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Mood disorders are inherently related to emotion. In particular, the behaviour of people suffering from mood disorders such as unipolar depression shows a strong temporal correlation with the affective dimensions valence, arousal and dominance. In addition to structured self-report questionnaires, psychologists and psychiatrists use in their evaluation of a(More)
While the first open comparative challenges in the field of paralinguistics targeted more 'conventional' phenomena such as emotion, age, and gender, there still exists a multiplicity of not yet covered, but highly relevant speaker states and traits. The INTERSPEECH 2011 Speaker State Challenge thus addresses two new sub-challenges to overcome the usually(More)
This paper describes a promising sleepiness detection approach based on prosodic and spectral speech characteristics and illustrates the validity of this method by briefly discussing results from a sleep deprivation study (N=20). We conducted a within-subject sleep deprivation design (8.00 p.m to 4.00 a.m). During the night of sleep deprivation, a(More)
In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t Comparing different novel feature sets and classifiers for speech(More)
Alterations in speech motor control in depressed individuals have been found to manifest as a reduction in spectral variability. In this paper we present a novel method for measuring acoustic volume-a model-based measure that is reflective of this decrease in spectral variability-and assess the ability of features resulting from this measure for indexing a(More)
This article describes a general framework for detecting accident-prone fatigue states based on prosody, articulation and speech quality related speech characteristics. The advantages of this real-time measurement approach are that obtaining speech data is non obtrusive, and free from sensor application and calibration efforts. The main part of the feature(More)
The aim of this study is to compare several classifiers commonly used within the field of speech emotion recognition (SER) on the speech based detection of self-confidence. A standard acoustic feature set was computed, resulting in 170 features per one-minute speech sample (e.g. fundamental frequency, intensity, formants, MFCCs). In order to identify speech(More)