Exploring the Natural Language Generation: Current Trends and Research Challenges

Natural Language Generation (NLG) acts as a bridge between input data and human communication. NLG systems are meant to generate human-understandable output making it a useful technique mainly in report generation, automatic replies to queries like Chatbots, and other domains that involve Natural Language Processing (NLP). NLG continues to evolve; embracing the latest trends like neural networks, large language models, personalized features, cognitive architectures, and emotional intelligence, but it still faces some challenges with its implementations and operations for cohesive integration. Therefore, this survey presents a brief introduction to some of the latest trends and challenges faced by NLG which are playing a dynamic role in shaping the evolution of NLG.