TROLLing

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Note: No datasets will be curated/published from July 20–31, 2026. More info.

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ASTRID

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71 to 80 of 5,205 Results

05_Stimuli.zip Jun 3, 2026 - Background data for: Exploring time-telling expressions: A cross-linguistic study of German, Czech, and Russian ZIP Archive - 3.1 MB - MD5: 129b08122a77cb5db0266ed0b88da799
06_Data_Czech.csv Jun 3, 2026 - Background data for: Exploring time-telling expressions: A cross-linguistic study of German, Czech, and Russian Comma Separated Values - 7.1 KB - MD5: a8de2afebcbeb10923e88c852d4b073d
07_Data_German.csv Jun 3, 2026 - Background data for: Exploring time-telling expressions: A cross-linguistic study of German, Czech, and Russian Comma Separated Values - 5.5 KB - MD5: ab704f1b4f8c66d268405d6b3b1d06c7
08_Data_Russian.csv Jun 3, 2026 - Background data for: Exploring time-telling expressions: A cross-linguistic study of German, Czech, and Russian Comma Separated Values - 8.3 KB - MD5: 4493980d2875b797b1579e64e0790d69
Replication Data for: Modeling monophthongal versus diphthongal /aɪ/ in sung vocal performance with interpretable machine learning Jun 3, 2026 De Timmerman, Romeo; Verbeke, Gil, 2026, "Replication Data for: Modeling monophthongal versus diphthongal /aɪ/ in sung vocal performance with interpretable machine learning", https://doi.org/10.18710/RDU8M2, DataverseNO, V1 Dataset description This dataset contains replication data for the study "Modeling monophthongal versus diphthongal /aɪ/ in sung vocal performance with interpretable machine learning" (De Timmerman & Verbeke, 2026). The study investigates how binary perceptual annotations of monophthongal versus diphthongal /aɪ/ relate to measurable acoustic variat...
00_README.txt Jun 3, 2026 - Replication Data for: Modeling monophthongal versus diphthongal /aɪ/ in sung vocal performance with interpretable machine learning Plain Text - 15.1 KB - MD5: 2d15149d3af5d14653033961ed323449 File documenting the dataset and the contents of each data file.
formant_features.csv Jun 3, 2026 - Replication Data for: Modeling monophthongal versus diphthongal /aɪ/ in sung vocal performance with interpretable machine learning Comma Separated Values - 557.1 KB - MD5: ebd7f2e6d1c474b35a25ee7f6dad7cf4 File containing engineered acoustic features for the same 1,004 /aɪ/ tokens (1,004 rows, 39 columns). Each row is a single vowel token, identified by vowel_id, with its perceptual label, vowel duration, a set of trajectory-based acoustic features derived from the F1 and F2 formants, and two phonological context variables. This file was used to trai...
formant_measurements.csv Jun 3, 2026 - Replication Data for: Modeling monophthongal versus diphthongal /aɪ/ in sung vocal performance with interpretable machine learning Comma Separated Values - 3.3 MB - MD5: ae940a2782c26ef7da541babf31ef514 File containing raw, time-aligned F1 and F2 formant trajectories for the 1,004 /aɪ/ tokens (1,004 rows, 204 columns). Each row is a single vowel token, identified by vowel_id, with its perceptual label, vowel duration, and the F1 and F2 formant values interpolated to 100 equidistant timepoints across the vowel's duration. This file was used to trai...
ASTRID May 26, 2026 The ASTRID database is a large-scale database with a primary goal of capturing and quantifying individual differences in multilingual experience and relating them to neurocognitive adaptations/outcomes. Herein, resting-state EEG serves as the default outcome, although subsets of the database have additional available neurocognitive measures, includ...
Supporting data for: LLM-Assisted Keymorph Analysis of Grammatical Case in RT's Israeli–Palestinian Conflict Coverage May 15, 2026 Lu, Tingting, 2026, "Supporting data for: LLM-Assisted Keymorph Analysis of Grammatical Case in RT's Israeli–Palestinian Conflict Coverage", https://doi.org/10.18710/YTSGDM, DataverseNO, V1 Dataset description: The dataset for this study supports a Keymorph Analysis of grammatical cases in Russian-language news headlines concerning the the 2023-2025 Israeli-Palestinian conflict, collected from RT's official news website. The dataset comprises four main components: Raw Headlines and Filtered Corpus: This component includes the initial...

