关键词: 手语识别, 深度学习, 数据集, 特征提取, 端到端

Abstract: The vast majority of hearing people who do not understand sign language cause deaf people who find jobs, seek medical treatment, legal advice, or other life and work area great communication difficulties. And sign language interpreters need to be made appointments in advance, the cost is also very high. Therefore, many researchers have begun to use machine learning to develop automatic sign language translators, but most of the researches do not work well because of the size and quality of the data sets. To create the largest Chinese sign language data set in the world, the end-to-end learning model of body joints’ position, facial expression and finger joint is used to train effectively. Conclusion shows the great advantage of modern deep learning technology in the recognition of complex sign language is highlighted. The BLEU-4 for a small subset has reached 30.8.

Key words: sign language recognition, deep learning, dataset, feature extraction, end-to-end