childhood (2019)Improving Cross-Corpus Speech Emotion Recognition with Adversarial Discriminative Domain Generalization (ADDoG) (2019)Vocal affect expression: A review and a model for future research. (1986)Emotion recognition in human-computer interaction (2001)Prevalence, Severity, and Comorbidity of 12-Month DSM-IV Disorders in the National Comorbidity Survey Replication (2005)An investigation of depressed speech detection: features and normalization (2011)Speech emotion recognition approaches in human computer interaction (2011)Multimodal assistive technologies for depression diagnosis and monitoring (2013)The emergence of gender differences in depression during adolescence. (1994)Major depressive disorder in older adolescents (1998)A survey of speech emotion recognition in natural environment (2020)A hybrid model for depression detection using deep learning (2022)Emotion recognition from unimodal to multimodal analysis: A review (2023)An Inventory for Measuring Depression (1961)Research Diagnostic Criteria (1978)Vocal biomarkers of depression based on motor incoordination (2013)A survey on big data-driven digital phenotyping of mental health (2019)SmartCoping - A Mobile Solution for Stress Recognition and Prevention (2014)Devices, Mobile Health and Digital Phenotyping (2023)Smiling is Fun: A Coping with Stress and Emotion Regulation Program (2012)Un programa de intervención auto-aplicado a través de Internet para el tratamiento de la depresión: “Sonreír es divertido” (2015)Depression and Mood Monitoring for Pregnant Women Using IoT-Based Wearables (2023)
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References

  • 2015A review of depression and suicide risk assessment using speech analysis1,007 cited
  • 2010Detection of Clinical Depression in Adolescents’ Speech During Family Interactions256 cited
  • 2004Voice acoustical measurement of the severity of major depression234 cited
  • 2007Critical Analysis of the Impact of Glottal Features in the Classification of Clinical Depression in Speech220 cited
  • 2004Investigation of Vocal Jitter and Glottal Flow Spectrum as Possible Cues for Depression and Near-Term Suicidal Risk204 cited
  • 2014Ecologically valid long-term mood monitoring of individuals with bipolar disorder using speech140 cited
  • 2012Speech analysis for mood state characterization in bipolar patients67 cited
  • 2011Online Predictive Tools for Intervention in Mental Illness: The OPTIMI Project20 cited
  • 2011Personal Health Systems for Mental Health: The European Projects17 cited

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