Part of the toolkit of language researchers is formed of stimuli that have been rated on various dimensions. The current study presents modality exclusivity norms for 336 properties and 411 concepts in Dutch. Forty-two respondents rated the auditory, haptic, and visual strength of these words. Mean scores were then computed, yielding acceptable reliability values. Measures of modality exclusivity and perceptual strength were also computed. Furthermore, the data includes psycholinguistic variables from other corpora, covering length (e.g., number of phonemes), frequency (e.g., contextual diversity), and distinctiveness (e.g., number of orthographic neighbours), along with concreteness and age of acquisition. To test these norms, Lynott and Connell's (2009, 2013) analyses were replicated. First, unimodal, bimodal, and tri-modal words were found. Vision was the most prevalent modality. Vision and touch were relatively related, leaving a more independent auditory modality. Properties were more strongly perceptual than concepts. Last, sound symbolism was investigated using regression, which revealed that auditory strength predicted lexical properties of the words better than the other modalities did, or else with a different direction. All the data and analysis code, including a web application, are available from https://osf.io/brkjw.
Bernabeu, P. (2018). Dutch modality exclusivity norms for 336 properties and 411 concepts. PsyArXiv. https://doi.org/10.31234/osf.io/s2c5h
Anderson, A. J., Binder, J. R., Fernandino, L., Humphries, C. J., Conant, L. L., Aguilar, M., Wang, X., Doko, D., & Raizada, R. D. S. (2016). Predicting Neural Activity Patterns Associated with Sentences Using a Neurobiologically Motivated Model of Semantic Representation. Cerebral Cortex, cercor;bhw240v1. https://doi.org/10.1093/cercor/bhw240
Anderson, A. J., Binder, J. R., Fernandino, L., Humphries, C. J., Conant, L. L., Raizada, R. D. S., Lin, F., & Lalor, E. C. (2019). An Integrated Neural Decoder of Linguistic and Experiential Meaning. The Journal of Neuroscience, 39(45), 8969–8987. https://doi.org/10.1523/JNEUROSCI.2575-18.2019
Anderson, A. J., & Lin, F. (2019). How pattern information analyses of semantic brain activity elicited in language comprehension could contribute to the early identification of Alzheimer's Disease. NeuroImage: Clinical, 22, 101788. https://doi.org/10.1016/j.nicl.2019.101788
Bagli, M. (2023). How to Point with Language: English Source-Based Language to Describe Taste Qualities. Lublin Studies in Modern Languages and Literature, 42(2), 31–46. https://doi.org/10.17951/lsmll.2023.47.2.31-46
Banks, B., Borghi, A. M., Fargier, R., Fini, C., Jonauskaite, D., Mazzuca, C., Montalti, M., Villani, C., & Woodin, G. (2023). Consensus Paper: Current Perspectives on Abstract Concepts and Future Research Directions. Journal of Cognition, 6(1), 62. https://doi.org/10.5334/joc.238
Bolognesi, M., Burgers, C., & Caselli, T. (2020). On abstraction: Decoupling conceptual concreteness and categorical specificity. Cognitive Processing, 21(3), 365–381. https://doi.org/10.1007/s10339-020-00965-9
Borghi, A. M., Mazzuca, C., Gervasi, A. M., Mannella, F., & Tummolini, L. (2023). Grounded cognition can be multimodal all the way down. Language, Cognition and Neuroscience, 1–5. https://doi.org/10.1080/23273798.2023.2210238
Bottini, R., Morucci, P., D'Urso, A., Collignon, O., & Crepaldi, D. (2022). The concreteness advantage in lexical decision does not depend on perceptual simulations. Journal of Experimental Psychology: General, 151(3), 731–738. https://doi.org/10.1037/xge0001090
Bruffaerts, R., De Deyne, S., Meersmans, K., Liuzzi, A. G., Storms, G., & Vandenberghe, R. (2019). Redefining the resolution of semantic knowledge in the brain: Advances made by the introduction of models of semantics in neuroimaging. Neuroscience & Biobehavioral Reviews, 103, 3–13. https://doi.org/10.1016/j.neubiorev.2019.05.015
Caballero, R., & Paradis, C. (2020). Soundscapes in English and Spanish: A corpus investigation of verb constructions. Language and Cognition, 12(4), 705–728. https://doi.org/10.1017/langcog.2020.19
Caballero, R., & Paradis, C. (2023). Sharing Perceptual Experiences through Language. Journal of Intelligence, 11(7), 129. https://doi.org/10.3390/jintelligence11070129
