Understanding human communication requires a huge amount of flexibility. So can computers, which ultimately have their foundations in the strict rules of binary code, ever be programmed to communicate with humans in a truly natural way?

When computers first arrived, those that used them adopted the machines’ language. However, as information technology developed, a process known as abstraction allowed users to understand and operate computers at a far higher level. At these levels, commands could be given using mouses, touchpads, graphical interfaces, etc.

Such high level control allowed the general population, rather than specialists alone, to use computers effectively. Today we all depend on computers. As such, any technology capable of improving our ability to interact with them is potentially lucrative.

Natural language processing (NLP) seeks to make computers respond appropriately when we “talk” to our devices, which means equipping them with technology that allows them to engage in natural human dialogue.

To date NLP has given us digital assistants and translation tools. Now even more ambitious projects, such as Prompt, which seeks to be the “command line for the real world” –  a highly-integrated textual interface which allows users to access various home automation, commerce, information, and productivity tools using natural language – are looking to make machines understand and respond to natural human communication in new and productive ways.

Nuance, for example, is looking to create a conversational connection between cars and the internet of things by using NLP to create intelligent and conversational voice experiences. These will allow cars to talk to “things” such as consumer electronics and smart devices. And SoundHound’s natural voice search app “Hound” includes a natural speaking engine which allows it to interpret conversational English directions without users having to memorise commands. 

Natural language processing is a difficult job. Humans bend and distort language to suit their purposes, relying heavily on their interlocutors’ ability to “catch” their drift and getting a machine to replicate this process is a real challenge. But, because of the benefits NLP offers, there are big opportunities in this field. And that means that we can expect to see more exciting NLP developments in the near future.

What NLP developments have you caught your eye? And do you think that computers will ever truly be able to understand and “talk” to their human users. 

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