Natural Language Processing at Home

By Manasi Patel

Photo by Thomas Kolnowski on Unsplash

In response to the current situation, many have been spending more time at home and have increasingly been using virtual voice assistants such as Google Home, Amazon Alexa, and Amazon Echo Dot. They are able to make our lives easy by completing simple tasks allowing us to focus on what we are working on. These powerful machines are able to take requests from our language, process it, and provide the user with an answer or response to the request or question asked. How exactly do these machines work though? The answer is through natural language processing (NLP). 

Natural language processing concerns the interactions between human language and computers. One application allows for computers and machines to take in human language and use different processes to understand the input. There are three steps behind this process, according to Investopedia. The first step is to understand the human language it initially took in. This is done so by a statistical model which translates the human language to a programming language. The second step in this process is “part-of-speech tagging.” Within this process, the computer works to understand the part of speech of each word which will allow it to understand the request or question made by the human. The final step in this process is to translate the programming language to a way it can communicate with the human, either through audio or text. 

This is the fundamental process behind many of these home assistants, allowing them to take in questions asked by humans such as “What is the weather today?” or “What is the nearest park?” For example, Amazon’s Alexa can be asked to change its volume, connect or disconnect to Bluetooth and WiFi, to read audiobooks, and complete other various tasks. While these are some of the more practical uses, it can also be asked to answer fun, personal questions, sing songs, and play simple games. The latter skillset of Alexa increases friendly interaction between the user and machine and makes it seem like the user is talking with another human rather than an automated assistant. 

While NLP is still progressing further, there are many other examples of natural language processing which we encounter every day. This includes functions like Google Translate and spell check. (Check out for more examples of NLP). We see it in play at home with these virtual assistants and it is also used in businesses, showing the flexible use of this process. The future of natural language processing and technology is still uncertain, but we may see further developments of virtual assistants and perhaps more similar-functioning devices to make everyday life easier.