Calzavarini, F. (2023). Rethinking modality-specificity in the cognitive neuroscience of concrete word meaning: A position paper. Language, Cognition and Neuroscience, 1–23. https://doi.org/10.1080/23273798.2023.2173789
Carney, J. (2020). Thinking avant la lettre: A Review of 4E Cognition. Evolutionary Studies in Imaginative Culture, 4(1), 77–90. https://doi.org/10.26613/esic.4.1.172
Charmhun Jo, Sun-A Kim, & Chu-Ren Huang. (2022). Linguistic synesthesia in Korean: A compound word-based study of cross-modal directionality. Linguistic Research, 39(2), 275–296. https://doi.org/10.17250/KHISLI.39.2.202206.002
Chedid, G., Brambati, S. M., Bedetti, C., Rey, A. E., Wilson, M. A., & Vallet, G. T. (2019). Visual and auditory perceptual strength norms for 3,596 French nouns and their relationship with other psycholinguistic variables. Behavior Research Methods, 51(5), 2094–2105. https://doi.org/10.3758/s13428-019-01254-w
Chedid, G., Wilson, M. A., Bedetti, C., Rey, A. E., Vallet, G. T., & Brambati, S. M. (2019). Norms of conceptual familiarity for 3,596 French nouns and their contribution in lexical decision. Behavior Research Methods, 51(5), 2238–2247. https://doi.org/10.3758/s13428-018-1106-8
Chen, I.-H., Zhao, Q., Long, Y., Lu, Q., & Huang, C.-R. (2019). Mandarin Chinese modality exclusivity norms. PLOS ONE, 14(2), e0211336. https://doi.org/10.1371/journal.pone.0211336
Connell, L. (2019). What have labels ever done for us? The linguistic shortcut in conceptual processing. Language, Cognition and Neuroscience, 34(10), 1308–1318. https://doi.org/10.1080/23273798.2018.1471512
Connell, L., Lynott, D., & Banks, B. (2018). Interoception: The forgotten modality in perceptual grounding of abstract and concrete concepts. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1752), 20170143. https://doi.org/10.1098/rstb.2017.0143
Corciulo, S., Bioglio, L., Basile, V., Patti, V., & Damiano, R. (2023). The DEEP Sensorium: A multidimensional approach to sensory domain labelling. Companion Proceedings of the ACM Web Conference 2023, 661–668. https://doi.org/10.1145/3543873.3587631
Davis, C. P., & Yee, E. (2021). Building semantic memory from embodied and distributional language experience. WIREs Cognitive Science, 12(5), e1555. https://doi.org/10.1002/wcs.1555
De Deyne, S., Navarro, D. J., Perfors, A., Brysbaert, M., & Storms, G. (2019). The “Small World of Words” English word association norms for over 12,000 cue words. Behavior Research Methods, 51(3), 987–1006. https://doi.org/10.3758/s13428-018-1115-7
Dellantonio, S., & Pastore, L. (2017). The ‘Proprioceptive’ Component of Abstract Concepts. In S. Dellantonio & L. Pastore, Internal Perception (Vol. 40, pp. 297–357). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-55763-1_6
Díez-Álamo, A. M., Díez, E., Alonso, M. Á., Vargas, C. A., & Fernandez, A. (2018). Normative ratings for perceptual and motor attributes of 750 object concepts in Spanish. Behavior Research Methods, 50(4), 1632–1644. https://doi.org/10.3758/s13428-017-0970-y
Díez-Álamo, A. M., Díez, E., Wojcik, D. Z., Alonso, M. A., & Fernandez, A. (2019). Sensory experience ratings for 5,500 Spanish words. Behavior Research Methods, 51(3), 1205–1215. https://doi.org/10.3758/s13428-018-1057-0
Dove, G. (2021). The Challenges of Abstract Concepts. In M. D. Robinson & L. E. Thomas (Eds.), Handbook of Embodied Psychology (pp. 171–195). Springer International Publishing. https://doi.org/10.1007/978-3-030-78471-3_8
Dymarska, A., Connell, L., & Banks, B. (2023). More is not necessarily better: How different aspects of sensorimotor experience affect recognition memory for words. Journal of Experimental Psychology: Learning, Memory, and Cognition, 49(10), 1572–1587. https://doi.org/10.1037/xlm0001265
Fischer, M. H., & Shaki, S. (2018). Number concepts: Abstract and embodied. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1752), 20170125. https://doi.org/10.1098/rstb.2017.0125
Fishman, A. (2022). The picture looks like my music sounds: Directional preferences in synesthetic metaphors in the absence of lexical factors. Language and Cognition, 14(2), 208–227. https://doi.org/10.1017/langcog.2022.2
Gangemi, A. (2020). Closing the Loop between knowledge patterns in cognition and the Semantic Web. Semantic Web, 11(1), 139–151. https://doi.org/10.3233/SW-190383
