NLP drives computer programs that translate text from one language to another, respond to spoken commands, and summarize large volumes of text rapidly—even in real time.
Like - Text to text generation, content creation, theme estimation, sentiment analysis, spam detection, virtual assistance

Analyze the sentiment(behavior) of users to the particular topic/entity. In the education sector how much efficient a student write, can talk?
It is a way to get an idea about the user’s behavior and mental health to the entity whether he thinking positive, negative, or neutral.
Example - Social media trend topic analysis, political activity, a person’s behaviour to another person.

Toolkit is CMU Sphinx which is an open-source toolkit used for speech recognition, it also has a lightweight recognizer library called Pocketsphinx which will be used to recognize the speech. This library is a great resource especially when you are offline as when you have internet access you should prefer Google API with speech recognition due to higher precision. Recognize our voice, it takes a waveform and then splits it according to utterances by silence then traverses and tries to find out what is being said in each utterance for accomplishing this task it takes all possible combinations of words and try to match them with audio choosing the best matching combination.