100 Best Natural Language Generation Videos


Text generation is the process of automatically producing natural language text based on input data and a set of predetermined rules or models. Text generation is accomplished using natural language processing (NLP) algorithms and techniques, which allow computers to analyze and understand human language in order to generate text that is fluent, natural-sounding, and appropriate to the intended context.

There are several different approaches to text generation, each with its own strengths and limitations. Some approaches, such as template-based generation, rely on pre-defined templates and rules to generate text, while other approaches, such as machine learning-based generation, use statistical models trained on large amounts of data to generate text.

To accomplish text generation, a computer program typically begins by analyzing the input data and determining the appropriate context and content for the generated text. This may involve identifying the main ideas or concepts in the input data, and selecting the most relevant and appropriate words and phrases to use in the generated text. The program then uses natural language processing algorithms to arrange the selected words and phrases into grammatically correct and fluent sentences, and may also apply additional post-processing to ensure that the generated text is natural-sounding and appropriate to the intended context.


See also:

KPML (Komet-Penman Multi-Lingual) | Linguistic Realizers | OpenCCG (OpenNLP CCG Library) | Realizers In Natural Language Processing | RiTa Toolkit | SimpleNLG Realization Engine 2017 | Text Generation

[61x Mar 2018]