Skip to main content
Go to the home page of the European Commission (opens in new window)
English English
CORDIS - EU research results
CORDIS

Emotion Recognition: A Statistical Learning Approach

Project description

Understanding emotion recognition using statistical learning

Some emotions are harder to recognise than others and some individuals, such as those with autism spectrum disorder (ASD), simply find it more difficult to recognise emotions generally. The EU-funded LearningEmotions project will explore whether the two phenomena may arise from a common source, that is, difficulties with learning patterns and their associations (i.e. statistical learning). The project will quantify the variability of cues used to signal emotions from an audio-visual emotion database to compare whether difficult-to-recognise emotions have less consistent patterns than emotions that are easier to recognise. The project will also compare individuals with and without ASD on their ability to recognise emotions and learn patterns to see if the two abilities are related using behavioural and neural methods.

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.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.

You need to log in or register to use this function

Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)

See all projects funded under this funding scheme

Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-MSCA-IF-2019

See all projects funded under this call

Coordinator

THE UNIVERSITY OF READING
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 212 933,76
Address
WHITEKNIGHTS CAMPUS WHITEKNIGHTS HOUSE
RG6 6AH Reading
United Kingdom

See on map

Region
South East (England) Berkshire, Buckinghamshire and Oxfordshire Berkshire
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 212 933,76
My booklet 0 0