{"url":"/dataset/glips","name":"GLips","full_name":"German Lips","description_markdown":"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 15GB.","description_withheld":null,"homepage":"https://www.fdr.uni-hamburg.de/record/10048","introduced_date":"2022-02-27","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-multimodal-german-dataset-for-automatic-lip","title":"A Multimodal German Dataset for Automatic Lip Reading Systems and Transfer Learning","first_author":"Gerald Schwiebert","url":null},"license":{"name":"CC-BY-NC-ND 4.0 International","url":"https://creativecommons.org/licenses/by-nc-nd/4.0/"},"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Texts","url":"/datasets/modality/texts"},{"name":"Audio","url":"/datasets/modality/audio"}],"tasks":[{"name":"Visual Speech Recognition","url":"/task/visual-speech-recognition","datasets_with_task":"/datasets/task/visual-speech-recognition"},{"name":"Lipreading","url":"/task/lipreading","datasets_with_task":"/datasets/task/lipreading"},{"name":"Lip to Speech Synthesis","url":"/task/lip-to-speech-synthesis","datasets_with_task":"/datasets/task/lip-to-speech-synthesis"},{"name":"Lip Reading","url":"/task/lip-reading","datasets_with_task":"/datasets/task/lip-reading"},{"name":"Unconstrained Lip-synchronization","url":"/task/lip-sync","datasets_with_task":"/datasets/task/lip-sync"},{"name":"Talking Face Generation","url":"/task/talking-face-generation","datasets_with_task":"/datasets/task/talking-face-generation"},{"name":"audio-visual learning","url":"/task/audio-visual-learning","datasets_with_task":"/datasets/task/audio-visual-learning"}],"languages":[{"name":"German","url":"/datasets/language/german"}],"variants":["GLips"],"data_loaders":[],"num_papers_in_archive":6,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}