CBSE Textbook: Natural Language Processing - Class 10 PDF Download

 Page 1


 
 
6.1 Introduction 
A natural language is a human language, such as French, Spanish, English, Japanese, etc. 
Features of Natural Languages 
• They are governed by set rules that include syntax, lexicon, and semantics. 
• All natural languages are redundant, i.e., the information can be conveyed in multiple 
ways. 
• All natural languages change over time. 
Test Yourself: 
Choose the right word: 
1. I am so tired; I want to take a ? 
 
 
2. Let’s her a letter. 
 
 
 
Do you see how same-sounding words can have totally different meanings? 
• Different meanings in different contexts. 
Let’s consider these three sentences: 
His face turned red after he found out that he took the wrong bag. 
What does this mean? Is he feeling ashamed because he took another person’s bag instead of 
his? Is he feeling angry because he did not manage to steal the bag that he has been 
targeting? 
 
 
The red car zoomed past his nose. 
Probably talking about the colour of the car 
 
 
 
Page 2


 
 
6.1 Introduction 
A natural language is a human language, such as French, Spanish, English, Japanese, etc. 
Features of Natural Languages 
• They are governed by set rules that include syntax, lexicon, and semantics. 
• All natural languages are redundant, i.e., the information can be conveyed in multiple 
ways. 
• All natural languages change over time. 
Test Yourself: 
Choose the right word: 
1. I am so tired; I want to take a ? 
 
 
2. Let’s her a letter. 
 
 
 
Do you see how same-sounding words can have totally different meanings? 
• Different meanings in different contexts. 
Let’s consider these three sentences: 
His face turned red after he found out that he took the wrong bag. 
What does this mean? Is he feeling ashamed because he took another person’s bag instead of 
his? Is he feeling angry because he did not manage to steal the bag that he has been 
targeting? 
 
 
The red car zoomed past his nose. 
Probably talking about the colour of the car 
 
 
 
 
 
His face turns red after consuming the medicine. 
Is he having an allergic reaction? Or was he ashamed because he lost a bet (“I will not fall 
sick because of this”)? Or was he taking a medicine that dilates the artery? 
 
 
Here we can see that context is important. We understand a sentence almost intuitively, 
depending on our history of using the language, and the memories that have been built 
within. In all three sentences, the word red has been used in three different ways which 
according to the context of the statement changes its meaning completely. Thus, in natural 
language, it is important to understand that a word can have multiple meanings and the 
meanings fit into the statement according to the context of it. 
 
 
Think of some other words which can have multiple meanings and use them in sentences. 
 
 
 
 
 
 
 
Computer Language 
Computer languages are languages used to interact with a computer, such as Python, C++, 
Java, HTML, etc. 
 
 
Can computers understand our language? 
Computers require a specific set of instructions to 
understand human input called programs. To talk to a 
computer, we convert natural language into a 
language that a computer understands. We need 
Natural Language Processing to help computers 
understand natural language. 
Why is NLP important? 
Computers can only process electronic signals in the 
form of binary language. Natural Language Processing 
facilitates this conversion to digital form from the 
natural form. Thus, the whole purpose of NLP is to 
make communication between computer systems and 
humans possible. This includes creating different tools 
and techniques that facilitate better communication of 
intent and context. 
 
Page 3


 
 
6.1 Introduction 
A natural language is a human language, such as French, Spanish, English, Japanese, etc. 
Features of Natural Languages 
• They are governed by set rules that include syntax, lexicon, and semantics. 
• All natural languages are redundant, i.e., the information can be conveyed in multiple 
ways. 
• All natural languages change over time. 
Test Yourself: 
Choose the right word: 
1. I am so tired; I want to take a ? 
 
 
2. Let’s her a letter. 
 
 
 
Do you see how same-sounding words can have totally different meanings? 
• Different meanings in different contexts. 
Let’s consider these three sentences: 
His face turned red after he found out that he took the wrong bag. 
What does this mean? Is he feeling ashamed because he took another person’s bag instead of 
his? Is he feeling angry because he did not manage to steal the bag that he has been 
targeting? 
 