Ghandhari, M., Fini, C., Da Rold, F., & Borghi, A. M. (2020). Different kinds of embodied language: A comparison between Italian and Persian languages. Brain and Cognition, 142, 105581. https://doi.org/10.1016/j.bandc.2020.105581
Gijssels, T., & Casasanto, D. (2020). Hand-use norms for Dutch and English manual action verbs: Implicit measures from a pantomime task. Behavior Research Methods, 52(4), 1744–1767. https://doi.org/10.3758/s13428-020-01347-x
Harpaintner, M., Sim, E.-J., Trumpp, N. M., Ulrich, M., & Kiefer, M. (2020). The grounding of abstract concepts in the motor and visual system: An fMRI study. Cortex, 124, 1–22. https://doi.org/10.1016/j.cortex.2019.10.014
Harpaintner, M., Trumpp, N. M., & Kiefer, M. (2018). The Semantic Content of Abstract Concepts: A Property Listing Study of 296 Abstract Words. Frontiers in Psychology, 9, 1748. https://doi.org/10.3389/fpsyg.2018.01748
Harpaintner, M., Trumpp, N. M., & Kiefer, M. (2022). Time course of brain activity during the processing of motor- and vision-related abstract concepts: Flexibility and task dependency. Psychological Research, 86(8), 2560–2582. https://doi.org/10.1007/s00426-020-01374-5
Hartman, J., & Paradis, C. (2023). The language of sound: Events and meaning multitasking of words. Cognitive Linguistics, 34(3–4), 445–477. https://doi.org/10.1515/cog-2022-0006
Hörberg, T., Larsson, M., & Olofsson, J. K. (2022). The Semantic Organization of the English Odor Vocabulary. Cognitive Science, 46(11), e13205. https://doi.org/10.1111/cogs.13205
Huang, C.-R., & Xiong, J. (2019). Linguistic synaesthesia in Chinese. In C.-R. Huang, Z. Jing-Schmidt, & B. Meisterernst (Eds.), The Routledge Handbook of Chinese Applied Linguistics (1st ed., pp. 294–312). Routledge. https://doi.org/10.4324/9781315625157-20
Iatropoulos, G., Herman, P., Lansner, A., Karlgren, J., Larsson, M., & Olofsson, J. K. (2018). The language of smell: Connecting linguistic and psychophysical properties of odor descriptors. Cognition, 178, 37–49. https://doi.org/10.1016/j.cognition.2018.05.007
Jacobs, A. M., & Kinder, A. (2017). “The Brain Is the Prisoner of Thought”: A Machine-Learning Assisted Quantitative Narrative Analysis of Literary Metaphors for Use in Neurocognitive Poetics. Metaphor and Symbol, 32(3), 139–160. https://doi.org/10.1080/10926488.2017.1338015
Jo, C. (2022). Linguistic Synesthesia in Korean: Universality and Variation. SAGE Open, 12(3), 215824402211178. https://doi.org/10.1177/21582440221117804
Johns, B. T. (2022). Accounting for item-level variance in recognition memory: Comparing word frequency and contextual diversity. Memory & Cognition, 50(5), 1013–1032. https://doi.org/10.3758/s13421-021-01249-z
Jones, L. L., Wurm, L. H., Calcaterra, R. D., & Ofen, N. (2017). Integrative Priming of Compositional and Locative Relations. Frontiers in Psychology, 8. https://doi.org/10.3389/fpsyg.2017.00359
Julich-Warpakowski, N., & Pérez Sobrino, P. (2023). Introduction: Current challenges in metaphor research. Metaphor and the Social World, 13(1), 1–15. https://doi.org/10.1075/msw.00026.jul
Kaiser, E. (2021). Consequences of Sensory Modality for Perspective-Taking: Comparing Visual, Olfactory and Gustatory Perception. Frontiers in Psychology, 12, 701486. https://doi.org/10.3389/fpsyg.2021.701486
Kernot, D., Bossomaier, T., & Bradbury, R. (2017). Novel Text Analysis for Investigating Personality: Identifying the Dark Lady in Shakespeare's Sonnets. Journal of Quantitative Linguistics, 24(4), 255–272. https://doi.org/10.1080/09296174.2017.1304049
Kernot, D., Bossomaier, T., & Bradbury, R. (2018). Using Shakespeare's Sotto Voce to Determine True Identity From Text. Frontiers in Psychology, 9, 289. https://doi.org/10.3389/fpsyg.2018.00289
Kernot, D., Bossomaier, T., & Bradbury, R. (2019). The Stylometric Impacts of Ageing and Life Events on Identity. Journal of Quantitative Linguistics, 26(1), 1–21. https://doi.org/10.1080/09296174.2017.1405719
Khatin-Zadeh, O., Hu, J., Banaruee, H., & Marmolejo-Ramos, F. (2023). How emotions are metaphorically embodied: Measuring hand and head action strengths of typical emotional states. Cognition and Emotion, 37(3), 486–498. https://doi.org/10.1080/02699931.2023.2181314
Kiefer, M., Pielke, L., & Trumpp, N. M. (2022). Differential temporo-spatial pattern of electrical brain activity during the processing of abstract concepts related to mental states and verbal associations. NeuroImage, 252, 119036. https://doi.org/10.1016/j.neuroimage.2022.119036
