Natural Language Processing Defined
Natural language processing is a type of machine learning process. It deals with the way humans speak. So that’s why we call it natural language because humans speak in natural language.
So that means when we say things we don’t say them as structured as a computer’s looking for it to be. So we will use the word “so” as I did. That is not something that adds value to the sentence. It is not the thing that the machine is looking for. The machine wants the important pieces, it wants the verb, it wants the noun, it wants the adjectives. The extra words, our tone, and the way we say things is natural language. It is what makes natural language different than what computers are expecting.
Natural language processing is the work a computer does to understand human language. This is when we type or when we speak out loud. When we say “okay Google” or “Hey Siri,” that is all natural language processing.
Natural Language Processing In Artificial Intelligence
Now, natural language processing is a part of artificial intelligence. It leverages machine learning and sometimes deep learning. Different algorithms are being used to make natural language processing usable. These algorithms need to make it something we cal deal with and use from the machine side of things.
How It Works
So the human says it and natural language processors do a bunch of work. Then out the other side is something that our computers can work with and interpret and then respond to. Natural language processing works in two parts. The first piece to communicate with our device. When we communicate to the device, the language processor will take what we say and process that in. Then it will pull out the important piece of information and try to extract context from it.
After it extracts that then it returns to the API or to the system that is going to use and act on it. It returns to it what the language was and what the intent was.
For example, take the words running, jogging, and sprinting. Those words translate into the person is moving and that is what the application needs to know. Then that is what natural language processors will return. So what we get back then is running.
Next, the computer takes action on what it should do when this person says running. Then the computer can pass through the next step on its algorithm. It can decide that now it is going to return information to the user based on the idea that they said “running.” Regardless of whether the word is jogging, running. or sprinting, those could all be things that will translate into the word running back to the user.
Natural Language Processing In Logistics
Also, natural language processing is being used in the logistics industry. It takes what people say or what somebody writes into emails and takes action on it. For example, when you send a text message, that is natural language. Then that natural language will get translated and into the way a machine could work on it. It goes through a natural language processor and then the machine can behave.
So we may ask for something specific. An example would be if we want to get a rate or find the status of a shipment. Using natural language processing in logistics, we can ask the computer this question. Usually, this gets done by a bot also known as an automated chat device. Then the bot will respond with an answer. The answer goes based on what it extracted from the natural language processor.
How We Use Natural Language Processing
At Teknowlogi we do a lot of work with natural language processing. We also use other forms of AI and machine learning. We take that information and give practical applications back to the user. This helps them do their job better.
The logistics provider quoting is a great example of this. Let’s say an email gets sent in and that email is a request for a quote. Currently, a human has to go and read through that email. Then they have to extract information from it, for example, the ZIP codes and the weight and so forth. They extract this information from the email and then they put it into the computer. Next, they generate a quote and they draft an email in response back before sending it back to the customer.
At Teknowlogi we have something we call our TAI Advisor. Well, one of the things we are doing with Tai Advisor is using it to read an email. Then it can extract that information and reply to the user. It can tell the user the quote that it was able to run. So it can run the quote, generate the information, and create the response email back. It is using natural language processing and sending it back. So, it can automate that whole process and make it almost instant.
The Efficiency Of Using Machines
So with something like Tai Advisor you are getting a quote back to customers in one or two minutes. This is better than the current way where it can take hours depending on how busy that staff member is.
There is, even more, we can do with this. So let’s say the customer forgot to send us the weight. Well, we can’t give a quote on a lot of shipments if we don’t have a weight. So we could respond and tell them with the shipment type they are looking for a weight is necessary. We can ask the user for that weight.
Then when they do respond with the weight, the human can interact with it. Or the Tai Advisor can process it from there. Either way, it gives us more opportunity and it helps communicate back to the customer. We can extract more information from the customer with less effort from our staff. Natural language processing helps to free up our staff to help our customers in other ways.