 
The red car zoomed past his nose. 
Probably talking about the colour of the car 
 
 
 
 
 
His face turns red after consuming the medicine. 
Is he having an allergic reaction? Or was he ashamed because he lost a bet (“I will not fall 
sick because of this”)? Or was he taking a medicine that dilates the artery? 
 
 
Here we can see that context is important. We understand a sentence almost intuitively, 
depending on our history of using the language, and the memories that have been built 
within. In all three sentences, the word red has been used in three different ways which 
according to the context of the statement changes its meaning completely. Thus, in natural 
language, it is important to understand that a word can have multiple meanings and the 
meanings fit into the statement according to the context of it. 
 
 
Think of some other words which can have multiple meanings and use them in sentences. 
 
 
 
 
 
 
 
Computer Language 
Computer languages are languages used to interact with a computer, such as Python, C++, 
Java, HTML, etc. 
 
 
Can computers understand our language? 
Computers require a specific set of instructions to 
understand human input called programs. To talk to a 
computer, we convert natural language into a 
language that a computer understands. We need 
Natural Language Processing to help computers 
understand natural language. 
Why is NLP important? 
Computers can only process electronic signals in the 
form of binary language. Natural Language Processing 
facilitates this conversion to digital form from the 
natural form. Thus, the whole purpose of NLP is to 
make communication between computer systems and 
humans possible. This includes creating different tools 
and techniques that facilitate better communication of 
intent and context. 
 
 
 
Demystify Natural Language Processing (NLP) 
Natural Language Processing, or NLP, is the sub-field of AI that is focused on enabling 
computers to analyse, understand and process human languages to derive meaningful 
information from human language. 
 
 
 
6.2 Applications of Natural Language Processing 
Since Artificial Intelligence nowadays is becoming an integral part of our lives, its 
applications are very commonly used by the majority of people in their daily lives. Here are 
some of the applications of Natural Language Processing which are used in the real-life 
scenario: 
 
 
Autogenerated captions: Captions are 
generated by turning natural speech into text in 
real-time. It is a valuable feature for enhancing 
the accessibility of video content. 
For example: 
Auto-generated captions on YouTube and Google 
Meet. 
 
 
 
Voice assistants: Voice assistants take 
our natural speech, process it, and give 
us an output. These assistants leverage 
NLP to understand natural language and 
execute tasks efficiently.  
For example: 
Hey Google, set an alarm at 3.30 pm 
Hey Alexa, play some music 
Hey Siri, what's the weather today 
  
Language Translation: It incorporates 
the generation of translation from another 
language. This involves the conversion of text 
or speech from one language to another, 
facilitating cross-linguistic 
communication and fostering global 
connectivity. 
For example: 
Google Translate 
Page 4


 
 
6.1 Introduction 
A natural language is a human language, such as French, Spanish, English, Japanese, etc. 
Features of Natural Languages 
• They are governed by set rules that include syntax, lexicon, and semantics. 
• All natural languages are redundant, i.e., the information can be conveyed in multiple 
ways. 
• All natural languages change over time. 
Test Yourself: 
Choose the right word: 
1. I am so tired; I want to take a ? 
 
 
2. Let’s her a letter. 
 
 
 
Do you see how same-sounding words can have totally different meanings? 
• Different meanings in different contexts. 
Let’s consider these three sentences: 
His face turned red after he found out that he took the wrong bag. 
What does this mean? Is he feeling ashamed because he took another person’s bag instead of 
his? Is he feeling angry because he did not manage to steal the bag that he has been 
targeting? 
 
 
The red car zoomed past his nose. 
Probably talking about the colour of the car 
 
 
 
 
 
His face turns red after consuming the medicine. 
Is he having an allergic reaction? Or was he ashamed because he lost a bet (“I will not fall 
sick because of this”)? Or was he taking a medicine that dilates the artery? 
 
 
Here we can see that context is important. We understand a sentence almost intuitively, 
depending on our history of using the language, and the memories that have been built 
within. In all three sentences, the word red has been used in three different ways which 
according to the context of the statement changes its meaning completely. Thus, in natural 
language, it is important to understand that a word can have multiple meanings and the 
meanings fit into the statement according to the context of it. 
 
 
Think of some other words which can have multiple meanings and use them in sentences. 
 
