The process of language generation involves the generation of coherent and contextually appropriate natural language text. Below are the general steps involved in the process:

  1. Input Analysis: The system analyzes the input data, which can be structured or unstructured, to understand the context, purpose, and constraints of the language generation task. This step may involve parsing, semantic analysis, and other techniques to extract relevant information.

  2. Content Planning: The system determines the main ideas, structure, and order of the generated text. It identifies the key points to be included and organizes them in a logical and coherent manner. Content planning may involve knowledge representation, reasoning, and content selection algorithms.

  3. Text Organization: The system organizes the selected content into paragraphs, sections, or other appropriate textual units. It ensures that the generated text flows smoothly and follows the intended structure or format. This step may involve generating headings, subheadings, bullet points, or other formatting elements.

  4. Sentence Generation: Based on the planned structure and content, the system generates individual sentences. It can utilize various techniques such as template-based generation, rule-based generation, statistical models, or neural networks to generate grammatically correct and contextually relevant sentences.

  5. Sentence Coherence: The system checks the coherence and cohesion among generated sentences to ensure a smooth flow of information. It may employ techniques like discourse analysis, referring expression generation, and lexical choice to maintain logical connections and avoid inconsistencies.

  6. Lexical Selection: The system selects appropriate words, phrases, and expressions based on the context, style, and target audience. It considers factors like tone, formality, domain-specific vocabulary, and cultural sensitivity. This step may involve using semantic networks, language databases, or machine learning algorithms to choose the most suitable lexical items.

  7. Surface Realization: The system generates the final surface form of the text, considering the grammatical and stylistic conventions of the target language. It applies syntactic and morphological rules to transform the abstract representation into a coherent and readable text. This can include tasks such as inflection, word order adjustment, determiner selection, and punctuation.

  8. Post-Processing: The system performs any necessary post-processing steps on the generated text, such as proofreading, spell checking, grammar correction, or text formatting. It ensures the overall quality and correctness of the output.

  It is important to note that the language generation process can vary depending on the specific application, techniques used, and desired output quality. Different approaches, such as rule-based, statistical, or neural network-based models, may be employed at different stages of the process to achieve the desired results.