Natural language processing (NLP) is a branch of artificial intelligence that helps computers understand, interpret and manipulate human language.
Using Natural language processing (NLP), developers can organize and structure knowledge to perform tasks such as automated summaries, translations, identification of designated entities, etc.
We may speak to each other, as a species, more than we write. Voice and text are how we communicate with each other.
Given the importance of this type of data, we must have methods to understand and reason about natural language.
How does Natural Language Processing Works?
In natural language processing, human language is separated into fragments so that the grammatical structure of sentences and the meaning of words can be analyzed and understood in context.
It helps computers to read and understand spoken or written text just like humans.
Here are some techniques that power Natural language processing:
Tokenization:
It breaks down text into smaller semantic units. After breaking the input into sentences, the next step is to break the sentences into tokens.
Lemmatization:
It standardizes words by reducing them to their original form. In other words, it is the process of finding the root word of a given word.
Stop words removal:
It filters out common words that add little or no unique information. For example, prepositions and articles (at, to, a, the).
Part-of-speech-tagging:
In this step, each token is analyzed and classified into different parts of speech. It marks nouns, verbs, adjectives, adverbs, pronouns, etc.
Why is Natural language processing (NLP) important?
Firstly, humans communicate with each other majorly in terms of voice and text. And, we build many products and applications around these communication modes.
If you are a Business handling thousands of calls and emails everyday, NLP systems can save a lot of money and time for your organization.
Secondly, today’s machines can analyze more language-based data than humans without getting tired and in a coherent, unbiased way.
So, considering the sheer amount of obsolete data generated on a daily basis, it would be difficult to fully analyze text and speech data efficiently.
In addition, NLP is important because it helps resolve language ambiguities and adds useful numerical structure to data for many downstream applications, such as speech recognition or text analytics.
Applications of NLP:
- Language translation applications such as Google Translate
- Search autocorrect and autocomplete
- Interactive Voice Response (IVR) applications used in call centers to respond to certain users’ requests
- Social media monitoring
- Personal assistant applications such as OK Google, Siri, Cortana, and Alexa.
- It can help the companies improve their products, and also keep the customers satisfied.
Summary
In conclusion, as per the definition of Wikipedia, “natural language processing is the field of study that focuses on the interactions between human language and computers”.
So, here, we have learnt about how NLP works, why and how important it is and more.