Kim, M.-K., Müller, H. M., & Weiss, S. (2021). What you “mean” is not what I “mean”: Categorization of verbs by Germans and Koreans using the semantic differential. Lingua, 252, 103012. https://doi.org/10.1016/j.lingua.2020.103012
Koblet, O., & Purves, R. S. (2020). From online texts to Landscape Character Assessment: Collecting and analysing first-person landscape perception computationally. Landscape and Urban Planning, 197, 103757. https://doi.org/10.1016/j.landurbplan.2020.103757
Körner, A., Castillo, M., Drijvers, L., Fischer, M. H., Günther, F., Marelli, M., Platonova, O., Rinaldi, L., Shaki, S., Trujillo, J. P., Tsaregorodtseva, O., & Glenberg, A. M. (2023). Embodied Processing at Six Linguistic Granularity Levels: A Consensus Paper. Journal of Cognition, 6(1), 60. https://doi.org/10.5334/joc.231
Krishna, P. P., Arulmozi, S., & Mishra, R. K. (2022). “Do You See and Hear More? A Study on Telugu Perception Verbs.” Journal of Psycholinguistic Research, 51(3), 473–484. https://doi.org/10.1007/s10936-021-09827-7
Kumcu, A. (2021). Linguistic Synesthesia in Turkish: A Corpus-based Study of Crossmodal Directionality. Metaphor and Symbol, 36(4), 241–255. https://doi.org/10.1080/10926488.2021.1921557
Lau, S. H., Huang, Y., Ferreira, V. S., & Vul, E. (2019). Perceptual features predict word frequency asymmetry across modalities. Attention, Perception, & Psychophysics, 81(4), 1076–1087. https://doi.org/10.3758/s13414-019-01682-y
Lee, J., & Shin, J.-A. (2023). The cross-linguistic comparison of perceptual strength norms for Korean, English and L2 English. Frontiers in Psychology, 14, 1188909. https://doi.org/10.3389/fpsyg.2023.1188909
Li, M., Lu, Q., Long, Y., & Gui, L. (2017). Inferring Affective Meanings of Words from Word Embedding. IEEE Transactions on Affective Computing, 8(4), 443–456. https://doi.org/10.1109/TAFFC.2017.2723012
Littlemore, J., Sobrino, P. P., Houghton, D., Shi, J., & Winter, B. (2018). What makes a good metaphor? A cross-cultural study of computer-generated metaphor appreciation. Metaphor and Symbol, 33(2), 101–122. https://doi.org/10.1080/10926488.2018.1434944
Liu, W., Bansal, D., Daruna, A., & Chernova, S. (2023). Learning instance-level N-ary semantic knowledge at scale for robots operating in everyday environments. Autonomous Robots, 47(5), 529–547. https://doi.org/10.1007/s10514-023-10099-4
Liu, W., Bansal, D., Daruna, A., & Chernova, S. (2021, July 12). Learning Instance-Level N-Ary Semantic Knowledge At Scale For Robots Operating in Everyday Environments. Robotics: Science and Systems XVII. Robotics: Science and Systems 2021. https://doi.org/10.15607/RSS.2021.XVII.035
Long, Y., Xiang, R., Lu, Q., Huang, C.-R., & Li, M. (2021). Improving Attention Model Based on Cognition Grounded Data for Sentiment Analysis. IEEE Transactions on Affective Computing, 12(4), 900–912. https://doi.org/10.1109/TAFFC.2019.2903056
Lynott, D., Connell, L., Brysbaert, M., Brand, J., & Carney, J. (2020). The Lancaster Sensorimotor Norms: Multidimensional measures of perceptual and action strength for 40,000 English words. Behavior Research Methods, 52(3), 1271–1291. https://doi.org/10.3758/s13428-019-01316-z
Mahmood, A., & Yeganegi, S. (2023). Lexical sophistication and crowdfunding outcomes. Venture Capital, 1–32. https://doi.org/10.1080/13691066.2023.2265565
Marson, F., Paoletti, P., Naor-Ziv, R., Carducci, F., & Ben-Soussan, T. D. (2023). Embodied empathy and abstract concepts’ concreteness: Evidence from contemplative practices. In Progress in Brain Research (Vol. 277, pp. 181–209). Elsevier. https://doi.org/10.1016/bs.pbr.2022.12.005
Márton, Z. C., Türker, S., Rink, C., Brucker, M., Kriegel, S., Bodenmüller, T., & Riedel, S. (2018). Improving object orientation estimates by considering multiple viewpoints: Orientation histograms of symmetries and measurement models for view selection. Autonomous Robots, 42(2), 423–442. https://doi.org/10.1007/s10514-017-9633-1
Miceli, A., Wauthia, E., Kandana Arachchige, K., Lefebvre, L., Ris, L., & Simoes Loureiro, I. (2023). Perceptual strength influences lexical decision in Alzheimer's disease. Journal of Neurolinguistics, 68, 101144. https://doi.org/10.1016/j.jneuroling.2023.101144
