The word “Generation” has been used in many different ways over the years, starting from a few centuries ago and evolving to its current meaning. Generating content is a very broad term that includes everything from writing something (text, blog posts, etc.), creating an online video or just making an audio recording of one’s thoughts (speech); generating text from speech and also from images, videos or even handwriting; or simply taking your own written words and generating new ones based on them. The more accurate definition is: the process of converting raw unstructured data into organised and structured information that can be presented as output or output formats for a machine. In other words: it’s the creation of an interface between you and those machines.
There are various methods for generating text data for a variety of reasons including human-to-human conversations. A specific method for this purpose may be named after the technology behind it: Natural Language Generation (NLG), which is used for generating text data via speech or text (or both). NLG technology and applications can be applied to generate text data on different platforms including mobile devices. NLG includes various tasks such as:
• Text to speech synthesis
• Image/video understanding
• Automatic transcriptions across languages
• Automated translation or paraphrasing of documents written in multiple languages
• Document summarization
• Synthesizing human or non-human voices and voices of animals
• NLP for automatic writing
• Voice and natural language processing for search
• Sentiment analysis
• Search engine optimization
• Question answering
• Information retrieval for business intelligence
• Content moderation
• Customer support
Many of these technologies are used today in various combinations. Some examples using NLG technology are:
• Siri, Google Assistant, Cortana
• (Amazon Alexa)
• Facebook Messenger chatbots or Slack bots
• AI generated text
• Artificial intelligent assistants like Amazon Echo
Content generation is an important part of a skill. Whether it’s building a web page, voice response to a user request or build up your own bot through text-based processing, you can provide your users with interesting and useful content by utilising the Text Cortex Generation API and this article is all about how you can utilising that API to do something more creative. Let’s get started!
Text generation is where we generate text based on some pre-defined input, like numbers, characters etc… In other words, text generation is generating text from the given input. It’s basically using Natural Language Processing (NLP) techniques to understand what your input text needs, what kind of structure you need, what keywords should appear, what type of content you want (text, images and HTML etc…) and so on…
So let’s say you’ve got some data which is structured in certain ways, you can send that data to Text Cortex and they will generate this content based on your defined structure. You can also use the same API to retrieve previously generated data. The difference between both cases, is that when you create your content, you can only generate one version at a time. Whereas with retrieving previous data from an existing TextCortex content, your system can access any number of versions from this content you have created.
Some tips about how to use TextCortex text generation API:
After installing your favourite package, head over to the example sections on github to see what you can do with the TextCortex technology.
Happy content creation!
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