When you talk to your virtual companion, use a voice assistant, or rely on an online translator, you’re witnessing a technological marvel. But how is it possible that a machine “understands” human speech, with all its richness, nuances, and chaos? The answer is Natural Language Processing, or NLP for short.
NLP is the bridge between the world of human communication and the binary logic of a computer. It’s code that learns to listen. Let’s go behind the scenes to understand, in simple terms, how it works.
Step 1: Slicing the Sentence into Pieces (Tokenization)
The first challenge for a computer is that it doesn’t see a sentence like we do. For it, it’s just a string of characters. Therefore, the first, absolutely crucial step is tokenization.
Imagine you get the sentence “I love talking to AI!” and you cut it with scissors into the smallest meaningful fragments. That’s what tokenization is. The system divides text into small units, called tokens, which can be words or even punctuation marks.
Our sentence after tokenization would look like this: ["I", "love", "talking", "to", "AI", "!"]
Thanks to this, the machine no longer has one long, incomprehensible string, but a collection of individual building blocks it can start working with.
Step 2: Turning Words into Numbers (Vectorization and Embeddings)
Computers have a secret: they hate text, but they love numbers. Therefore, each of our tokens must be converted into a numerical form. This process is called
vectorization or creating embeddings.
Each token receives its unique vector, which is a list of numbers. You can compare it to giving each word unique coordinates on a gigantic, multi-dimensional map.
Most importantly, these numbers are not random. During training, the model learns to arrange words on this map so that those with similar meanings are close to each other. For example, the vectors for “king” and “queen” will be much closer to each other than the vectors for “king” and “car.”
Step 3: Finding Meaning in Numbers (Analysis and Understanding)
Once we have our words converted into numbers that carry meaning, the AI can start to work. Using advanced techniques, it analyzes the relationships between these vectors to understand:
- Grammar (syntactic analysis): It recognizes which word is a noun and which is a verb, and how they combine in a sentence to create a logical structure.
- Meaning (semantic analysis): It tries to understand the true sense and intention of the utterance, taking context into account. It recognizes whether the word “lock” means a building or a door mechanism, based on other words in the sentence.
Code That Truly Listens
This entire process – from slicing a sentence into tokens, to converting them into meaningful numbers, to analyzing the relationships between them – allows the machine to “listen.” It’s thanks to this that your virtual companion can answer questions, translate languages, analyze your emotions, and hold a conversation that seems so natural.
It’s a complex field, combining linguistics, mathematics, and computer science. But at its heart is a simple idea: to translate our beautiful, human language into something that code can process and understand.