March 1, 2022 Dataset Open Access

Schwiebert, Gerald; Weber, Cornelius; Qu, Leyuan; Siqueira, Henrique; Wermter, Stefan

JSON Export

{"conceptdoi":"10.25592/uhhfdm.10047","conceptrecid":"10047","created":"2022-03-01T14:51:06.987925+00:00","doi":"10.25592/uhhfdm.10048","id":10048,"links":{"badge":"https://www.fdr.uni-hamburg.de/badge/doi/10.25592/uhhfdm.10048.svg","conceptbadge":"https://www.fdr.uni-hamburg.de/badge/doi/10.25592/uhhfdm.10047.svg","conceptdoi":"http://doi.org/10.25592/uhhfdm.10047","doi":"http://doi.org/10.25592/uhhfdm.10048"},"metadata":{"access_right":"open","access_right_category":"success","communities":[{"id":"uhh"}],"creators":[{"affiliation":"University of Hamburg","name":"Schwiebert, Gerald"},{"affiliation":"University of Hamburg","name":"Weber, Cornelius"},{"affiliation":"University of Hamburg","name":"Qu, Leyuan"},{"affiliation":"University of Hamburg","name":"Siqueira, Henrique"},{"affiliation":"University of Hamburg","name":"Wermter, Stefan"}],"description":"<p>The German Lipreading dataset consists of 250,000 publicly available videos of the faces of speakers of the Hessian Parliament, which was processed for word-level lip reading using an automatic pipeline. The format is similar to that of the English language Lip Reading in the Wild (LRW) dataset, with each H264-compressed MPEG-4 video encoding one word of interest in a context of 1.16 seconds duration, which yields compatibility for studying transfer learning between both datasets. Choosing video material based on naturally spoken language in a natural environment ensures more robust results for real-world applications than artificially generated datasets with as little noise as possible. The 500 different spoken words ranging between 4-18 characters in length each have 500 instances and separate MPEG-4 audio- and text metadata-files, originating from 1018 parliamentary sessions. Additionally, the complete TextGrid files containing the segmentation information of those sessions are also included. The size of the uncompressed dataset is 16GB.</p>","doi":"10.25592/uhhfdm.10048","keywords":["Computer Vision","Pattern Recognition","Machine Learning","Deep Learning","Language","Dataset","Automatic Speech Recognition","Transfer Learning","Lip Reading","Corpus"],"language":"deu","license":{"id":"CC-BY-NC-ND-4.0"},"notes":"Copyright of original data: Hessian Parliament (https://hessischer-landtag.de).\nIf you use this dataset, you agree to use it for research purpose only and to cite the following reference in any works that make any use of the dataset.\n\nReference:\nGerald Schwiebert, Cornelius Weber, Leyuan Qu, Henrique Siqueira, Stefan Wermter (2022). A Multimodal German Dataset for Automatic Lip Reading Systems and Transfer Learning. arXiv:2202.13403","publication_date":"2022-03-01","references":["Gerald Schwiebert, Cornelius Weber, Leyuan Qu, Henrique Siqueira, Stefan Wermter (2022). A Multimodal German Dataset for Automatic Lip Reading Systems and Transfer Learning","arXiv:2202.13403"],"related_identifiers":[{"identifier":"arXiv:2202.13403","relation":"isReferencedBy","scheme":"arxiv"},{"identifier":"10.25592/uhhfdm.10047","relation":"isVersionOf","scheme":"doi"}],"relations":{"version":[{"count":1,"index":0,"is_last":true,"last_child":{"pid_type":"recid","pid_value":"10048"},"parent":{"pid_type":"recid","pid_value":"10047"}}]},"resource_type":{"title":"Dataset","type":"dataset"},"title":"GLips - German Lipreading Dataset","version":"1.0"},"owners":[276],"revision":9,"updated":"2022-05-03T08:48:04.893753+00:00"}