Word megastudy data and eye movement corpora available
If you are looking for word processing data, the following resources may be of use for various languages. If you know of more resources or have better links, feel free to contact marc dot brysbaert at ugent dot be. If you are looking for word features rather than word processing data, better have a look here.
Chinese
- Liu et al. (2007)
- Word naming
- Visual presentation
- 2,423 single character words
- Data (Word features and Naming latencies in txt or excl).
- Sze et al. (2014)
- Lexical decision
- Visual presentation
- 2,500 single character words
- Data
- Lee et al. (2015)
- Lexical decision
- Visual presentation
- 3,423 single character words
- Data
- Chang et al. (2016)
- Word naming
- Visual presentation
- 3,314 single character words
- Data
- Tse et al. (2017)
- Lexical decision
- Visual presentation (Chinese Lexicon Project)
- 25,286 words
- Data
- Tsang et al. (2018)
- Lexical decision
- Visual presentation
- 12,578 words
- Data
- Wang et al. (2019)
- Writing spoken words
- 1,600 characters
- Data
- Pan et al. (2021)
- Sentence reading (eye movements)
- 1685 word tokens
- Data
- Li et al. (2022)
- Listening comprehension
- fMRI
- 90+ min novel (Le Petit Prince)
- data
- Sui et al. (2022)
- Text reading (eye movements of novel)
- Visual presentation (GECO)
- 5053 word types
- data
- Zhang et al. (2022)
- Sentence reading (eye movements)
- 8551 word types
- Data
- Tse et al. (2023)
- Naming
- Visual presentation (Chinese Lexicon Project II)
- 25,000+ words
- data
Danish
- Hollenstein et al. (2022)
- Eye movement corpus
- Visual presentation
- 5872 words
- data
Dutch
- Keuleers et al. (2010)
- Lexical decision
- Visual presentation
- 14,089 monosyllabic and disyllabic words
- Data
- Ernestus & Cutler (2015)
- Lexical decision
- Auditory presentation
- 2,780 words
- Data
- Brysbaert et al. (2016)
- Lexical decision
- Visual presentation
- 30,016 words (lemmas)
- Data
- Heyman et al. (2016)
- Speeded fragment completion
- Visual presentation
- 8,240 words (lemmas)
- Data
- Cop et al. (2017)
- Text reading (eye movement data)
- Visual presentation
- 5,575 words
- Data and word reading times
- Brysbaert et al. (2019)
- Word recognition times in Y/N vocabulary test (Dutch Crowdsourcing Project)
- Visual presentation
- 54,319 words
- Data
- Mak & Willems (2019)
- Story reading (eye movements)
- Visual presentation
- 7,200 word tokens (three narrative texts)
- Data
- Siegelman et al. (2022)
- Eye movement data of students reading short texts (MECO)
- Visual presentation
- 2000 word tokens
- Data
English
- Seidenberg & Waters (1989)
- Word naming
- Visual presentation
- 2,900 monosyllabic words
- Data
- Treiman et al. (1995)
- Word naming
- Visual presentation
- 1,327 monosyllabic words
- Data
- Spieler & Balota (1997) + Balota & Spieler (1998)
- Word naming (young and old people)
- Visual presentation
- 2,428 monosyllabic words
- Data (Trial data or word means)
- Kessler et al. (2002)
- Word naming
- Visual presentation
- 3,688 monosyllabic words
- Data
- Chateau & Jared (2003)
- Word naming
- Visual presentation
- 1,000 disyllabic words
- Data
- Balota et al. (2004)
- Lexical decision (young and old people)
- Visual presentation
- 2,428 monosyllabic words
- Data (Trial level or item means)
- Pynte & Kennedy (2007)
- Text reading (eye movements, Dundee corpus)
- Visual presentation
- 9,776 words
- Data
- Balota et al. (2007)
- Lexical decision and Word naming
- Visual presentation
- 40,481 words
- Data
- Lemhöfer et al. (2008)
- Progressive demasking (in L1 and L2)
- Visual presentation
- 1,025 words
- Data
- Cortese et al. (2010)
- Recognition memory
- Visual presentation
- 2,578 monosyllabic words
- Data
- Keuleers et al. (2010)
- Lexical decision
- Visual presentation
- 28,730 monosyllabic and disyllabic words
- Data
- Pritchard et al. (2012)
- Non-word naming
- Visual presentation
- 1,475 monosyllabic nonwords
- Data
- Adelman et al. (2013)
- Word naming
- Visual presentation
- 2,820 monosyllabic words
- Data
- Cohen-Shikora et al. (2013)
- Past tense generation of verbs
- Visual presentation
- 2,200 verbs
- Data
- Frank et al. (2013)
