What is Natural Language Processing?
Humans use language to express thoughts and communicate with others. However, can computers process and respond to human language in a meaningful way?
Natural Language Processing
(NLP) is an AI technology that enables computers to understand and utilize human language.
Natural Language Processing involves converting human language into a structured format that computers can interpret and then analyzing its meaning.
In this lesson, we will explore the concept of Natural Language Processing and its key applications.
What are the steps in Natural Language Processing?
Natural Language Processing involves converting sentences into a form that computers can understand and analyzing their meaning.
Since computers cannot directly comprehend human language, NLP technology processes sentences through the following stages.
1. Preprocessing
This is the process of removing unnecessary parts from a sentence and extracting essential information.
For example, preprocessing may involve removing punctuation or eliminating stop words — commonly used words such as “the” or “is” that carry little semantic value and do not contribute significantly to the meaning of a sentence.
text = "Hello! Wow, the weather is really nice today." preprocessed_text = "Hello the weather really nice today"
2. Morphological Analysis
Morphological analysis involves splitting sentences into words and identifying the part of speech (noun, verb, etc.) for each word.
For example, the sentence "I like apples" is divided into "I/pronoun"
, "like/verb"
, "apples/noun"
.
3. Vectorization
This is the process of converting the words separated through morphological analysis into numerical forms that computers can understand.
By representing words as vectors, which are numerical arrays, computers can begin to interpret the patterns and relationships within textual data.
For example, the word "apple" can be represented as the vector [0.1, 0.2, 0.3]
.
Key Applications of Natural Language Processing
The following are key applications of NLP technology:
1. Machine Translation
Machine translation is a technology that uses AI to translate one language into another.
Google Translate
and similar services are widely used examples, and the quality of translations improves as the model is trained on larger datasets.
2. Sentiment Analysis
Sentiment analysis is a technology that extracts emotions from a sentence.
It is used by companies to classify customer feedback as positive or negative, and is also applied in trend prediction through the analysis of social media data.
text = "This movie is really fun!" sentiment = "Positive"
3. Chatbots
Chatbots are conversational AIs that communicate naturally with people.
Chatbot services such as ChatGPT
, Perplexity
, and Claude
are widely used in customer service, reservation systems, and automated information delivery.
4. Speech Recognition
Speech recognition is the technology that converts spoken language into text.
It is used in voice assistants like Siri
and Google Assistant
.
This technology is also employed in transcription services that convert meeting recordings into written text automatically.
Natural Language Processing is utilized in various AI fields and is expected to further develop as a technology aiding communication between humans and computers.
On the practice screen, input the same prompt into different AI chatbots and compare their responses to observe how each model interprets natural language.
Send a question to the AI using the prompt below.
Hello, who are you?Lecture
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