Miceli, A., Wauthia, E., Lefebvre, L., Ris, L., & Simoes Loureiro, I. (2021). Perceptual and Interoceptive Strength Norms for 270 French Words. Frontiers in Psychology, 12, 667271. https://doi.org/10.3389/fpsyg.2021.667271
Miceli, A., Wauthia, E., Lefebvre, L., Vallet, G. T., Ris, L., & Loureiro, I. S. (2022). Differences related to aging in sensorimotor knowledge: Investigation of perceptual strength and body object interaction. Archives of Gerontology and Geriatrics, 102, 104715. https://doi.org/10.1016/j.archger.2022.104715
Miklashevsky, A. (2018). Perceptual Experience Norms for 506 Russian Nouns: Modality Rating, Spatial Localization, Manipulability, Imageability and Other Variables. Journal of Psycholinguistic Research, 47(3), 641–661. https://doi.org/10.1007/s10936-017-9548-1
Morucci, P., Bottini, R., & Crepaldi, D. (2019). Augmented Modality Exclusivity Norms for Concrete and Abstract Italian Property Words. Journal of Cognition, 2(1), 42. https://doi.org/10.5334/joc.88
Okuno, H. Y., & Guedes, G. (2020). Automatic XML creation for Multisensorial Books. 2020 XV Conferencia Latinoamericana de Tecnologias de Aprendizaje (LACLO), 1–6. https://doi.org/10.1109/LACLO50806.2020.9381139
Pathak, A., Velasco, C., Petit, O., & Calvert, G. A. (2019). Going to great lengths in the pursuit of luxury: How longer brand names can enhance the luxury perception of a brand. Psychology & Marketing, 36(10), 951–963. https://doi.org/10.1002/mar.21247
Pérez-Sánchez, M. Á., Stadthagen-Gonzalez, H., Guasch, M., Hinojosa, J. A., Fraga, I., Marín, J., & Ferré, P. (2021). EmoPro – Emotional prototypicality for 1286 Spanish words: Relationships with affective and psycholinguistic variables. Behavior Research Methods, 53(5), 1857–1875. https://doi.org/10.3758/s13428-020-01519-9
Perlman, M., Little, H., Thompson, B., & Thompson, R. L. (2018). Iconicity in Signed and Spoken Vocabulary: A Comparison Between American Sign Language, British Sign Language, English, and Spanish. Frontiers in Psychology, 9, 1433. https://doi.org/10.3389/fpsyg.2018.01433
Pexman, P. M., Muraki, E., Sidhu, D. M., Siakaluk, P. D., & Yap, M. J. (2019). Quantifying sensorimotor experience: Body–object interaction ratings for more than 9,000 English words. Behavior Research Methods, 51(2), 453–466. https://doi.org/10.3758/s13428-018-1171-z
Plekhanov Russian University of Economics, Simonenko, M. A., Kazaryan, S. Y., & Plekhanov Russian University of Economics. (2023). Synaesthetic metaphor and its reproduction in Russian-to-English translation: A frame-based study. RESEARCH RESULT Theoretical and Applied Linguistics, 9(3). https://doi.org/10.18413/2313-8912-2023-9-3-0-2
Pollock, L. (2018). Statistical and methodological problems with concreteness and other semantic variables: A list memory experiment case study. Behavior Research Methods, 50(3), 1198–1216. https://doi.org/10.3758/s13428-017-0938-y
Popović Stijačić, M., & Filipović Đurđević, D. (2022). Perceptual richness of words and its role in free and cued recall. Primenjena Psihologija, 15(3), 355–381. https://doi.org/10.19090/pp.v15i3.2400
Purves, R. S., Striedl, P., Kong, I., & Majid, A. (2023). Conceptualizing Landscapes Through Language: The Role of Native Language and Expertise in the Representation of Waterbody Related Terms. Topics in Cognitive Science, 15(3), 560–583. https://doi.org/10.1111/tops.12652
Raj, R., Hörberg, T., Lindroos, R., Larsson, M., Herman, P., Laukka, E. J., & Olofsson, J. K. (2023). Odor identification errors reveal cognitive aspects of age-associated smell loss. Cognition, 236, 105445. https://doi.org/10.1016/j.cognition.2023.105445
Repetto, C., Rodella, C., Conca, F., Santi, G. C., & Catricalà, E. (2022). The Italian Sensorimotor Norms: Perception and action strength measures for 959 words. Behavior Research Methods. https://doi.org/10.3758/s13428-022-02004-1
Rey, A. E., Riou, B., Vallet, G. T., & Versace, R. (2017). The automatic visual simulation of words: A memory reactivated mask slows down conceptual access. Canadian Journal of Experimental Psychology / Revue Canadienne de Psychologie Expérimentale, 71(1), 14–22. https://doi.org/10.1037/cep0000100
Reymore, L. (2022). Characterizing prototypical musical instrument timbres with timbre trait profiles. Musicae Scientiae, 26(3), 648–674. https://doi.org/10.1177/10298649211001523
