Kay L Ritchie
Biographic Data
| ID | 1932151 |
|---|---|
| NAME | Kay L Ritchie |
| GIVEN NAMES | Kay L |
| FAMILY NAME | Ritchie |
| SIGNATURE | RITCHIE K L |
| AFFILIATIONS | University of Lincoln |
| ORCID | 0000-0002-1348-760X |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 4 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Face and voice identity matching accuracy is not improved by multimodal identity information
Identity verification from both faces and voices can be error‐prone. Previous research has shown that faces and voices signal concordant information and cross‐modal unfamiliar face‐to‐voice matching is possible, albeit often with low accuracy. In the current study, we ask whether performance on a face or voice identity matching task can be improved by using multimodal stimuli which add a second modality (voice or face). We find that overall accur…
Having options alters the attractiveness of familiar versus novel faces
Multiple-image arrays in face matching tasks with and without memory
To which world regions does the valence-dominance model of social perception apply
Over the past 10 years, Oosterhof and Todorov’s valence–dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof an…
Face averages and multiple images in a live matching task
We know from previous research that unfamiliar face matching (determining whether two simultaneously presented images show the same person or not) is very error-prone. A small number of studies in laboratory settings have shown that the use of multiple images or a face average, rather than a single image, can improve face matching performance. Here, we tested 1,999 participants using four-image arrays and face averages in two separate live matchi…
Th European Federation for Primatology Meeting
8th European Federation for Primatology Meeting
To which world regions does the valence-dominance model of social perception apply
Over the past 10 years, Oosterhof and Todorov’s valence–dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof an…
Th European Federation for Primatology Meeting
8th European Federation for Primatology Meeting
Face averages and multiple images in a live matching task
We know from previous research that unfamiliar face matching (determining whether two simultaneously presented images show the same person or not) is very error-prone. A small number of studies in laboratory settings have shown that the use of multiple images or a face average, rather than a single image, can improve face matching performance. Here, we tested 1,999 participants using four-image arrays and face averages in two separate live matchi…
Having options alters the attractiveness of familiar versus novel faces
Multiple-image arrays in face matching tasks with and without memory
To which world regions does the valence-dominance model of social perception apply
Over the past 10 years, Oosterhof and Todorov’s valence–dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof an…
Face and voice identity matching accuracy is not improved by multimodal identity information
Identity verification from both faces and voices can be error‐prone. Previous research has shown that faces and voices signal concordant information and cross‐modal unfamiliar face‐to‐voice matching is possible, albeit often with low accuracy. In the current study, we ask whether performance on a face or voice identity matching task can be improved by using multimodal stimuli which add a second modality (voice or face). We find that overall accur…
Psychology (6 works) · Computer Science (4 works) · Evolutionary Psychology and Human Behavior (4 works) · Face Recognition and Perception (4 works) · Mathematics (4 works) · Cognitive psychology (3 works) · Face (sociological concept) (3 works) · Matching (statistics) (3 works) · Perception (3 works) · Artificial Intelligence (2 works)