Dataset Open Access
Schwiebert, Gerald; Weber, Cornelius; Qu, Leyuan; Siqueira, Henrique; Wermter, Stefan
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-3" xsi:schemaLocation="http://datacite.org/schema/kernel-3 http://schema.datacite.org/meta/kernel-3/metadata.xsd"> <identifier identifierType="DOI">10.25592/uhhfdm.10048</identifier> <creators> <creator> <creatorName>Schwiebert, Gerald</creatorName> <affiliation>University of Hamburg</affiliation> </creator> <creator> <creatorName>Weber, Cornelius</creatorName> <affiliation>University of Hamburg</affiliation> </creator> <creator> <creatorName>Qu, Leyuan</creatorName> <affiliation>University of Hamburg</affiliation> </creator> <creator> <creatorName>Siqueira, Henrique</creatorName> <affiliation>University of Hamburg</affiliation> </creator> <creator> <creatorName>Wermter, Stefan</creatorName> <affiliation>University of Hamburg</affiliation> </creator> </creators> <titles> <title>GLips - German Lipreading Dataset</title> </titles> <publisher>Universität Hamburg</publisher> <publicationYear>2022</publicationYear> <subjects> <subject>Computer Vision</subject> <subject>Pattern Recognition</subject> <subject>Machine Learning</subject> <subject>Deep Learning</subject> <subject>Language</subject> <subject>Dataset</subject> <subject>Automatic Speech Recognition</subject> <subject>Transfer Learning</subject> <subject>Lip Reading</subject> <subject>Corpus</subject> </subjects> <dates> <date dateType="Issued">2022-03-01</date> </dates> <language>de</language> <resourceType resourceTypeGeneral="Dataset"/> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://www.fdr.uni-hamburg.de/record/10048</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="arXiv" relationType="IsReferencedBy">arXiv:2202.13403</relatedIdentifier> <relatedIdentifier relatedIdentifierType="DOI" relationType="IsPartOf">10.25592/uhhfdm.10047</relatedIdentifier> </relatedIdentifiers> <version>1.0</version> <rightsList> <rights rightsURI="https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode">Creative Commons Attribution Non Commercial No Derivatives 4.0 International</rights> <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights> </rightsList> <descriptions> <description descriptionType="Abstract"><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></description> <description descriptionType="Other">Copyright of original data: Hessian Parliament (https://hessischer-landtag.de). If 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. Reference: 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</description> <description descriptionType="Other">{"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"]}</description> </descriptions> </resource>