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21 to 24 of 24 Results

Code for Training and Testing CNVVE Feb 13, 2024 - Analytic Computing Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "Code for Training and Testing CNVVE", https://doi.org/10.18419/DARUS-3896, DaRUS, V1 This dataset consists of files used for training and testing the CNVVE Dataset. This dataset consists of 950 audio samples encompassing six distinct classes of voice expressions. These expressions were collected from 42 generous individuals who donated their voice recordings for the study. By making the dataset publicly accessible, we hope to facil...
Raw audio samples of the CNVVE dataset Feb 13, 2024 - Analytic Computing Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "Raw audio samples of the CNVVE dataset", https://doi.org/10.18419/DARUS-3897, DaRUS, V1 This CNVVE Dataset contains raw audio samples encompassing six distinct classes of voice expressions, namely “Uh-huh” or “mm-hmm”, “Uh-uh” or “mm-mm”, “Hush” or “Shh”, “Psst”, “Ahem”, and Continuous humming, e.g., “hmmm.” Audio samples of each class are found in the respective folders. The samples are recorded through a dedicated website for data c...
Data for: NILK, entity linking dataset targeting NIL-linking cases Jun 29, 2023 - NILK Iurshina, Anastasiia; Pan, Jiaxin; Boutalbi, Rafika; Staab, Steffen, 2023, "Data for: NILK, entity linking dataset targeting NIL-linking cases", https://doi.org/10.18419/DARUS-3454, DaRUS, V1 A dataset for the NIL-detection and NIL-disambiguation tasks. The NILK dataset has two main features: 1) It marks NIL-mentions for NIL-detection by extracting mentions which belong to newly added entities in Wikipedia text. 2) It provides an entity label for NIL-disambiguation by marking NIL-mentions with WikiData IDs from the newer dump. Dataset f...
Website Screenshot to Eye-Gaze Nov 17, 2022 - Udeco-EyeGaze Aspandi Latif, Decky, 2022, "Website Screenshot to Eye-Gaze", https://doi.org/10.18419/DARUS-3251, DaRUS, V1 This dataset contains unified datasets that consist of two pre-processed datasets of Gaze-Mining and Contrastive-Website to allow for the development of Machine Learning based model Eye-Gaze location predictions using Website Screenshot Input.

Code for Training and Testing CNVVE

Feb 13, 2024 - Analytic Computing

Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "Code for Training and Testing CNVVE", https://doi.org/10.18419/DARUS-3896, DaRUS, V1

This dataset consists of files used for training and testing the CNVVE Dataset. This dataset consists of 950 audio samples encompassing six distinct classes of voice expressions. These expressions were collected from 42 generous individuals who donated their voice recordings for the study. By making the dataset publicly accessible, we hope to facil...

Raw audio samples of the CNVVE dataset

Feb 13, 2024 - Analytic Computing

Hedeshy, Ramin; Menges, Raphael; Staab, Steffen, 2024, "Raw audio samples of the CNVVE dataset", https://doi.org/10.18419/DARUS-3897, DaRUS, V1

This CNVVE Dataset contains raw audio samples encompassing six distinct classes of voice expressions, namely “Uh-huh” or “mm-hmm”, “Uh-uh” or “mm-mm”, “Hush” or “Shh”, “Psst”, “Ahem”, and Continuous humming, e.g., “hmmm.” Audio samples of each class are found in the respective folders. The samples are recorded through a dedicated website for data c...

Data for: NILK, entity linking dataset targeting NIL-linking cases

Jun 29, 2023 - NILK

Iurshina, Anastasiia; Pan, Jiaxin; Boutalbi, Rafika; Staab, Steffen, 2023, "Data for: NILK, entity linking dataset targeting NIL-linking cases", https://doi.org/10.18419/DARUS-3454, DaRUS, V1

A dataset for the NIL-detection and NIL-disambiguation tasks. The NILK dataset has two main features: 1) It marks NIL-mentions for NIL-detection by extracting mentions which belong to newly added entities in Wikipedia text. 2) It provides an entity label for NIL-disambiguation by marking NIL-mentions with WikiData IDs from the newer dump. Dataset f...

Website Screenshot to Eye-Gaze

Nov 17, 2022 - Udeco-EyeGaze

Aspandi Latif, Decky, 2022, "Website Screenshot to Eye-Gaze", https://doi.org/10.18419/DARUS-3251, DaRUS, V1

This dataset contains unified datasets that consist of two pre-processed datasets of Gaze-Mining and Contrastive-Website to allow for the development of Machine Learning based model Eye-Gaze location predictions using Website Screenshot Input.

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