Language Dataset

Dataset containing the images and labels for the Language data used in the CVPR NAS workshop Unseen-data challenge under the codename "LaMelo"The Language dataset is a constructed dataset using words from aspell dictionaries. The intention of this dataset is to require machine learning models to not only perform image classification but also linguistic analysis to figure out which letter frequency is associated with each language. For each Language image we selected four six-letter words using the standard latin alphabet and removed any words with letters that used diacritics (such as ́e or ̈u) or included ‘y’ or ‘z’.We encode these words on a graph with one axis representing the index of the 24 character long string (the four words joined together) and the other representing the letter (going A-X).The data is in a channels-first format with a shape of (n, 1, 24, 24) where n is the number of samples in the corresponding set (50,000 for training, 10,000 for validation, and 10,000 for testing).There are ten classes in the dataset, with 7,000 examples of each, distributed evenly between the three subsets.The ten classes and corresponding numerical label are as follows:English: 0,Dutch: 1,German: 2,Spanish: 3,French: 4,Portuguese: 5,Swahili: 6,Zulu: 7,Finnish: 8,Swedish: 9本数据集包含CVPR NAS研讨会“不可见数据挑战赛”（代号"LaMelo"）所用语言数据的图像与标签。该语言数据集基于aspell词典（aspell）中的词汇构建而成，其设计目标是使得机器学习模型不仅需完成图像分类任务，还需开展语言学分析，以厘清与每种语言相关联的字母频率特征。针对每种语言对应的图像样本，我们选取4个由标准拉丁字母构成的6字母单词，并剔除所有包含变音符号（如é或ü）或字母“y”、“z”的单词。我们将这些单词编码至二维图像中：其中一个轴代表24字符长字符串（由4个单词拼接而成）的索引，另一个轴代表字母（取值范围为A至X）。该数据集采用通道优先（channels-first）的数据格式，形状为(n, 1, 24, 24)，其中n对应各子集的样本量：训练集50000条，验证集10000条，测试集10000条。本数据集共包含10个类别，每个类别拥有7000条样本，且在训练、验证、测试三个子集上均匀分布。10个类别及其对应的数字标签如下：英语（0）、荷兰语（1）、德语（2）、西班牙语（3）、法语（4）、葡萄牙语（5）、斯瓦西里语（6）、祖鲁语（7）、芬兰语（8）、瑞典语（9）