05_Stimuli.zip

Jun 3, 2026 - Background data for: Exploring time-telling expressions: A cross-linguistic study of German, Czech, and Russian

ZIP Archive - 3.1 MB -

06_Data_Czech.csv

Jun 3, 2026 - Background data for: Exploring time-telling expressions: A cross-linguistic study of German, Czech, and Russian

Comma Separated Values - 7.1 KB -

07_Data_German.csv

Jun 3, 2026 - Background data for: Exploring time-telling expressions: A cross-linguistic study of German, Czech, and Russian

Comma Separated Values - 5.5 KB -

08_Data_Russian.csv

Jun 3, 2026 - Background data for: Exploring time-telling expressions: A cross-linguistic study of German, Czech, and Russian

Comma Separated Values - 8.3 KB -

Replication Data for: Modeling monophthongal versus diphthongal /aɪ/ in sung vocal performance with interpretable machine learning

Jun 3, 2026

De Timmerman, Romeo; Verbeke, Gil, 2026, "Replication Data for: Modeling monophthongal versus diphthongal /aɪ/ in sung vocal performance with interpretable machine learning", https://doi.org/10.18710/RDU8M2, DataverseNO, V1

Dataset description This dataset contains replication data for the study "Modeling monophthongal versus diphthongal /aɪ/ in sung vocal performance with interpretable machine learning" (De Timmerman & Verbeke, 2026). The study investigates how binary perceptual annotations of monophthongal versus diphthongal /aɪ/ relate to measurable acoustic variat...

00_README.txt

Jun 3, 2026 - Replication Data for: Modeling monophthongal versus diphthongal /aɪ/ in sung vocal performance with interpretable machine learning

Plain Text - 15.1 KB -

File documenting the dataset and the contents of each data file.

formant_features.csv

Jun 3, 2026 - Replication Data for: Modeling monophthongal versus diphthongal /aɪ/ in sung vocal performance with interpretable machine learning

Comma Separated Values - 557.1 KB -

File containing engineered acoustic features for the same 1,004 /aɪ/ tokens (1,004 rows, 39 columns). Each row is a single vowel token, identified by vowel_id, with its perceptual label, vowel duration, a set of trajectory-based acoustic features derived from the F1 and F2 formants, and two phonological context variables. This file was used to trai...

formant_measurements.csv

Jun 3, 2026 - Replication Data for: Modeling monophthongal versus diphthongal /aɪ/ in sung vocal performance with interpretable machine learning

Comma Separated Values - 3.3 MB -

File containing raw, time-aligned F1 and F2 formant trajectories for the 1,004 /aɪ/ tokens (1,004 rows, 204 columns). Each row is a single vowel token, identified by vowel_id, with its perceptual label, vowel duration, and the F1 and F2 formant values interpolated to 100 equidistant timepoints across the vowel's duration. This file was used to trai...

ASTRID

May 26, 2026

The ASTRID database is a large-scale database with a primary goal of capturing and quantifying individual differences in multilingual experience and relating them to neurocognitive adaptations/outcomes. Herein, resting-state EEG serves as the default outcome, although subsets of the database have additional available neurocognitive measures, includ...

Supporting data for: LLM-Assisted Keymorph Analysis of Grammatical Case in RT's Israeli–Palestinian Conflict Coverage

May 15, 2026

Lu, Tingting, 2026, "Supporting data for: LLM-Assisted Keymorph Analysis of Grammatical Case in RT's Israeli–Palestinian Conflict Coverage", https://doi.org/10.18710/YTSGDM, DataverseNO, V1

Dataset description: The dataset for this study supports a Keymorph Analysis of grammatical cases in Russian-language news headlines concerning the the 2023-2025 Israeli-Palestinian conflict, collected from RT's official news website. The dataset comprises four main components: Raw Headlines and Filtered Corpus: This component includes the initial...

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