The Ultimate Guide to Text Generation with NLP: Summaries, Captions and Headlines
Updated: May 24
Natural language processing (NLP) is a branch of artificial intelligence (AI) that deals with the interaction between computers and human languages. NLP can help us perform various tasks such as sentiment analysis, machine translation, speech recognition and more.
One of the most useful applications of NLP is text generation, which is the process of creating natural language texts from some input data.
Text generation can be used for various purposes such as summarizing long articles, creating captions for images and videos, and writing catchy headlines for blogs and news. In this article, we will explore how to use NLP to generate text summaries, captions and headlines using some of the popular tools and frameworks available online.
Text Summaries
Text summarization is the task of creating a short and concise summary of a longer text document. Text summarization can help us save time and get the main idea of a text without reading the whole document. There are two main types of text summarization: extractive and abstractive.
Extractive summarization involves selecting the most important sentences or phrases from the original text and concatenating them to form a summary. Abstractive summarization involves generating new sentences that capture the essence of the original text using natural language generation techniques.
One of the tools that can help us perform extractive summarization is SMMRY (https://smmry.com/), which is a web-based service that can summarize any web page or text document in a few seconds.
SMMRY uses an algorithm that ranks sentences based on their relevance and importance and then selects the top sentences to form a summary.
Another tool that can help us perform abstractive summarization is Hugging Face Transformers (https://huggingface.co/transformers/), which is a library that provides state-of-the-art models for natural language processing tasks such as text generation, translation, classification and more.
Hugging Face Transformers offers several pre-trained models for abstractive summarization such as T5, BART and Pegasus, which are based on deep neural networks that can generate fluent and coherent summaries from any input text.
Text Captions
Text captioning is the task of creating a natural language description of an image or a video. Text captioning can help us understand the content and context of visual media better and make it more accessible for people with visual impairments. Text captioning can also be used for entertainment purposes such as creating memes or funny captions.
One of the tools that can help us perform text captioning is CaptionBot (https://www.captionbot.ai/), which is a web-based service that can generate captions for any image or video uploaded by the user.
CaptionBot uses a combination of computer vision and natural language processing techniques to analyze the visual media and produce a relevant and accurate caption.
Another tool that can help us perform text captioning is CLIP (https://openai.com/blog/clip/), which is a model developed by OpenAI that can learn from any kind of natural language supervision such as captions, hashtags, titles and more. CLIP can generate captions for any image or video by comparing it with billions of texts from the internet and finding the most likely match.
Text Headlines
Text headline generation is the task of creating a short and catchy title for a blog post or a news article. Text headline generation can help us attract more readers and increase the click-through rate of our content. Text headline generation can also be used for creative purposes such as generating slogans or taglines.
One of the tools that can help us perform text headline generation is Blog Title Generator (https://www.seopressor.com/blog-title-generator/), which is a web-based service that can generate headlines for any topic or keyword entered by the user.
Blog Title Generator uses an algorithm that analyzes the topic or keyword and suggests various headlines based on different formulas and templates.
Another tool that can help us perform text headline generation is GPT-3 (https://openai.com/blog/openai-api/), which is a model developed by OpenAI that can generate natural language texts for any prompt or query given by the user. GPT-3 is one of the most advanced models for natural language generation and can produce coherent and diverse texts for various domains and tasks.
GPT-3 can generate headlines for any blog post or news article by taking the summary or the first paragraph as input and producing a suitable title as output.
So, you can create amazing content using artificial intelligence and 10x your productivity!