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LearningEmotions SIGNED

Emotion Recognition: A Statistical Learning Approach

Total Cost €


EC-Contrib. €






Project "LearningEmotions" data sheet

The following table provides information about the project.


Organization address
postcode: RG6 6AH

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 212˙933 €
 EC max contribution 212˙933 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2019
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2020
 Duration (year-month-day) from 2020-04-01   to  2022-03-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE UNIVERSITY OF READING UK (READING) coordinator 212˙933.00


 Project objective

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.

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The information about "LEARNINGEMOTIONS" are provided by the European Opendata Portal: CORDIS opendata.

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