What are the use cases for Natural Language Processing (NLP)?

NLP is used for several use cases, including creating models for:

1. Text Classification — a popular classification example is sentiment analysis where class labels are used to represent the emotional tone of the text, usually as “positive” or “negative“.

Further examples include:

Filtering spam — classifying email text as spam.

Language identification — classifying the language of the source text.

Genre classification — classifying the genre of a fictional story.

2. Language Modeling — a language model which learns the probabilistic relationships between words, enabling it to predict the next word — they are, however, also used for text or speech generation; for example, generating article headlines, new sentences, paragraphs, documents and continuation of a sentence.

3. Speech Recognition — a model for understanding speech to either generate text readable by humans, or issue commands.

Examples of where speech recognition can be used includes:

Transcribing a speech.

Creating text captions for a movie or TV show.

Issuing commands to the radio while driving.

4. Caption Generation — as the name suggests, this solves the problem of describing the contents of a digital image or video. This language model can be strategic as it allows you to create searchable text for search engines.

5. Machine Translation — focuses on solving the problem of translating one source text from one particular language into another language.

6. Document Summarisation — This looks to create a short description about a document. A language model is essentially used to output a summary of a document.

Applications can include:

7. Question Answering — as the name suggests, this involves building a model capable of taking a question posed in a natural language and providing an answer is