Natural Language Generation (NLG) is an application of AI technology that produces a context-appropriate message in human-readable form.
Natural Language Processing (NLP) consists of Natural Language Understanding (NLU) and Natural Language Generation (NLG), which are distinct processes that may be used individually or together. NLG is the output-oriented component of Natural Language Processing (NLP). NLG starts with data and produces syntactically correct and context-appropriate natural language streams that range from simple responses to complex narratives. Generating narratives—story telling—from data may be interactive (conversational) or driven by events.
For example, a change in the database representing a change in a stock price may trigger the generation of a new narrative about the company; or, the arrival of a data feed at the end of a sporting event may trigger the generation of a summation of the event or game.
NLG tools are rapidly emerging as alternatives to business intelligence visualization tools, content generation, and as options for custom output for conversational interfaces.
Although conversational AI should not be viewed as a solution, as technologies are becoming more advanced, it can be part of a solution to enabling conversations with customers, partners, and employees. This research note overviews four trends contributing to the adoption of conversational AI and discusses four vendors who are offering conversational tools.
Conversational AI has the potential to transform customer, employee, and partner experiences. Register for this upcoming webinar to learn more about the latest advances in conversational AI and where to get started in your enterprise.