| { |
| "field_id": "F013", |
| "field": "affective computing", |
| "directions": [ |
| { |
| "direction_id": "G0", |
| "name": "Visual inference of depicted people's affect", |
| "scope": "Infer individual or group emotions from depicted people's faces, actions, and scene and social context, including joint learning of related facial affect descriptors." |
| }, |
| { |
| "direction_id": "G1", |
| "name": "Affect inference from communicative signals", |
| "scope": "Infer expressed emotion or affect from speech, non-linguistic vocalizations, text, and combined audio, visual, and textual evidence, including the use of conversational relationships and turn context." |
| }, |
| { |
| "direction_id": "G2", |
| "name": "Affect elicited by media", |
| "scope": "Predict or explain the emotional responses that images, videos, memes, art, music, and other content elicit in viewers or listeners, including response distributions and reasons for those responses." |
| }, |
| { |
| "direction_id": "G3", |
| "name": "Monitoring affective and cognitive states", |
| "scope": "Estimate people's emotions and activity-related stress, engagement, attention, fatigue, and cognitive load from physiological, neural, thermal, or behavioral observations." |
| }, |
| { |
| "direction_id": "G4", |
| "name": "Learning with limited or uncertain affect supervision", |
| "scope": "Obtain representations and supervision usable for affect prediction when affect annotations are scarce, ambiguous, or unreliable, and address label disagreement or predictive uncertainty." |
| }, |
| { |
| "direction_id": "G5", |
| "name": "Affect inference across shifts and impaired observations", |
| "scope": "Maintain effective affect inference when populations or corpora change, or when expected affective evidence is missing, occluded, noisy, or degraded." |
| }, |
| { |
| "direction_id": "G6", |
| "name": "Fairness of affective inference", |
| "scope": "Identify or mitigate demographic or other group-dependent bias and unfairness in the inference of affect and related psychological states." |
| }, |
| { |
| "direction_id": "G7", |
| "name": "Explaining emotions through events and roles", |
| "scope": "Link emotions to the events that elicit them, relevant participants, or cognitive appraisals of situations to extract or explain the basis on which emotions arise." |
| }, |
| { |
| "direction_id": "G8", |
| "name": "Emotionally responsive agents", |
| "scope": "Enable interactive agents to reason, provide support or interventions, or respond with embodied affect in light of people's emotions or circumstances." |
| }, |
| { |
| "direction_id": "G9", |
| "name": "Emotion-controlled expressive generation", |
| "scope": "Generate or transform music, speech, images, and facial reactions so that the outputs convey an intended emotion or have an appropriate affective expression." |
| }, |
| { |
| "direction_id": "G10", |
| "name": "Affect research resources and measurement validity", |
| "scope": "Establish annotated data, tasks, and benchmarks for affect research, and examine whether labels, measurements, and evaluation protocols support credible research conclusions." |
| } |
| ] |
| } |
|
|
