Modeling spectral variability for the classification of depressed speech
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Roland Göcke | Michael Breakspear | Vidhyasaharan Sethu | Nicholas Cummins | Julien Epps | M. Breakspear | Roland Göcke | J. Epps | N. Cummins | V. Sethu
[1] Michael Wagner,et al. From Joyous to Clinically Depressed: Mood Detection Using Spontaneous Speech , 2012, FLAIRS.
[2] Roland Göcke,et al. An Investigation of Depressed Speech Detection: Features and Normalization , 2011, INTERSPEECH.
[3] William M. Campbell. A covariance kernel for svm language recognition , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.
[4] Nicholas Cummins,et al. A Comparison of Classification Paradigms for Speaker Likeability Determination , 2012, INTERSPEECH.
[5] M. Landau. Acoustical Properties of Speech as Indicators of Depression and Suicidal Risk , 2008 .
[6] Nicholas B. Allen,et al. Influence of acoustic low-level descriptors in the detection of clinical depression in adolescents , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.
[7] Thomas F. Quatieri,et al. Vocal-Source Biomarkers for Depression: A Link to Psychomotor Activity , 2012, INTERSPEECH.
[8] D. Mitchell Wilkes,et al. Acoustical properties of speech as indicators of depression and suicidal risk , 2000, IEEE Transactions on Biomedical Engineering.
[9] Douglas A. Reynolds,et al. Speaker Verification Using Adapted Gaussian Mixture Models , 2000, Digit. Signal Process..
[10] Shrikanth S. Narayanan,et al. Automatic speaker age and gender recognition using acoustic and prosodic level information fusion , 2013, Comput. Speech Lang..
[11] J. Markowitz,et al. The 16-Item quick inventory of depressive symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression , 2003, Biological Psychiatry.
[12] Margaret Lech,et al. Effect of Clinical Depression on Automatic Speaker Identification , 2009, 2009 3rd International Conference on Bioinformatics and Biomedical Engineering.
[13] Roland Göcke,et al. An approach for automatically measuring facial activity in depressed subjects , 2009, 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops.
[14] M. Thase,et al. Psychiatric rating scales. , 2012, Handbook of clinical neurology.
[15] Eliathamby Ambikairajah,et al. Spectro-temporal analysis of speech affected by depression and psychomotor retardation , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[16] Shrikanth S. Narayanan,et al. Intoxicated speech detection: A fusion framework with speaker-normalized hierarchical functionals and GMM supervectors , 2014, Comput. Speech Lang..
[17] D. Mitchell Wilkes,et al. Investigation of vocal jitter and glottal flow spectrum as possible cues for depression and near-term suicidal risk , 2004, IEEE Transactions on Biomedical Engineering.
[18] M. Alpert,et al. Reflections of depression in acoustic measures of the patient's speech. , 2001, Journal of affective disorders.
[19] Douglas A. Reynolds,et al. Robust text-independent speaker identification using Gaussian mixture speaker models , 1995, IEEE Trans. Speech Audio Process..
[20] Eliathamby Ambikairajah,et al. Using clustering comparison measures for speaker recognition , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[21] Björn W. Schuller,et al. Medium-term speaker states - A review on intoxication, sleepiness and the first challenge , 2014, Comput. Speech Lang..
[22] Robert T. Wertz,et al. Apraxia of speech in adults: The disorder and its management , 1984 .
[23] Björn W. Schuller,et al. Paralinguistics in speech and language - State-of-the-art and the challenge , 2013, Comput. Speech Lang..
[24] M. Swerts,et al. Verbal and Nonverbal Correlates for Depression: A Review , 2012 .
[25] J. Mundt,et al. Vocal Acoustic Biomarkers of Depression Severity and Treatment Response , 2012, Biological Psychiatry.
[26] H. Sackeim,et al. Psychomotor symptoms of depression. , 1997, The American journal of psychiatry.
[27] J. Mundt,et al. Voice acoustic measures of depression severity and treatment response collected via interactive voice response (IVR) technology , 2007, Journal of Neurolinguistics.
[28] Douglas E. Sturim,et al. Automatic Detection of Depression in Speech Using Gaussian Mixture Modeling with Factor Analysis , 2011, INTERSPEECH.
[29] Björn Schuller,et al. Opensmile: the munich versatile and fast open-source audio feature extractor , 2010, ACM Multimedia.
[30] Björn W. Schuller,et al. Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge , 2011, Speech Commun..
[31] Thomas F. Quatieri,et al. Phonologically-based biomarkers for major depressive disorder , 2011, EURASIP J. Adv. Signal Process..
[32] John H. L. Hansen,et al. A Study on Universal Background Model Training in Speaker Verification , 2011, IEEE Transactions on Audio, Speech, and Language Processing.