San Roque, L., Kendrick, K. H., Norcliffe, E., & Majid, A. (2018). Universal meaning extensions of perception verbs are grounded in interaction. Cognitive Linguistics, 29(3), 371–406. https://doi.org/10.1515/cog-2017-0034
Scerrati, E., Lugli, L., Nicoletti, R., & Borghi, A. M. (2017). The Multilevel Modality-Switch Effect: What Happens When We See the Bees Buzzing and Hear the Diamonds Glistening. Psychonomic Bulletin & Review, 24(3), 798–803. https://doi.org/10.3758/s13423-016-1150-2
Schulte Im Walde, S., & Frassinelli, D. (2022). Distributional Measures of Semantic Abstraction. Frontiers in Artificial Intelligence, 4, 796756. https://doi.org/10.3389/frai.2021.796756
Sidhu, D. M., & Pexman, P. M. (2018). Lonely sensational icons: Semantic neighbourhood density, sensory experience and iconicity. Language, Cognition and Neuroscience, 33(1), 25–31. https://doi.org/10.1080/23273798.2017.1358379
Speed, L. J., & Brybaert, M. (2022). Dutch sensory modality norms. Behavior Research Methods, 54(3), 1306–1318. https://doi.org/10.3758/s13428-021-01656-9
Speed, L. J., & Majid, A. (2017). Dutch modality exclusivity norms: Simulating perceptual modality in space. Behavior Research Methods, 49(6), 2204–2218. https://doi.org/10.3758/s13428-017-0852-3
Speed, L. J., & Majid, A. (2018). An Exception to Mental Simulation: No Evidence for Embodied Odor Language. Cognitive Science, 42(4), 1146–1178. https://doi.org/10.1111/cogs.12593
Speed, L. J., & Majid, A. (2020). Grounding language in the neglected senses of touch, taste, and smell. Cognitive Neuropsychology, 37(5–6), 363–392. https://doi.org/10.1080/02643294.2019.1623188
Speed, L. J., Papies, E. K., & Majid, A. (2023). Mental simulation across sensory modalities predicts attractiveness of food concepts. Journal of Experimental Psychology: Applied, 29(3), 557–571. https://doi.org/10.1037/xap0000461
Strik Lievers, F., & Winter, B. (2018). Sensory language across lexical categories. Lingua, 204, 45–61. https://doi.org/10.1016/j.lingua.2017.11.002
Su, C., Wang, X., Wang, Z., & Chen, Y. (2019). A model of synesthetic metaphor interpretation based on cross-modality similarity. Computer Speech & Language, 58, 1–16. https://doi.org/10.1016/j.csl.2019.03.003
Tatiya, G., Hosseini, R., Hughes, M. C., & Sinapov, J. (2019). Sensorimotor Cross-Behavior Knowledge Transfer for Grounded Category Recognition. 2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 1–6. https://doi.org/10.1109/DEVLRN.2019.8850715
Tatiya, G., Hosseini, R., Hughes, M. C., & Sinapov, J. (2020). A Framework for Sensorimotor Cross-Perception and Cross-Behavior Knowledge Transfer for Object Categorization. Frontiers in Robotics and AI, 7, 522141. https://doi.org/10.3389/frobt.2020.522141
Tatiya, G., & Sinapov, J. (2019). Deep Multi-Sensory Object Category Recognition Using Interactive Behavioral Exploration. 2019 International Conference on Robotics and Automation (ICRA), 7872–7878. https://doi.org/10.1109/ICRA.2019.8794095
Teodorescu, H.-N., & Bolea, S. C. (2019). Text Sectioning based on Stylometric Distances. 2019 International Conference on Speech Technology and Human-Computer Dialogue (SpeD), 1–6. https://doi.org/10.1109/SPED.2019.8906616
Thomason, J., Padmakumar, A., Sinapov, J., Walker, N., Jiang, Y., Yedidsion, H., Hart, J., Stone, P., & Mooney, R. (2020). Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog. Journal of Artificial Intelligence Research, 67, 327–374. https://doi.org/10.1613/jair.1.11485
Tjuka, A., Forkel, R., & List, J.-M. (2021). Linking norms, ratings, and relations of words and concepts across multiple language varieties. Behavior Research Methods, 54(2), 864–884. https://doi.org/10.3758/s13428-021-01650-1
Tomsk State University, Rezanova, Z. I., Nekrasova, E. D., Tomsk State University, Miklashevsky, А. А., & Tomsk State University. (2018). INVESTIGATION OF PSYCHO-LINGUISTIC AND COGNITIVE ASPECTS OF LANGUAGE CONTACTING IN THE PROJECT “LINGUISTIC AND ETHNOCULTURAL DIVERSITY OF SOUTHERN SIBERIA IN SYNCHRONY AND DIAHRONY: INTERACTION OF LANGUAGES AND CULTURES.” Rusin, 52, 107–117. https://doi.org/10.17223/18572685/52/8
Tomsk State University, Vladimirova, V. E., Rezanova, Z. I., Tomsk State University, Korshunova, I. S., & Tomsk State University. (2022). Ethno-linguistic contact as reflected in language cognition: Does bilingualism affect subjective assessments of perceptual semantics?*. Rusin, 70, 214–231. https://doi.org/10.17223/18572685/70/12
