Applying deep neural networks to Natural Language Processing has helped achieve state-of-the-art performance across different tasks, including the task of language generation due to the capability of neural networks to learn representations with different levels of abstraction. There are four main approaches that have been applied to the task of language generation:

• Language models
• Encoder-decoder architecture
• Memory networks
• Transformer models