Angèle Brunellière

The Interpersonal Reactivity Index (IRI) is one of the most used self-report measures of empathy, comprising 4 factors assessing both cognitive and affective empathy. Nowadays, three different French adaptations of this instrument co-exist. This research compares the three French adaptations of the IRI scale using both quantitative and qualitative evaluations. In Study 1, a French-speaking sample (N = 339) completed all three French IRI versions at 2-month time intervals in a counterbalanced order. In Study 2, the item wording of the three versions was evaluated by six independent professional translators. Study 1 assessed the items’ distribution, the scale’s factorial structure, the subscales’ internal consistency, and their correlations with alternative measures of empathy (the Empathy Quotient) and other clinically relevant indicators (anxiety, depression). These quantitative analyses highlighted that all three French adaptations can be used for research purposes. They all exhibit acceptable internal consistency, a factorial structure compliant with the 4-factor model originally proposed by Davis, as well as convergent and discriminant validity. However, by combining item quantitative analyses and translators’ judgments, we revealed some problematic items in each version. Taken together, the findings suggest that the French IRI adaptations by Guttman & Laporte (2000) and Braun et al. (2015) should be slightly preferred. To improve the overall quality of each French IRI version, we provide some recommendations about how to adapt problematic items.

Recent work on predicting category structure with distributional models, using either static word embeddings (Heyman and Heyman, 2019) or contextualized language models (CLMs) (Misra et al., 2021), report low correlations with human ratings, thus calling into question their plausibility as models of human semantic memory. In this work, we revisit this question testing a wider array of methods for probing CLMs for predicting typicality scores. Our experiments, using BERT (Devlin et al., 2018), show the importance of using the right type of CLM probes, as our best BERT-based typicality prediction methods substantially improve over previous works. Second, our results highlight the importance of polysemy in this task: our best results are obtained when using a disambiguation mechanism. Finally, additional experiments reveal that Information Contentbased WordNet (Miller, 1995), also endowed with disambiguation, match the performance of the best BERT-based method, and in fact capture complementary information, which can be combined with BERT to achieve enhanced typicality predictions.

Joseph Renner, Pascal Denis, Remi Gilleron, Angèle Brunellière. Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics. 2023.

Tangram pictures are abstract pictures which may be used as stimuli in various fields of experimental psychology and are often used in the field of dialogu

Background: Stroke may cause sentence comprehension disorders. Speech segmentation, i.e. the ability to detect word boundaries while listening to continuous speech, is an initial step allowing the successful identification of words and the accurate understanding of meaning within sentences. It has received little attention in people with post-stroke aphasia (PWA). Objectives: Our goal was to study speech segmentation in PWA and examine the potential benefit of seeing the speakers’ articulatory gestures while segmenting sentences. Methods: Fourteen PWA and twelve healthy controls participated in this pilot study. Performance was measured with a word-monitoring task. In the auditory-only modality, participants were presented with auditory-only stimuli while in the audiovisual modality, visual speech cues (i.e. speaker’s articulatory gestures) accompanied the auditory input. The proportion of correct responses was calculated for each participant and each modality. Visual enhancement was then calculated in order to estimate the potential benefit of seeing the speaker’s articulatory gestures. Results: Both in auditory-only and audiovisual modalities, PWA performed significantly less well than controls, who had 100% correct performance in both modalities. The performance of PWA was correlated with their phonological ability. Six PWA used the visual cues. Group level analysis performed on PWA did not show any reliable difference between the auditory-only and audiovisual modalities (median of visual enhancement = 7% [Q1 − Q3: −5 − 39]). Conclusion: Our findings show that speech segmentation disorder may exist in PWA. This points to the importance of assessing and training speech segmentation after stroke. Further studies should investigate the characteristics of PWA who use visual speech cues during sentence processing.