LearningEmotions · Emotion Recognition: A Statistical Learning Approach
„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“
- Период
- 2021-01-04 → 2023-01-03
- Финансиране от ЕС
- 212 934 €
- Участници
- 1
- Схема
- MSCA-IF
Линиите свързват координатора с партньорите.
Накратко на български
Разпознаването на емоциите се изследва чрез анализ на това как хората учат модели и връзки, например защо някои чувства са по-трудни за разпознаване от други. Това помага да се разбере обработката на емоциите и да се създадат по-добри методи за подкрепа на аутистичните хора.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Резултати накратко
Emotion Recognition: A Statistical Learning Approach
The LearningEmotions project attempted to address two questions: (i) Why are some emotions harder to recognise than others? and (ii) Why do some individuals, such as autistic individuals, have more difficulty recognising emotions generally? Specifically, I examined whether the two questions may actually arise from a common source, that is, difficulties with learning patterns and their associations (i.e., statistical learning). Examining these two questions is key to further our understanding of emotion processing and may provide valuable insight in designing interventions for autistic individuals.
Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз
Цел на проекта
Statistical learning refers to the ability to learn through the discovery of patterns and structures. I propose to investigate emotion recognition using a statistical learning perspective in order to understand (i) why some emotions are harder to recognise than others; and (ii) why individuals with autism spectrum disorder (ASD individuals) have more difficulty recognising emotions than neurotypicals (i.e., individuals without autism).I argue that part of the difficulty in recognising certain emotions lies in how reliable or consistent the auditory and visual cues are in signalling the emotion. That is, if particular cues consistently signal or have a high probability of signalling an emotion (e.g., 'happy' is consistently signaled by squinty eyes and grin/smile), then that emotion would be easier to recognise than emotions that are signalled by inconsistent cues (e.g., sarcasm may have varied expressions depending on the individual, context, etc. and so sarcasm would be more difficult to recognise). To investigate this, I will use an audio-visual emotion database that is currently under development to quantify the variability of cues across speakers in signalling the intended emotion.I propose that the difficulty ASD individuals have with recognising emotions lies in a general difficulty with consolidating probabilistic information. In terms of emotion recognition, this would manifest as a difficulty with making a correct inference of the intended emotion given particular cues, which vary in their probabilities in signalling the emotion. To investigate this hypothesis, I will conduct a behavioural and a neural experiment comparing ASD individuals with neurotypicals on probabilistic learning to determine whether group differences exist and whether probabilistic learning is related to emotion recognition.Outcomes of this project may inform intervention practices for ASD individuals and provide a general framework of understanding other ASD characteristics.
Оригинален текст от CORDIS (на английски).
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Връзки
Данни: CORDIS, © Европейски съюз