 
 
 
 
 
 
Computer Language 
Computer languages are languages used to interact with a computer, such as Python, C++, 
Java, HTML, etc. 
 
 
Can computers understand our language? 
Computers require a specific set of instructions to 
understand human input called programs. To talk to a 
computer, we convert natural language into a 
language that a computer understands. We need 
Natural Language Processing to help computers 
understand natural language. 
Why is NLP important? 
Computers can only process electronic signals in the 
form of binary language. Natural Language Processing 
facilitates this conversion to digital form from the 
natural form. Thus, the whole purpose of NLP is to 
make communication between computer systems and 
humans possible. This includes creating different tools 
and techniques that facilitate better communication of 
intent and context. 
 
 
 
Demystify Natural Language Processing (NLP) 
Natural Language Processing, or NLP, is the sub-field of AI that is focused on enabling 
computers to analyse, understand and process human languages to derive meaningful 
information from human language. 
 
 
 
6.2 Applications of Natural Language Processing 
Since Artificial Intelligence nowadays is becoming an integral part of our lives, its 
applications are very commonly used by the majority of people in their daily lives. Here are 
some of the applications of Natural Language Processing which are used in the real-life 
scenario: 
 
 
Autogenerated captions: Captions are 
generated by turning natural speech into text in 
real-time. It is a valuable feature for enhancing 
the accessibility of video content. 
For example: 
Auto-generated captions on YouTube and Google 
Meet. 
 
 
 
Voice assistants: Voice assistants take 
our natural speech, process it, and give 
us an output. These assistants leverage 
NLP to understand natural language and 
execute tasks efficiently.  
For example: 
Hey Google, set an alarm at 3.30 pm 
Hey Alexa, play some music 
Hey Siri, what's the weather today 
  
Language Translation: It incorporates 
the generation of translation from another 
language. This involves the conversion of text 
or speech from one language to another, 
facilitating cross-linguistic 
communication and fostering global 
connectivity. 
For example: 
Google Translate 
 
 
 
Sentiment Analysis: Sentiment Analysis is a 
tool to express an opinion, whether the 
underlying sentiment is positive, negative, or 
neutral. Customer sentiment analysis helps in the 
automatic detection of emotions when 
customers interact with the products, services, or 
brand 
 
 
Text Classification: Text classification is 
a tool which classifies a sentence or 
document category-wise. 
In the example, we can observe news 
articles containing information on various 
sectors, including Food, Sports, and Politics, 
being categorized through the text 
classification process. This process classifies 
the raw texts into predefined groups or 
categories. 
 
 
Keyword Extraction: Keyword extraction is a 
tool that automatically extracts the most used, 
important words and expressions from a text. It 
can give valuable insights into people’s opinions 
about any business on social media. Customer 
Service can be improved by using a Keyword 
extraction tool. 
 
 
Activity 1: Keyword Extraction 
 
 
Purpose: To learn how to utilize an API for performing keyword extraction from a website. 
 
 
Say: “Keyword extraction in NLP involves automatically identifying and extracting the most important 
words or phrases from a piece of text. These keywords represent the main topics or themes within 
the text and are useful for tasks like document summarization, information retrieval, and 
content analysis.” 
Page 5


 
 
6.1 Introduction 
A natural language is a human language, such as French, Spanish, English, Japanese, etc. 
Features of Natural Languages 
• They are governed by set rules that include syntax, lexicon, and semantics. 
• All natural languages are redundant, i.e., the information can be conveyed in multiple 
ways. 
• All natural languages change over time. 
Test Yourself: 
Choose the right word: 
1. I am so tired; I want to take a ? 
 
 
2. Let’s her a letter. 
 
 
 
Do you see how same-sounding words can have totally different meanings? 
• Different meanings in different contexts. 
Let’s consider these three sentences: 
His face turned red after he found out that he took the wrong bag. 
What does this mean? Is he feeling ashamed because he took another person’s bag instead of 
his? Is he feeling angry because he did not manage to steal the bag that he has been 
targeting? 
 
 
The red car zoomed past his nose. 
Probably talking about the colour of the car 
 
 
 
 
 
His face turns red after consuming the medicine. 
Is he having an allergic reaction? Or was he ashamed because he lost a bet (“I will not fall 
sick because of this”)? Or was he taking a medicine that dilates the artery? 
 
