Applications of NLP

Six applications, and the board picks one, describes it, and asks you to name it. So learn these by what they do, not by their order in a list.

1The six applications

Application	What it does	Example
Voice assistants	Take natural speech, process it and give an output	“Hey Google, set an alarm at 3:30 pm”
Autogenerated captions	Turn natural speech into text in real time	Captions on YouTube and Google Meet
Language translation	Convert text or speech from one language to another	Google Translate
Sentiment analysis	Express an opinion — whether the sentiment is positive, negative or neutral	Detecting emotion in customer reviews
Text classification	Classify a sentence or document category-wise into predefined groups	Sorting news into Food, Sports, Politics
Keyword extraction	Automatically pull out the most used, important words and expressions	Finding what people say about a business on social media

2The two that get confused

Sentiment analysis vs text classification

Both sort text into groups, so read what the groups are.
Sentiment analysis sorts by feeling— positive, negative or neutral. If the question mentions an opinion, a review, a mood or an emotion, this is it.
Text classification sorts by subjectinto predefined categories — sport, politics, food.

Keyword extraction

Keyword extraction does not sort anything. It pulls the important words out of a text. It is useful for summarising documents, retrieving information and analysing content.

3Where sentiment analysis is examined

The use case is a practical

The syllabus lists NLP: Use Case Walkthrough— sentiment analysis built in Orange Data Mining — under “to be assessed through Practicals”. For the written paper you need to know what sentiment analysis is and what it is for; building it is lab work.

Two uses of sentiment analysis the handbook names:

Customer service — automatically detecting emotions when customers interact with a product, service or brand.
Voice of the customer — analysing feedback to measure the gap between what customers expect and what they actually get.

4From the board papers

________ is an NLP tool to express an opinion, whether the underlying sentiment is positive, negative or neutral.
(a) Text Classification (b) Machine Translation (c) Sentiment Analysis (d) Automatic Text SummarizationClass X handbook, and the 2023–24 / 2024–25 sample papers

1 mark

▶Show the answer

(c) Sentiment Analysis. The three words positive, negative, neutral appear in no other definition in this unit.

Aditi developed a chatbot that clarifies the doubts of Economics students. She trained it with lots of datasets; if a student types or asks a question related to Economics, the software gives an instant reply. Identify the domain of AI in this scenario.CBSE sample papers 2023–24 and 2024–25

1 mark

▶Show the answer

Natural Language Processing. What goes in is typed or spoken language, not images and not a table of numbers.

Identify the application of NLP: classifying raw text into pre-defined groups.CBSE board exam 2026

1 mark

▶Show the answer

Text Classification. The phrase pre-defined groups is the giveaway — somebody decided the categories in advance. Sentiment analysis has only ever three groups, and they are feelings.

5Check yourself

Quick Check

Turning natural speech into text in real time on a video is:

Quick Check

A tool that automatically pulls the most important words out of a text is:

Quick Check

Analysing customer reviews to find whether people feel positive or negative is:

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