- Sentence reading (eye movements and self-paced reading)
- Visual presentation
- 1,524 words
- Data
- Hutchison et al. (2013)
- Lexical decision and word naming
- Visual presentation (with semantic primes)
- 1,661 words
- Data
- Smith & Levy (2013)
- Self-paced reading (Brown SPR corpus)
- Visual presentation
- 450 sentences, 7,188 words
- Data
- Adelman et al. (2014a)
- Lexical decision (1,000 participants)
- Visual presentation (with orthographic primes)
- 420 words
- Data
- Adelman et al. (2014b)
- Word naming (100 participants)
- Visual presentation
- 592 monosyllabic words
- Data
- Cortese et al. (2015a)
- Word naming (beginning v. end of block)
- Visual presentation
- 2,614 monosyllabic words
- Data
- Cortese et al. (2015b)
- Recognition memory
- Visual presentation
- 2,897 disyllabic words
- Data
- Dufau et al. (2015)
- Go / no-go task (EEG measurement)
- Visual presentation
- 960 nouns
- Data
- Frank et al. (2015)
- Sentence reading (EEG measurement)
- Visual presentation
- 1,524 words
- Rayner et al. (2015)
- Sentence reading (15 studies run at UCSD)
- Visual presentation
- 100s of sentences
- Data
- Goh et al. (2016)
- Lexical decision and semantic categorization
- Auditory presentation
- 468 words
- Data
- Brysbaert et al. (2017)
- Lexical decision (Dutch-English L2 participants)
- Visual presentation
- 420 words (same as Adelman et al., 2014a)
- Data
- Cop et al. (2017)
- Text reading (eye movements, L1 and L2)
- Visual presentation
- 5,012 words
- Data and word reading times
- Cortese et al. (2017)
- Word naming (manipulation of list difficulty)
- Visual presentation
- 2,500 monosyllabic words
- Data
- Dirix & Duyck (2017)
- Lexical decision (Dutch-English L2 participants)
- Visual presentation
- 800 words
- Data
- Mousikou et al. (2017)
- Non-word naming
- Visual presentation
- 915 disyllabic nonwords
- Data
- Pexman et al. (2017)
- Semantic decision
- Visual presentation
- 10,000 words (lemmas)
- Data
- Futrell et al. (2018)
- Self-paced text reading
- Visual presentation
- 2,332 words
- Data
- Hollenstein et al. (2018)
- Eye movements for text reading (ZuCo)
- Visual presentation
- 21,629 words
- Data
- Lau et al. (2018)
- Free recall and word recognition
- Visual presentation
- 532 words
- Data
- Luke & Christianson (2018)
- Text reading (eye movements; ProVo)
- Visual presentation
- 1,197 words
- Data
- Cortese et al. (2018)
- Word naming (conditional)
- Visual presentation
- 2,145 monosyllabic words
- Data
- Winsler et al. (2018)
- Go / no-go (EEG measurement)
- Auditory presentation
- 960 words
- Hollenstein et al. (2019)
- Eye movements during sentence reading (ZuCo2)
- Visual presentation
- 349 sentences
- Data
- Tucker et al. (2019)
- Lexical decision
- Auditory presentation
- 26,793 words
- Data
- Liben-Nowell et al. (2019)
- Perceptual identification
- Auditory presentation
- 1,081 monosyllabic words
- Data
- Hsu et al. (2019)
- Sentence reading (eye movements and fMRI)
- Visual presentation
- 1,500 words (5 expository texts)
- Data
- Mandera et al. (2020)
- Word recognition times in Y/N vocabulary test (English Crowdsourcing Project)
- Visual presentation
- 61,851 words
- Summary data and raw data
- Goh et al. (2020)
- Lexical decision
- Auditory presentation
- 10,170 words
- Data
- Schmidtke et al. (2020)
- Eye movements in reading
- Visual presentation
- 931 compound words
- Data
- Brysbaert et al. (2021)
- Word recognition times in Y/N vocabulary test (English Crowdsourcing Project)
- English as L2
- Visual presentation
- 61,851 words
- Data
- Peekbank (2021)
- Eye movement data of children reading words (repository)
- Visual presentation
- Unknown number of words
- Data
- Siegelman et al. (2022)
- Eye movement data of students reading short texts (MECO)
- Visual presentation
- 2000 word tokens
- Data
- Kuperman et al. (2022)
- Eye movement data of L2 students reading short texts (MECO L2)
- Visual presentation
- 2000 word tokens
- Data
- Berzak et al. (2022)
- Eye movement data L1 and L2 participants
- Visual presentation
- various numbers of words
- Data
- Li et al. (2022)
- Listening comprehension
- fMRI
- 90+ min novel (Le Petit Prince)
- data
- Sui et al. (2022)
- Text reading Chinese L2 speakers (eye movements of novel)
