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In this paper, we report the influence that classification accuracies have in speech analysis from a clinical dataset by adding acoustic low-level descriptors (LLD) belonging to prosodic (i.e. pitch, formants, energy, jitter, shimmer) and spectral features (i.e. spectral flux, centroid, entropy and roll-off) along with their delta (Δ) and delta-delta(More)
A novel method for facial expression recognition from sequences of image frames is described and tested. The expression recognition system is fully automatic, and consists of the following modules: face detection, maximum arousal detection, feature extraction, selection of optimal features, and facial expression recognition. The face detection is based on(More)
We present new methods that extract characteristic features from speech magnitude spectrograms. Two of the presented approaches have been found particularly efficient in the process of automatic stress and emotion classification. In the first approach, the spectrograms are sub-divided into ERB frequency bands and the average energy for each band is(More)
The introduction of Gaussian Mixture Models (GMMs) in the field of speaker verification has led to very good results. This paper illustrates an evolution in state-of-the-art Speaker Verification by highlighting the contribution of recently established information theoretic based vector quantization technique. We explore the novel application of three(More)
We proposed a framework to detect the video contents of depressed and non-depressed subjects. First we characterized the expressed emotions in the video stream using Gabor wavelet features extracted at the facial landmarks which were detected using landmark model matching algorithm. Depressed and non-depressed class models were constructed using Gaussian(More)
The properties of acoustic speech have previously been investigated as possible cues for depression in adults. However, these studies were restricted to small populations of patients and the speech recordings were made during patients' clinical interviews or fixed-text reading sessions. Symptoms of depression often first appear during adolescence at a time(More)
The speech of cleft palate (CP) patients has typical characteristics. Hypernasality and low speech intelligibility are the primary characteristics for CP speech. In this work, an automatic evaluation of different levels of hypernasality and speech intelligibility algorithm for CP speech was proposed, in order to provide an objective tool for speech(More)