Troche, J., Crutch, S. J., & Reilly, J. (2017). Defining a Conceptual Topography of Word Concreteness: Clustering Properties of Emotion, Sensation, and Magnitude among 750 English Words. Frontiers in Psychology, 8, 1787. https://doi.org/10.3389/fpsyg.2017.01787
Van De Weijer, J., Bianchi, I., & Paradis, C. (2023). Sensory modality profiles of antonyms. Language and Cognition, 1–15. https://doi.org/10.1017/langcog.2023.20
Vergallito, A., Petilli, M. A., & Marelli, M. (2020). Perceptual modality norms for 1,121 Italian words: A comparison with concreteness and imageability scores and an analysis of their impact in word processing tasks. Behavior Research Methods, 52(4), 1599–1616. https://doi.org/10.3758/s13428-019-01337-8
Verheyen, S., De Deyne, S., Linsen, S., & Storms, G. (2020). Lexicosemantic, affective, and distributional norms for 1,000 Dutch adjectives. Behavior Research Methods, 52(3), 1108–1121. https://doi.org/10.3758/s13428-019-01303-4
Vigliocco, G., Zhang, Y., Del Maschio, N., Todd, R., & Tuomainen, J. (2020). Electrophysiological signatures of English onomatopoeia. Language and Cognition, 12(1), 15–35. https://doi.org/10.1017/langcog.2019.38
Villani, C., D'Ascenzo, S., Borghi, A. M., Roversi, C., Benassi, M., & Lugli, L. (2022). Is justice grounded? How expertise shapes conceptual representation of institutional concepts. Psychological Research, 86(8), 2434–2450. https://doi.org/10.1007/s00426-021-01492-8
Villani, C., Lugli, L., Liuzza, M. T., & Borghi, A. M. (2019). Varieties of abstract concepts and their multiple dimensions. Language and Cognition, 11(3), 403–430. https://doi.org/10.1017/langcog.2019.23
Wan, M., Su, Q., Ahrens, K., & Huang, C.-R. (2023). Perceptional and actional enrichment for metaphor detection with sensorimotor norms. Natural Language Engineering, 1–29. https://doi.org/10.1017/S135132492300044X
Wang, X., Su, C., & Chen, Y. (2019). A Method of Abstractness Ratings for Chinese Concepts. In A. Lotfi, H. Bouchachia, A. Gegov, C. Langensiepen, & M. McGinnity (Eds.), Advances in Computational Intelligence Systems (Vol. 840, pp. 217–226). Springer International Publishing. https://doi.org/10.1007/978-3-319-97982-3_18
Wang, Y., & Zeng, Y. (2022a). Multisensory Concept Learning Framework Based on Spiking Neural Networks. Frontiers in Systems Neuroscience, 16, 845177. https://doi.org/10.3389/fnsys.2022.845177
Wang, Y., & Zeng, Y. (2022b). Statistical Analysis of Multisensory and Text-Derived Representations on Concept Learning. Frontiers in Computational Neuroscience, 16, 861265. https://doi.org/10.3389/fncom.2022.861265
Wicke, P., & Bolognesi, M. (2020). Emoji-based semantic representations for abstract and concrete concepts. Cognitive Processing, 21(4), 615–635. https://doi.org/10.1007/s10339-020-00971-x
Winter, B. (2019). Statistics for Linguists: An Introduction Using R (1st ed.). Routledge. https://doi.org/10.4324/9781315165547
Winter, B. (2022). Mapping the landscape of exploratory and confirmatory data analysis in linguistics. In D. Tay & M. X. Pan (Eds.), Data Analytics in Cognitive Linguistics (pp. 13–48). De Gruyter. https://doi.org/10.1515/9783110687279-002
Winter, B. (2023). Abstract concepts and emotion: Cross-linguistic evidence and arguments against affective embodiment. Philosophical Transactions of the Royal Society B: Biological Sciences, 378(1870), 20210368. https://doi.org/10.1098/rstb.2021.0368
Winter, B., Lupyan, G., Perry, L. K., Dingemanse, M., & Perlman, M. (2023). Iconicity ratings for 14,000+ English words. Behavior Research Methods. https://doi.org/10.3758/s13428-023-02112-6
Winter, B., & Perlman, M. (2021). Size sound symbolism in the English lexicon. Glossa: A Journal of General Linguistics, 6(1). https://doi.org/10.5334/gjgl.1646
Winter, B., Perlman, M., & Majid, A. (2018). Vision dominates in perceptual language: English sensory vocabulary is optimized for usage. Cognition, 179, 213–220. https://doi.org/10.1016/j.cognition.2018.05.008
Winter, B., Perlman, M., Perry, L. K., & Lupyan, G. (2017). Which words are most iconic?: Iconicity in English sensory words. Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systems, 18(3), 443–464. https://doi.org/10.1075/is.18.3.07win