- Visual presentation (GECO)
- 5053 word types
- data
Estonian
- Siegelman et al. (2022)
- Eye movement data of students reading short texts (MECO)
- Visual presentation
- 2000 word tokens
- Data
Finnish
- Siegelman et al. (2022)
- Eye movement data of students reading short texts (MECO)
- Visual presentation
- 2000 word tokens
- Data
French
- Pynte & Kennedy (2007)
- Text reading (eye movements, Dundee corpus)
- Visual presentation
- 11,321 words
- Ferrand et al. (2010)
- Lexical decision
- Visual presentation
- 38,840 words
- Data
- Ferrand et al. (2011)
- Lexical decision, progressive demasking, and word naming
- Visual presentation
- 1,482 monosyllabic words
- Data
- Ferrand et al. (2018)
- Lexical decision
- Auditory and visual presentation
- 17,876 or 28,466 words
- Data
- Li et al. (2022)
- Listening comprehension
- fMRI
- 90+ min novel (Le Petit Prince)
- data
German
- Kliegl et al. (2006)
- Sentence reading (eye movements)
- Visual presentation
- About 1,000 word types
- Data
- Brysbaert et al. (2011)
- Lexical decision
- Visual presentation
- 2,152 compound words
- Data
- Schröter & Schroeder (2017)
- Lexical decision and word naming
- Visual presentation
- 1,152 words
- Data
- Jäger et al. (2021)
- Eye movements in text reading (Potsdam Textbook Corpus; PoTeC)
- Visual presentation
- Data
- Siegelman et al. (2022)
- Eye movement data of students reading short texts (MECO)
- Visual presentation
- 2000 word tokens
- Data
Greek
- Siegelman et al. (2022)
- Eye movement data of students reading short texts (MECO)
- Visual presentation
- 2000 word tokens
- Data
Hebrew
- Siegelman et al. (2022)
- Eye movement data of students reading short texts (MECO)
- Visual presentation
- 2000 word tokens
- Data
Hindi
- Husain et al. (2015)
- Sentence reading (eye movements)
- Visual presentation
- about 1,000 word types
- Data
Italian
- Siegelman et al. (2022)
- Eye movement data of students reading short texts (MECO)
- Visual presentation
- 2000 word tokens
- Data
Japanese
- Asahara et al. (2016)
- Eye movement data of students reading short texts
- Visual presentation
- 1600 word tokens
Korean
- Siew et al. (2021)
- Lexical decision
- Visual presentation
- 30,930 words
- Data
- Siegelman et al. (2022)
- Eye movement data of students reading short texts (MECO)
- Visual presentation
- 2000 word tokens
- Data
Malay
- Yap et al. (2010)
- Lexical decision
- Visual presentation
- 9,592 words
- Data
- Maziyah Mohamed et al. (2022)
- Lexical Decision
- Visual presentation
- 1,264 words
- Data
Norwegian
- Siegelman et al. (2022)
- Eye movement data of students reading short texts (MECO)
- Visual presentation
- 2000 word tokens
- Data
Persian
- Nemati et al. (2022)
- Lexical decision
- Visual presentation
- 1800 words
- Data
Portuguese
- Soares et al. (2019)
- Word naming and lexical decision
- Visual presentation
- 1,920 words
- Leal et al. (2022)
- Paragraph reading (eye movements)
- Visual presentation
- 2494 tokens (1237 types)
- Data
Russian
-
- Sentence reading (eye movements)
- Visual presentation
- About 1,000 word types
- Data
- Siegelman et al. (2022)
- Eye movement data of students reading short texts (MECO)
- Visual presentation
- 2000 word tokens
- Data
Spanish
- Davies et al. (2013)
- Word naming
- Visual presentation
- 2,764 words
- Data
- González-Nosti et al. (2014)
- Lexical decision
- Visual presentation
- 2,765 words
- Data
- Aguasvivas et al. (2018)
- Word recognition (crowdsourcing)
- Visual presentation
- 45,389 words
- Data
- Miguel-Abella et al. (2021)
- Word naming
- Visual presentation
- 4562 verbs
- Data (Word means or Trial data)
- Siegelman et al. (2022)
- Eye movement data of students reading short texts (MECO)
- Visual presentation
- 2000 word tokens
- Data
Turkish
- Siegelman et al. (2022)
- Eye movement data of students reading short texts (MECO)
- Visual presentation
- 2000 word tokens
- Data
References
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Brysbaert, M., Stevens, M., Mandera, P., & Keuleers, E. (2016). The impact of word prevalence on lexical decision times: Evidence from the Dutch Lexicon Project 2. Journal of Experimental Psychology: Human Perception and Performance, 42, 441-458.
