Research on natural language generation is rapidly growing due to the increasing demand for human-machine communication in natural language. This workshop aims to promote the discussion, exchange, and dissemination of ideas on the topic of text generation, touching several important aspects in this modality: learning schemes and evaluation, model design and structures, advanced decoding strategies, and natural language generation applications. This workshop aims to be a venue for the exchange of ideas regarding data-driven machine learning approaches for text generation, including mainstream tasks such as dialogue generation, instruction generation, and summarization; and for establishing new directions and ideas with potential for impact in the fields of machine learning, deep learning, and NLP.