데이터셋 탐색

The Lip Reading in the Wild (LRW) dataset a large-scale audio-visual database that contains 500 different words from over 1,000 speakers. Each utterance has 29 frames, whose boundary is centered around the target word. The database is divided into training, validation and test sets. The training set contains at least 800 utterances for each class while the validation and test sets contain 50 utterances. Source: Towards Pose-invariant Lip-Reading Image Source: https://www.robots.ox.ac.uk/~vgg/data/lip_reading/lrw1.html

LRW-1000 has been renamed as CAS-VSR-W1k.* It is a naturally-distributed large-scale benchmark for word-level lipreading in the wild, including 1000 classes with about 718,018 video samples from more than 2000 individual speakers. There are more than 1,000,000 Chinese character instances in total. Each class corresponds to the syllables of a Mandarin word which is composed by one or several Chinese characters. This dataset aims to cover a natural variability over different speech modes and imaging conditions to incorporate challenges encountered in practical applications. Source: VIPL Image Source: https://arxiv.org/pdf/1810.06990v6.pdf

This dataset contains the opinions of Russian native speakers about the relationship between a generic term (hypernym) and a specific instance of it (hyponym). Assembled by Dmitry Ustalov in 2017. A set of 300 most frequent nouns was extracted from the Russian National Corpus. Then each method or resource (including RuThes and RuWordNet) produced at most five hypernyms, if possible. This resulted in 10,600 unique non-empty subsumption pairs, which were annotated by seven different performers whose mother tongue is Russian and were at least 20 years old as of February 1, 2017. As a result, 4,576 out of 10,600 pairs were annotated as positive while the remaining 6,024 were annotated as negative. Interestingly, the performers were more confident in the negative answers than in the positive ones.