Words are all around us – in the form of spoken language, texts, sound bytes and even videos. The world would have been a chaotic place had it not been for words and languages that help us communicate with each other.
Now, if we were to enhance language with the attributes of artificial intelligence, we would be working with what is known as Natural Language Processing or NLP – the confluence of artificial intelligence and computational linguistics.
In other words, “NLP is the machine’s ability to process what was said to it, structure the information received, determine the necessary response and respond in a language that we understand”.
Here is a list of popular applications of NLP in the modern world.
1. Machine Translation
When a machine translates from one language to another, “we deal with “Machine” Translation. The idea behind MT is simple — to develop computer algorithms to allow automatic translation without any human intervention. The best-known application is probably Google Translate.”
2. Voice and Speech Recognition
Though voice recognition technology has been around for 50 years, it is only in the last few decades, owing to NLP, have scientists achieved significant success in the field. “Now we have a whole variety of speech recognition software programs that allow us to decode the human voice,”be it in mobile telephony, home automation, hands-free computing, virtual assistance and video games.
3. Sentiment Analysis
“Sentiment analysis (also known as opinion mining or emotion AI) is an interesting type of data mining that measures the inclination of people’s opinions. The task of this analysis is to identify subjective information in the text”. Companies use sentiment analysis to keep abreast of their reputation and customer satisfaction.
4. Question Answering
Question-Answering concerns building systems that “automatically answer questions posed by humans in a natural language”. The real examples of Question-Answering applications are: Siri, OK Google, chat boxes and virtual assistants.
5. Automatic Summarization
Automatic Summarization is the process of creating a short, accurate, and fluent summary of a longer text document. The most important advantage of using a summary is it reduces the time taken to read a piece of text. Here are some applications – Aylien Text Analysis, MeaningCloud Summarization, ML Analyzer, Summarize Text and Text Summary.
6. Chatbots
Chatbots currently operate on several channels like the Internet, web applications and messaging platforms. “Businesses today are interested in developing bots that can not only understand a person but also communicate with him at one level”.
While such applications celebrate the use of NLP in modern computing, there are some glitches that arise in systems that cannot be ignored. “The very nature of human natural language makes some NLP tasks difficult…For example, the task of automatically detecting sarcasm, irony, and implications in texts has not yet been effectively solved. NLP technologies still struggle with the complexities inherent in elements of speech such as similes and metaphors.”
To know more, do take a look at the DexLab Analytics website. DexLab Analytics is a premiere institute that trains professionals in NLP deep learning classification in Delhi.
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