Titlebook: Affective Computing and Intelligent Interaction; Second International Ana C. R. Paiva,Rui Prada,Rosalind W. Picard Conference proceedings 2

FRAUD

Time- and Amplitude-Based Voice Source Correlates of Emotional Portrayalsficant differentiation of all emotions in terms of all the glottal parameters analysed. Results furthermore suggest that the dynamics of the individual parameters are likely to be important in differentiating among the emotions.

序曲

Corporate Governance in the United Kingdom was observed on utterance level, the HMM-based approach outperformed static classification on word level. However, setting up general guidelines which kind of models are best suited appeared to be rather difficult.

LAST

https://doi.org/10.1007/978-3-658-11619-4es, whereas Valence was correlated mainly to intensity related features. Further, ANOVA analysis showed some interesting contrasts between the two scales, and interesting differences in the judgments of native vs. non-native English speakers.

AND

強(qiáng)化

pericardium

Characterizing Emotion in the Soundtrack of an Animated Film: Credible or Incredible?es, whereas Valence was correlated mainly to intensity related features. Further, ANOVA analysis showed some interesting contrasts between the two scales, and interesting differences in the judgments of native vs. non-native English speakers.

小溪

ATRIA

Expressive Face Animation Synthesis Based on Dynamic Mapping Methodthe synthesized neutral FAP streams will be extended with expressive variations according to the prosody of the input speech. The quantitative evaluation of the experimental result is encouraging and the synthesized face shows a realistic quality.

GEM

Reconstruction and Recognition of Occluded Facial Expressions Using PCAon of occluded top and bottom halves of faces. The results indicate that occluded-top expressions can be reconstructed with little loss of expression recognition – occluded-bottom expressions are reconstructed less accurately but still give comparable performance to human rates of facial expression recognition.

草率女

Recognising Human Emotions from Body Movement and Gesture Dynamics We propose a method for the analysis of emotional behaviour based on both direct classification of time series and a model that provides indicators describing the dynamics of expressive motion cues. Finally we show and interpret the recognition rates for both proposals using different classification algorithms.