Dataset Information

ZuCo, a simultaneous EEG and eye-tracking resource for natural sentence reading.

ABSTRACT: We present the Zurich Cognitive Language Processing Corpus (ZuCo), a dataset combining electroencephalography (EEG) and eye-tracking recordings from subjects reading natural sentences. ZuCo includes high-density EEG and eye-tracking data of 12 healthy adult native English speakers, each reading natural English text for 4-6?hours. The recordings span two normal reading tasks and one task-specific reading task, resulting in a dataset that encompasses EEG and eye-tracking data of 21,629 words in 1107 sentences and 154,173 fixations. We believe that this dataset represents a valuable resource for natural language processing (NLP). The EEG and eye-tracking signals lend themselves to train improved machine-learning models for various tasks, in particular for information extraction tasks such as entity and relation extraction and sentiment analysis. Moreover, this dataset is useful for advancing research into the human reading and language understanding process at the level of brain activity and eye-movement.

SUBMITTER: Hollenstein N

PROVIDER: S-EPMC6289117 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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ZuCo, a simultaneous EEG and eye-tracking resource for natural sentence reading.

Hollenstein Nora N Rotsztejn Jonathan J Troendle Marius M Pedroni Andreas A Zhang Ce C Langer Nicolas N

Scientific data 20181211

We present the Zurich Cognitive Language Processing Corpus (ZuCo), a dataset combining electroencephalography (EEG) and eye-tracking recordings from subjects reading natural sentences. ZuCo includes high-density EEG and eye-tracking data of 12 healthy adult native English speakers, each reading natural English text for 4-6 hours. The recordings span two normal reading tasks and one task-specific reading task, resulting in a dataset that encompasses EEG and eye-tracking data of 21,629 words in 11 ...[more]

PMID: 30531985

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Project description:Prosodic constraints play a fundamental role during both spoken sentence comprehension and silent reading. In Chinese, the rhythmic pattern of the verb-object (V-O) combination has been found to rapidly affect the semantic access/integration process during sentence reading (Luo and Zhou, 2010). Rhythmic pattern refers to the combination of words with different syllabic lengths, with certain combinations disallowed (e.g., [2 + 1]; numbers standing for the number of syllables of the verb and the noun respectively) and certain combinations preferred (e.g., [1 + 1] or [2 + 2]). This constraint extends to the situation in which the combination is used to modify other words. A V-O phrase could modify a noun by simply preceding it, forming a V-O-N compound; when the verb is disyllabic, however, the word order has to be O-V-N and the object is preferred to be disyllabic. In this study, we investigated how the reader processes the rhythmic pattern and word order information by recording the reader's eye-movements. We created four types of sentences by crossing rhythmic pattern and word order in compounding. The compound, embedding a disyllabic verb, could be in the correct O-V-N or the incorrect V-O-N order; the object could be disyllabic or monosyllabic. We found that the reader spent more time and made more regressions on and after the compounds when either type of anomaly was detected during the first pass reading. However, during re-reading (after all the words in the sentence have been viewed), less regressive eye movements were found for the anomalous rhythmic pattern, relative to the correct pattern; moreover, only the abnormal rhythmic pattern, not the violated word order, influenced the regressive eye movements. These results suggest that while the processing of rhythmic pattern and word order information occurs rapidly during the initial reading of the sentence, the process of recovering from the rhythmic pattern anomaly may ease the reanalysis processing at the later stage of sentence integration. Thus, rhythmic pattern in Chinese can dynamically affect both local phrase analysis and global sentence integration during silent reading.

Dataset Information

ZuCo, a simultaneous EEG and eye-tracking resource for natural sentence reading.

Publications

ZuCo, a simultaneous EEG and eye-tracking resource for natural sentence reading.

Similar Datasets

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