Editing Natural language generation (section)

===Chatbots===

Another area  where NLG has been widely applied is automated [[dialogue]] systems, frequently in the form of chatbots. A [[chatbot]] or chatterbot is a [[Software agent|software]] application used to conduct an on-line chat [[conversation]] via text or [[Speech synthesis|text-to-speech]], in lieu of providing direct contact with a live human agent. While [[natural language processing]] (NLP) techniques are applied in deciphering human input, NLG informs the output part of the chatbot algorithms in facilitating real-time dialogues.

Early chatbot systems, including [[Cleverbot]] created by Rollo Carpenter in 1988 and published in 1997,{{Citation needed|date=January 2023}}  reply to questions by identifying how a human has responded to the same question in a conversation database using [[information retrieval]] (IR) techniques.{{Citation needed|date=January 2023}} Modern chatbot systems predominantly rely on machine learning (ML) models, such as sequence-to-sequence learning and reinforcement learning to generate natural language output. Hybrid models have also been explored. For example, the Alibaba shopping assistant first uses an IR approach to retrieve the best candidates from the knowledge base, then uses the  ML-driven seq2seq model re-rank the candidate responses and generate the answer.<ref>{{cite arXiv |last=Mnasri |first=Maali |date=2019-03-21 |title=Recent advances in conversational NLP: Towards the standardization of Chatbot building |class=cs.CL |eprint=1903.09025 }}</ref>