What is natural language processing?
Natural language processing (NLP) is a subset of AI that involves the detection, analysis and interpretation of human language by computers. This can include both textual and spoken language.
We can see the technology in action when we speak into devices via Apple’s Siri and Amazon’s Alexa. These applications use sophisticated speech recognition and function by picking up speech, interpreting its meaning, then providing a response or acting on a command.
This kind of voice control is a relatively new development, however, it is already changing the way we interact with the world around us. The capabilities of NLP are advancing at an impressive rate, so it’s an exciting field to be involved in.
Why is natural language processing important?
In the past, interpreting written or spoken language was a skill exclusive to humans. This meant that any linguistic communication had to involve a human, at least as a middleman. For example, any text had to be written by a person and then read by another person to extract the information from it.
And this absolutely fine if you just want to read a newspaper or a couple of chapters of a book. However, when you want to digest large amounts of information or search for something specific within a large source, the whole process becomes extremely time consuming.
Since roughly the 1990s, NLP has been benefited massively from the use of machine learning algorithms. A process called statistical inference is used to detect patterns and learn rules with minimal or no human input, making modern NLP programs exponentially more powerful than they were just 20 years ago.
“NLP has progressed to the point where speech recognition software can very accurately understand human voices, including different accents and pronunciations.”
Nowadays, NLP has progressed to the point where speech recognition software can very accurately understand human voices, including different accents and pronunciations. Machine learning technology even allows NLP software to adapt to individual voices.
Fundamentally, NLP’s importance stems from the fact that it reduces or eliminates the need for human intervention in many tasks. It has many possible applications, many of which have not even been realized yet.
This application of NLP is probably the most commonly encountered in our day-to-day lives. Think of the smart devices that have become hugely popular in the last few years. Devices like Amazon Echo and Google Home utilize sophisticated NLP algorithms to detect and understand spoken user commands, then act upon them appropriately. Similar technology is used in many call centers to reduce reliance on human staff when dealing with simple queries.
It is now far easier for a computer to understand multiple languages than it is for us. Take translation software as an example. Many of these products can accurately translate between hundreds of languages, and even detect spoken language then convert it into text.
Machine translations using NLP already have many commercial applications and, while they may not be entirely flawless, the technology continues to improve rapidly.
Huge volumes of textual or spoken information can be processed and analyzed using NLP programs. Where in the past large amounts of data could be sorted in simple ways, such as via the presence of certain keywords, NLP can use far more complex methods to detect much deeper themes. Identifying patterns in unstructured data like spoken and text-based language is notoriously difficult, but modern NLP methods make it both possible and highly efficient.
This has wide-ranging applications such as more accurate information extraction, sentiment analysis, paraphrase detection, and more. It also has huge implications for all kinds of research, including academic and commercial kinds, cutting down the amount of human labor drastically.
A new era of communication
NLP is transforming the way we communicate with computers and each other.
At Sciling, we’ve been working with AI and machine learning technology for decades. Our team has worked in cutting edge academic research as well as with high-level commercial applications. Using our proven expertise, we build companies NLP solutions powered by machine learning to change the way they communicate.
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