An equal opportunity for all is the basic right of every human being. The deaf society of the world needs to have access to all the information just like hearing people do. For this to happen there should be a mode of direct communication between hearing and deaf people. The need at this time is to automate this communication so as the deaf society is not dependent upon human interpreters. This paper deals with the systematic survey of conventional and state-of-the-art sign language machine translation and sign language generation projects. We used a standard procedure of carrying out a systematic literature review on 148 studies published in 30 reputed journals and 40 premium conferences and workshops. Existing literature about sign language machine translation is broadly classified into three different categories. These categories are further sub-classified into different classifications depending upon the type of machine translation. Studies pertaining to the specified classifications have been presented with their advantages and limitations. Different methods for sign language generation are reported with their benefits and limitations. Manual and automatic evaluation methods used in every study is presented along with their respective performance metrics. We call for increased efforts in presentation of signs to make them an easy and comfortable mode of communication for deaf society. There is also a requirement to improve translation methods and include the contribution of advanced technologies such as deep learning and neural networks to make an optimal translation process between text and sign language.

人人享有平等机会是每个人的基本权利。世界上的聋人社会需要像听力正常的人一样访问所有信息。要做到这一点，听力和聋人之间应该有一种直接交流的模式。此时需要使这种交流自动化，以便聋人社会不依赖于人工翻译。本文涉及对传统和最先进的手语机器翻译和手语生成项目的系统调查。我们使用标准程序对发表在 30 种知名期刊和 40 次高级会议和研讨会上的 148 项研究进行系统的文献综述。现有的关于手语机器翻译的文献大致分为三类。根据机器翻译的类型，这些类别进一步细分为不同的类别。已经介绍了与指定分类有关的研究及其优点和局限性。报告了不同的手语生成方法及其优点和局限性。每项研究中使用的手动和自动评估方法以及它们各自的性能指标都被呈现出来。我们呼吁加大力度展示标志，使之成为聋人社会一种轻松舒适的交流方式。还需要改进翻译方法，包括深度学习和神经网络等先进技术的贡献，以实现文本和手语之间的最佳翻译过程。