multimedia concepts and applications multimedia concepts and applications affect sensing in speech:...
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Multimedia Concepts and Applications Multimedia Concepts and Applications Fusion Decision-level Feature-levelTRANSCRIPT
Multimedia Concepts and Applications
Multimedia Concepts and Applications
Affect Sensing in Speech: Studying Fusion of Linguistic and Acoustic Features
Alexander Osherenko, Elisabeth André, Thurid VogtUniversity of Augsburg
Multimedia Concepts and Applications
Multimedia Concepts and ApplicationsAffect Sensing
• Acoustic information• Linguistic information (lexical, stylometric,
deictic)
Multimedia Concepts and Applications
Multimedia Concepts and ApplicationsFusion
• Decision-level• Feature-level
Multimedia Concepts and Applications
Multimedia Concepts and ApplicationsResearch Questions
• Fusion• Context• Decision-level vs. feature-level
Multimedia Concepts and Applications
Multimedia Concepts and ApplicationsExperimental Setting
• SAL corpus, 574 turns, 5 classes• Decision-level using majority, feature-level –
fusing features• Data: 2 stages (history 0 and history 7)– Acoustic modality - 2 (discrete/continuous)
acoustic datasets (A)– Lingustic modality - 29 lexical (L), 31 stylometric
(S), 63 deictic datasets (D)
Multimedia Concepts and Applications
Multimedia Concepts and Applications
• Tree– Nodes – features from
particular modalities (A, L,S, D)
– Values
• Maximal recall value• Maximal multimodality
value• Dotted arcs
Results‘ representation
Multimedia Concepts and Applications
Multimedia Concepts and Applications
• Best results: 64.2% (history 7) and 44.2% (history 0)
• Significant improvement through context• Insignificant improvement through fusion (about 2%)• Maximal multimodality value (76.5%)
Decision-level Fusion Before Discretization
Multimedia Concepts and Applications
Multimedia Concepts and Applications
• Best results: 66.0% (history 7) and 49.0% (history 0)
• Significant improvement through context• Insignificant improvement through fusion (about 2%)• Maximal multimodality value (77.8%)
Decision-level Fusion After Discretization
Multimedia Concepts and Applications
Multimedia Concepts and Applications
• Best results: 62.8% vs. 64.2% (history 7) and 46.7% vs. 44.2% (history 0)
• Significant improvement through context• Insignificant improvement through fusion (about 2%)
Feature-level Fusion Before Discretization
Multimedia Concepts and Applications
Multimedia Concepts and Applications
Feature-level Fusion After Discretization
• Best results: 67.5% vs. 64.9% (history 7) and 52.8% vs. 45.9% (history 0)
• Significant improvement through context• Insignificant improvement through fusion (about 2%)
Multimedia Concepts and Applications
Multimedia Concepts and ApplicationsDiscussion
• Role of context• Role of discretization• Fusion?
Multimedia Concepts and Applications
Multimedia Concepts and ApplicationsFuture work
• New modalities• Weighting