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GTC ON-DEMAND

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Abstract:
Autonomous vehicles will require in-cabin sensing to respond to user activities and emotional states. This session will provide an overview of Affectiva's Emotion AI technology to redefine the in-cabin experience. We will describe the progression of unimodal analysis of face and voice emotions to the fusion of these modalities to detect affective states, such as frustration. This process employs techniques such as deep learning-based spatio-temporal modeling, in addition to large-scale natural datasets -- made larger still by cross-domain augmentation -- to develop AI systems that can detect these affective states.
Autonomous vehicles will require in-cabin sensing to respond to user activities and emotional states. This session will provide an overview of Affectiva's Emotion AI technology to redefine the in-cabin experience. We will describe the progression of unimodal analysis of face and voice emotions to the fusion of these modalities to detect affective states, such as frustration. This process employs techniques such as deep learning-based spatio-temporal modeling, in addition to large-scale natural datasets -- made larger still by cross-domain augmentation -- to develop AI systems that can detect these affective states.  Back
 
Topics:
Autonomous Vehicles, Deep Learning & AI Frameworks, AI Application, Deployment & Inference
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9466
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