Chang, Y. N., Hsu, C. H., Tsai, J. L., Chen, C. L., & Lee, C. Y. (2016). A psycholinguistic database for traditional Chinese character naming. Behavior Research Methods, 48(1), 112-122.
Chateau, D., & Jared, D. (2003). Spelling–sound consistency effects in disyllabic word naming. Journal of Memory and Language, 48(2), 255-280.
Cohen-Shikora, E. R., Balota, D. A., Kapuria, A., & Yap, M. J. (2013). The past tense inflection project (PTIP): Speeded past tense inflections, imageability ratings, and past tense consistency measures for 2,200 verbs. Behavior research methods, 45(1), 151-159.
Cop, U., Dirix, N., Drieghe, D., & Duyck, W. (2017). Presenting GECO: An eyetracking corpus of monolingual and bilingual sentence reading. Behavior Research Methods, 49(2), 602-615.
Cortese, M.J., Hacker, S., Schock, J. & Santo, J.B. (2015a). Is reading aloud performance in megastudies systematically influenced by the list context? Quarterly Journal of Experimental Psychology, 68, 1711-1722. doi: 10.1080/17470218.2014.974624
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Cortese, M.J., Khanna, M.M., Kopp, R., Santo, J.B, Preston, K.S., & Van Zuiden, T. (2017). Participants shift response deadlines based on list difficulty during reading aloud megastudies, Memory & Cognition, 45, 589-599.
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Cortese, M. J., Yates, M., Schock, J., & Vilks, L. (2018). Examining word processing via a megastudy of conditional reading aloud. Quarterly Journal of Experimental Psychology, 71(11), 2295-2313.
Davies, R., Barbón, A., & Cuetos, F. (2013). Lexical and semantic age-of-acquisition effects on word naming in Spanish. Memory & Cognition, 41(2), 297-311.
Dirix, N., & Duyck, W. (2017). The first-and second-language age of acquisition effect in first-and second-language book reading. Journal of Memory and Language, 97, 103-120.
Dufau, S., Grainger, J., Midgley, K. J., & Holcomb, P. J. (2015). A thousand words are worth a picture: Snapshots of printed-word processing in an event-related potential megastudy. Psychological Science, 26(12), 1887-1897.
Ernestus, M., & Cutler, A. (2015). BALDEY: A database of auditory lexical decisions. The Quarterly Journal of Experimental Psychology, 68(8), 1469-1488.
Ferrand, L., Brysbaert, M., Keuleers, E., New, B., Bonin, P., Meot, A., Augustinova, M., & Pallier, C. (2011). Comparing word processing times in naming, lexical decision, and progressive demasking: evidence from Chronolex. Frontiers in Psychology, 2:306. doi: 10.3389/fpsyg.2011.00306.
Ferrand, L., Méot, A., Spinelli, E., New, B., Pallier, C., Bonin, P., … & Grainger, J. (2018). MEGALEX: A megastudy of visual and auditory word recognition. Behavior Research Methods, 50(3), 1285-1307.
Ferrand, L., New, B., Brysbaert, M., Keuleers, E., Bonin, P., Meot, A., Augustinova, M., & Pallier, C. (2010). The French Lexicon Project: Lexical decision data for 38,840 French words and 38,840 pseudowords. Behavior Research Methods, 42, 488-496.
Frank, S. L., Monsalve, I. F., Thompson, R. L., & Vigliocco, G. (2013). Reading time data for evaluating broad-coverage models of English sentence processing. Behavior Research Methods, 45(4), 1182-1190.
Frank, S. L., Otten, L. J., Galli, G., & Vigliocco, G. (2015). The ERP response to the amount of information conveyed by words in sentences. Brain and language, 140, 1-11.
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Goh, W. D., Yap, M. J., Lau, M. C., Ng, M. M., & Tan, L. C. (2016). Semantic richness effects in spoken word recognition: A lexical decision and semantic categorization megastudy. Frontiers in psychology, 7, 976.
