Publication date: Available online 21 September 2018Source: Speech CommunicationAuthor(s): Shaoling Jing, Xia Mao, Lijiang Chen, Maria Colomba Comes, Arianna Mencattini, Grazia Raguso, Fabien Ringeval, Björn Schuller, Corrado Di Natale, Eugenio MartinelliAbstractTime-continuous emotion estimation (e. g., arousal and valence) from spontaneous speech expressions has recently drawn increasing commercial attention. However, real-life applications of emotion recognition technology require challenging conditions, such as noise from recording devices and background environments. In this work, we introduce a novel personalized emotion prediction model validated in different noisy environments. It is performed by a three-level noise reduction algorithm: (i) data downsampling, (ii) feature synchro...
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Σάββατο 22 Σεπτεμβρίου 2018
A Closed-form Solution to the Graph Total Variation Problem for Continuous Emotion Profiling in Noisy Environment
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