Chinese

The ICDAR 2013 dataset consists of 229 training images and 233 testing images, with word-level annotations provided. It is the standard benchmark dataset for evaluating near-horizontal text detection. Source: Single Shot Text Detector with Regional Attention Image Source: https://plos.figshare.com/articles/Detection_examples_of_the_proposed_method_on_the_ICDAR_2013_dataset_17_/5325856

Simplified Chinese dataset for NER in The Third International Chinese Language Processing Bakeoff (2006), provided by Microsoft Research Asia (MSRA).

CASIA-HWDB is a dataset for handwritten Chinese character recognition. It contains 300 files (240 in HWDB1.1 training set and 60 in HWDB1.1 test set). Each file contains about 3000 isolated gray-scale Chinese character images written by one writer, as well as their corresponding labels. Source: Generating Handwritten Chinese Characters using CycleGAN Image Source: http://www.nlpr.ia.ac.cn/databases/handwriting/Touching_Characters_Databases.html

CUGE is a Chinese Language Understanding and Generation Evaluation benchmark with the following features: (1) Hierarchical benchmark framework, where datasets are principally selected and organized with a language capability-task-dataset hierarchy. (2) Multi-level scoring strategy, where different levels of model performance are provided based on the hierarchical framework. CUGE covers 7 important language capabilities, 17 mainstream NLP tasks and 19 representative datasets. It includes tasks like: word segmentation, part of speech tagging, reading comprehension and document retrieval.

Large Scale Informal Chinese Corpus (LSICC) is a large-scale corpus of informal Chinese. This corpus contains around 37 million book reviews and 50 thousand netizen's comments to the news. Source: LSICC: A Large Scale Informal Chinese Corpus