Winter, B., Sóskuthy, M., Perlman, M., & Dingemanse, M. (2022). Trilled /r/ is associated with roughness, linking sound and touch across spoken languages. Scientific Reports, 12(1), 1035. https://doi.org/10.1038/s41598-021-04311-7
Winter, B., & Strik-Lievers, F. (2023). Semantic distance predicts metaphoricity and creativity judgments in synesthetic metaphors. Metaphor and the Social World, 13(1), 59–80. https://doi.org/10.1075/msw.00029.win
Wu, C., & Mu, X. (2023). Sensory experience ratings (SERs) for 1,130 Chinese words: Relationships with other semantic and lexical psycholinguistic variables. Linguistics Vanguard, 0(0). https://doi.org/10.1515/lingvan-2022-0083
Xiong, J., & Huang, C.-R. (2018). Somewhere in COLDNESS Lies Nibbāna: Lexical Manifestations of COLDNESS. In J.-F. Hong, Q. Su, & J.-S. Wu (Eds.), Chinese Lexical Semantics (Vol. 11173, pp. 70–81). Springer International Publishing. https://doi.org/10.1007/978-3-030-04015-4_6
Yin Zhong, & Chu-Ren Huang. (2020). Sweetness or Mouthfeel: A corpus-based study of the conceptualization of taste. Linguistic Research, 37(3), 359–387. https://doi.org/10.17250/KHISLI.37.3.202012.001
Zeng, Y., Zhao, D., Zhao, F., Shen, G., Dong, Y., Lu, E., Zhang, Q., Sun, Y., Liang, Q., Zhao, Y., Zhao, Z., Fang, H., Wang, Y., Li, Y., Liu, X., Du, C., Kong, Q., Ruan, Z., & Bi, W. (2023). BrainCog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired AI and brain simulation. Patterns, 4(8), 100789. https://doi.org/10.1016/j.patter.2023.100789
Zhang, X., Amiri, S., Sinapov, J., Thomason, J., Stone, P., & Zhang, S. (2023). Multimodal embodied attribute learning by robots for object-centric action policies. Autonomous Robots, 47(5), 505–528. https://doi.org/10.1007/s10514-023-10098-5
Zhang, X., Sinapov, J., & Zhang, S. (2021, July 12). Planning Multimodal Exploratory Actions for Online Robot Attribute Learning. Robotics: Science and Systems XVII. Robotics: Science and Systems 2021. https://doi.org/10.15607/RSS.2021.XVII.005
Zhao, Q. (2020a). From Linguistic Synaesthesia to Conceptual Metaphor Theory. In Q. Zhao, Embodied Conceptualization or Neural Realization (Vol. 10, pp. 115–128). Springer Singapore. https://doi.org/10.1007/978-981-32-9315-1_7
Zhao, Q. (2020b). Methodology: A Corpus-Driven Approach. In Q. Zhao, Embodied Conceptualization or Neural Realization (Vol. 10, pp. 19–34). Springer Singapore. https://doi.org/10.1007/978-981-32-9315-1_2
Zhao, Q., Ahrens, K., & Huang, C.-R. (2022). Linguistic synesthesia is metaphorical: A lexical-conceptual account. Cognitive Linguistics, 33(3), 553–583. https://doi.org/10.1515/cog-2021-0098
Zhao, Q., Huang, C.-R., & Ahrens, K. (2019). Directionality of linguistic synesthesia in Mandarin: A corpus-based study. Lingua, 232, 102744. https://doi.org/10.1016/j.lingua.2019.102744
Zhao, Q., & Long, Y. (2022). A Diachronic Study on Linguistic Synesthesia in Chinese. In M. Dong, Y. Gu, & J.-F. Hong (Eds.), Chinese Lexical Semantics (Vol. 13250, pp. 84–94). Springer International Publishing. https://doi.org/10.1007/978-3-031-06547-7_6
Zhao, Q., Long, Y., & Huang, C.-R. (2020). Linguistic Synaesthesia of Mandarin Sensory Adjectives: Corpus-Based and Experimental Approaches. In J.-F. Hong, Y. Zhang, & P. Liu (Eds.), Chinese Lexical Semantics (Vol. 11831, pp. 139–146). Springer International Publishing. https://doi.org/10.1007/978-3-030-38189-9_14
Zhong, Y., Ahrens, K., & Huang, C.-R. (2023). Entity, event, and sensory modalities: An onto-cognitive account of sensory nouns. Humanities and Social Sciences Communications, 10(1), 255. https://doi.org/10.1057/s41599-023-01677-z
Zhong, Y., Huang, C.-R., & Dong, S. (2022). Bodily sensation and embodiment: A corpus-based study of gustatory vocabulary in Mandarin Chinese. Journal of Chinese Linguistics, 50(1), 196–230. https://doi.org/10.1353/jcl.2022.0008
Zhong, Y., Wan, M., Ahrens, K., & Huang, C.-R. (2022). Sensorimotor norms for Chinese nouns and their relationship with orthographic and semantic variables. Language, Cognition and Neuroscience, 37(8), 1000–1022. https://doi.org/10.1080/23273798.2022.2035416
Zhu, S., Wang, X., & Liu, P. (2021). Who Killed Sanmao and Virginia Woolf? A Comparative Study of Writers with Suicidal Attempt Based on a Quantitative Linguistic Method. In M. Liu, C. Kit, & Q. Su (Eds.), Chinese Lexical Semantics (Vol. 12278, pp. 408–420). Springer International Publishing. https://doi.org/10.1007/978-3-030-81197-6_34