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Natural language processing is a combination of artificial intelligence and computer science that deals with the way humans and computers communicate (via text and speech) with each other. Before the development of artificial intelligence, computers were only able to complete tasks that they were programmed to do. Computers were unable to think on their own. Users had to input all data by typing. Now, machine learning software enables a computer to use natural language from humans to complete a wide variety of advanced tasks. Innovative programmer, Austin Alexander Burridge of Rosemount, IL, believes natural language processing used in machine learning algorithms is poised to revolutionize development platforms in several significant technical fields such as voice recognition, text summarization, machine translation, question answering, autocomplete and predictive typing, and spam detection.
In this article, Mr. Burridge expands on several of these developments.
#1 Voice Recognition
Voice recognition – also known as speech recognition – is the ability of a computer to recognize and respond to human voice commands in real-time. For example, smart home devices respond to voice commands when users tell them to perform tasks like these:
- Check the weather.
- Check the news.
- Turn on/off lights.
- Adjust the thermostat.
- Make a list.
Speech recognition software is also used to interpret dictation from recordings. For example, when a doctor dictates her patient notes, she can upload them to a computer. The computer can then use natural language processing software to interpret medical terminology and search for information in online databases.
#2 Text Summarization
The amount of text data online is vast and continues to grow each day. Therefore, text summarization is needed to summarize this large amount of online text. That way, machine learning platforms can accurately analyze text data. Otherwise, natural language processing would take much longer, and it would be less accurate. For example, if you asked your smart device to look up something online, it would take a long time to find the answer.
#3 Machine Translation
Machine translation software translates text in one natural language (like English) into another natural language (like Chinese) in real-time. For example, let’s say a person in New York sends an email to someone in Shanghai. The person in New York will type her message in English. However, the person in Shanghai will read the message in Chinese. Machine translation has become vitally important to international businesses that have workers who speak different languages.
#4 Question Answering
Question answering software uses natural language processing to answer a question asked by a human. For example, when you ask a smart device to find information, the device is using question answering software. The software queries online databases to find information to answer the user’s question.
#5 Autocomplete and Predictive Typing
Autocomplete – also known as predictive typing – uses machine learning algorithms to “complete” words that a user begins typing. The autocomplete system tries to learn what a user (typically) types when they start entering a certain combination of characters. A good example of autocomplete is when you begin typing a search query on Google, several possible options display below the text box. Predictive typing is also used a lot for typing text messages on mobile phones.
#6 Spam Detection
A spam detection filter is exactly what it sounds like. A good example is the spam folder in your email account. Your email provider uses machine learning algorithms to detect (likely) spam email messages. The email provider’s spam detection software uses the number of email recipients to determine if an email is (likely) spam. Also, many of the newer smartphones are incorporating spam detection filters to block (likely) spam text messages.
In short, natural language processing is changing the way that computers and people communicate with each other. Without natural language processing, you wouldn’t be able to control your smart home devices with voice commands. Text summarization is the reason that machine learning algorithms can search and analyze vast amounts of text data online.
Machine translation is making it possible for two (or more) people who speak different languages to communicate with each other in real-time. Question answering software enables your smart devices to search online for information that you request. Autocomplete and predictive typing machine learning algorithms reduce the amount of typing that you have to do when entering text. Lastly, spam detection filters keep your email’s inbox from getting cluttered with spam messages.
