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AVEC 2017: Real-life Depression, and Affect Recognition Workshop and Challenge
The Audio/Visual Emotion Challenge and Workshop (AVEC 2017) "Real-life depression, and affect" will be the seventh competition event aimed at comparison of multimedia processing and machine learningExpand
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A review of depression and suicide risk assessment using speech analysis
Review of current diagnostic and assessment methods for depression and suicidality.Review the characteristics of active depressed and suicidal speech databases.Discuss the effects of depression andExpand
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AVEC 2018 Workshop and Challenge: Bipolar Disorder and Cross-Cultural Affect Recognition
The Audio/Visual Emotion Challenge and Workshop (AVEC 2018) "Bipolar disorder, and cross-cultural affect recognition'' is the eighth competition event aimed at the comparison of multimedia processingExpand
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Snore Sound Classification Using Image-Based Deep Spectrum Features
In this paper, we propose a method for automatically detecting various types of snore sounds using image classification convolutional neural network (CNN) descriptors extracted from audio fileExpand
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An Investigation of Depressed Speech Detection: Features and Normalization
In recent years, the problem of automatic detection of mental illness from the speech signal has gained some initial interest, however questions remaining include how speech segments should beExpand
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Diagnosis of depression by behavioural signals: a multimodal approach
Quantifying behavioural changes in depression using affective computing techniques is the first step in developing an objective diagnostic aid, with clinical utility, for clinical depression. As partExpand
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auDeep: Unsupervised Learning of Representations from Audio with Deep Recurrent Neural Networks
auDeep is a Python toolkit for deep unsupervised representation learning from acoustic data. It is based on a recurrent sequence to sequence autoencoder approach which can learn representations ofExpand
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Analysis of acoustic space variability in speech affected by depression
Present novel probabilistic acoustic volume, a robust acoustic variability measure.As depression increases phonetic events become concentrated in acoustic space.MFCC feature space becomes tightlyExpand
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The University of Passau Open Emotion Recognition System for the Multimodal Emotion Challenge
This paper presents the University of Passau’s approaches for the Multimodal Emotion Recognition Challenge 2016. For audio signals, we exploit Bag-of-Audio-Words techniques combining Extreme LearningExpand
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Speech analysis for health: Current state-of-the-art and the increasing impact of deep learning.
Due to the complex and intricate nature associated with their production, the acoustic-prosodic properties of a speech signal are modulated with a range of health related effects. There is an activeExpand
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