Goh, W.D., Yap, M.J., & Chee, Q.W. (2020). The Auditory English Lexicon Project: A multi-talker, multi-region psycholinguistic database of 10,170 spoken words and nonwords. Behavior Resesearch Methods. https://doi.org/10.3758/s13428-020-01352-0
González-Nosti, M., Barbón, A., Rodríguez-Ferreiro, J., & Cuetos, F. (2014). Effects of the psycholinguistic variables on the lexical decision task in Spanish: A study with 2,765 words. Behavior Research Methods, 46(2), 517-525.
Heyman, T., Van Akeren, L., Hutchison, K. A., & Storms, G. (2016). Filling the gaps: A speeded word fragment completion megastudy. Behavior Research Methods, 48(4), 1508-1527.
Hollenstein, N., Barrett, M., & Björnsdóttir, M. (2022). The Copenhagen Corpus of Eye Tracking Recordings from Natural Reading of Danish Texts. arXiv preprint arXiv:2204.13311.
Hollenstein, N., Rotsztejn, J., Troendle, M., Pedroni, A., Zhang, C., & Langer, N. (2018). ZuCo, a simultaneous EEG and eye-tracking resource for natural sentence reading. Scientific data, 5(1), 1-13.
Hollenstein, N., Troendle, M., Zhang, C., & Langer, N. (2019). ZuCo 2.0: A dataset of physiological recordings during natural reading and annotation. arXiv preprint arXiv:1912.00903.
Hsu, C.R., Clariana, R., Schloss, B., & Li, P. (2019). Neurocognitive Signatures of Naturalistic Reading of Scientific Texts: A Fixation-Related fMRI Study. Scientific Reports, 9, 10678.
Husain, S., Vasishth, S., and Srinivasan, N. (2014). Integration and prediction difficulty in Hindi sentence comprehension: Evidence from an eye-tracking corpus. Journal of Eye Movement Research, 8(2), 1-12.
Hutchison, K. A., Balota, D. A., Neely, J. H., Cortese, M. J., Cohen-Shikora, E. R., Tse, C. S., … & Buchanan, E. (2013). The semantic priming project. Behavior Research Methods, 45(4), 1099-1114.
Jäger, L., Kern, T., & Haller, P. (2021). Potsdam Textbook Corpus (PoTeC): Eye tracking data from experts and non-experts reading scientific texts. available on OSF.
Kessler, B., Treiman, R., & Mullennix, J. (2002). Phonetic biases in voice key response time measurements. Journal of Memory and Language, 47, 145-171.
Keuleers, E & Balota, D.A. (2015) Megastudies, crowd-sourcing, and large datasets in psycholinguistics: An overview of recent developments, The Quarterly Journal of Experimental Psychology. 68, (8) 1457-1468.
Keuleers, E., Diependaele, K. & Brysbaert, M. (2010). Practice effects in large-scale visual word recognition studies: A lexical decision study on 14,000 Dutch mono- and disyllabic words and nonwords. Frontiers in Psychology 1:174. doi: 10.3389/fpsyg.2010.00174.
Keuleers, E., Lacey, P., Rastle, K., & Brysbaert, M. (2012). The British Lexicon Project: Lexical decision data for 28,730 monosyllabic and disyllabic English words. Behavior Research Methods, 44, 287-304.
Kuperman, V., Siegelman, N., Schroeder, S., Acartürk, C., Alexeeva, S., Amenta, S., … & Usal, K. A. (2022). Text reading in English as a second language: Evidence from the Multilingual Eye-Movements Corpus. Studies in Second Language Acquisition, 1-35.
Lau, M. C., Goh, W. D., & Yap, M. J. (2018). An item-level analysis of lexical-semantic effects in free recall and recognition memory using the megastudy approach. Quarterly Journal of Experimental Psychology, 71, 2207-2222.
Laurinavichyute, A. K., Sekerina, I. A., Alexeeva, S., Bagdasaryan, K., & Kliegl, R. (2019). Russian Sentence Corpus: Benchmark measures of eye movements in reading in Russian. Behavior Research Methods.
Leal, S. E., Lukasova, K., Carthery-Goulart, M. T., & Aluísio, S. M. (2022). RastrOS Project: Natural Language Processing contributions to the development of an eye-tracking corpus with predictability norms for Brazilian Portuguese. Language Resources and Evaluation, 1-40.
Lee, C. Y., Hsu, C. H., Chang, Y. N., Chen, W. F., & Chao, P. C. (2015). The feedback consistency effect in Chinese character recognition: Evidence from a psycholinguistic norm. Language and Linguistics, 16(4), 535-554.
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