 
Here we can see that context is important. We understand a sentence almost intuitively, 
depending on our history of using the language, and the memories that have been built 
within. In all three sentences, the word red has been used in three different ways which 
according to the context of the statement changes its meaning completely. Thus, in natural 
language, it is important to understand that a word can have multiple meanings and the 
meanings fit into the statement according to the context of it. 
 
 
Think of some other words which can have multiple meanings and use them in sentences. 
 
 
 
 
 
 
 
Computer Language 
Computer languages are languages used to interact with a computer, such as Python, C++, 
Java, HTML, etc. 
 
 
Can computers understand our language? 
Computers require a specific set of instructions to 
understand human input called programs. To talk to a 
computer, we convert natural language into a 
language that a computer understands. We need 
Natural Language Processing to help computers 
understand natural language. 
Why is NLP important? 
Computers can only process electronic signals in the 
form of binary language. Natural Language Processing 
facilitates this conversion to digital form from the 
natural form. Thus, the whole purpose of NLP is to 
make communication between computer systems and 
humans possible. This includes creating different tools 
and techniques that facilitate better communication of 
intent and context. 
 
 
 
Demystify Natural Language Processing (NLP) 
Natural Language Processing, or NLP, is the sub-field of AI that is focused on enabling 
computers to analyse, understand and process human languages to derive meaningful 
information from human language. 
 
 
 
6.2 Applications of Natural Language Processing 
Since Artificial Intelligence nowadays is becoming an integral part of our lives, its 
applications are very commonly used by the majority of people in their daily lives. Here are 
some of the applications of Natural Language Processing which are used in the real-life 
scenario: 
 
 
Autogenerated captions: Captions are 
generated by turning natural speech into text in 
real-time. It is a valuable feature for enhancing 
the accessibility of video content. 
For example: 
Auto-generated captions on YouTube and Google 
Meet. 
 
 
 
Voice assistants: Voice assistants take 
our natural speech, process it, and give 
us an output. These assistants leverage 
NLP to understand natural language and 
execute tasks efficiently.  
For example: 
Hey Google, set an alarm at 3.30 pm 
Hey Alexa, play some music 
Hey Siri, what's the weather today 
  
Language Translation: It incorporates 
the generation of translation from another 
language. This involves the conversion of text 
or speech from one language to another, 
facilitating cross-linguistic 
communication and fostering global 
connectivity. 
For example: 
Google Translate 
 
 
 
Sentiment Analysis: Sentiment Analysis is a 
tool to express an opinion, whether the 
underlying sentiment is positive, negative, or 
neutral. Customer sentiment analysis helps in the 
automatic detection of emotions when 
customers interact with the products, services, or 
brand 
 
 
Text Classification: Text classification is 
a tool which classifies a sentence or 
document category-wise. 
In the example, we can observe news 
articles containing information on various 
sectors, including Food, Sports, and Politics, 
being categorized through the text 
classification process. This process classifies 
the raw texts into predefined groups or 
categories. 
 
 
Keyword Extraction: Keyword extraction is a 
tool that automatically extracts the most used, 
important words and expressions from a text. It 
can give valuable insights into people’s opinions 
about any business on social media. Customer 
Service can be improved by using a Keyword 
extraction tool. 
 
 
Activity 1: Keyword Extraction 
 
 
Purpose: To learn how to utilize an API for performing keyword extraction from a website. 
 
 
Say: “Keyword extraction in NLP involves automatically identifying and extracting the most important 
words or phrases from a piece of text. These keywords represent the main topics or themes within 
the text and are useful for tasks like document summarization, information retrieval, and 
content analysis.” 
 
 
STEP – 1: Go to the given website: 
https://cloud.google.com/natural-language 
 
 
 
 
STEP – 2: Click on ‘Analyze’ and check the results. 
 
 
 
• The keywords from the 
paragraph in the textbox have 
been highlighted in different 
colours e.g., Google, Mountain 
View, etc. 
 
• Click on other options to check 
the output. 
 
• Use your own text in the text box 
and observe the results.