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Why is NLP important?
Communication through text or speech is a common method of interaction among humans. Now, computers are
equipped with a technology called Natural Language Processing, enabling them to understand, learn, process, and
manipulate human language.
Applications of Natural Language Processing
Natural Language Processing (NLP) is at the forefront of bridging the gap between human communication and
machine intelligence. By enabling computers to understand, interpret, and generate human language, NLP has
become a transformative force in modern technology. Its applications are far-reaching, impacting nearly every
industry and aspect of daily life.
Some real-life applications of NLP are as follows:
• Automatic Text Summarisation: Automatic Text Summarisation is the process of creating the most meaningful
and relevant summary of voluminous texts from multiple sources. Google News, Blogspot, Inshorts app and
many other apps are dealing with text summarisation tasks by using Machine learning algorithms that helps in
producing short and relevant data from the multiple sources, by identifying the important sections in a huge
textual dataset.
Document Summary
There are two different approaches of creating Automatic
text summarisation:
o Extractive summarisation: In this approach, selected
text, phrases, sentences or sections are extracted from
the multiple sources and joined appropriately to form a
concise summary.
o Abstractive Summarisation: In this approach, the
summary is created by interpreting the text from multiple
sources using advanced NLP techniques. This new
summary may or may not have text, phrases or sentences from the original documents.
• Autogenerated Captions: NLP is used to produce
descriptive text for images, videos or real-world
contexts. They are widely used in areas such as social
media and content creation. The captions are generated
using speech-to-text and image-to-text features on a
real time basis. For example, Captions are automatically
generated for speech, in the language of the meeting,
using Instagram’s or YouTube’s captioning tools.
• Language Translation: It refers to the process of
converting text or speech from one language to another
using NLP. This technology aids in learning new languages
and facilitates cross-cultural understanding. The process
of language translation continues to evolve, with
advancements in AI and NLP making it increasingly fast,
accurate, and accessible. For example, Google Translate
uses deep learning models to improve translation quality
over time.
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