Natural Language Processing
We facilitate human-machine interaction
The evolution of "intelligent machines" that are able to understand and respond to «human» communication lies in the recognition of a user's intent and sentiments
Natural Language Processing: what it is and what it consists of
What does Natural Language Processing (NLP) mean?
The exact definition of the term “Natural Language Processing” is “Natural Language Processing”.“Natural Language Processing” can be defined as a subject or a branch of Artificial Intelligence (A.I.). Its purpose is to make human language understandable to machines and allow the latter to correctly process the text or speech data sent/received.
What are the Natural Processing Language phases
In this phase, the machine recognizes what is said to it, segments the speech and then separates it into words, before performing a vocal synthesis and further segmentation of the words (also called "tokenization").
Indeed, once the speech has been codified and understood (word for word), the sentiment has been analyzed and particular attitudes, such as sarcasm, confusion and other emotions related to the text or audio, have been detected, the machine formulates what is required to correctly respond to the inputs received. It will then respond in the same way, i.e. via text or speech.
Morphological segmentation and tagging of specific parts of speech will follow. These operations are used to identify the correct meaning of words inserted in a given context and recognize if they can serve as parts of the discourse.
For example, the machine recognizes that the word "pencil" can be a noun ("the pencil is on the table"), can be linked to a verb ("pick up a pencil") and so on.
However, the machine must be able to recognize that the same term cannot be used as an adjective. Indeed, used as an adjective, the term "pencil" will have no meaning. The human language is very complex and it is often very difficult to correctly analyze the meaning of a sentence or single words.
Without a shadow of a doubt, the main problems derive from: homonyms, metaphors, idioms, grammatical exceptions and so on.
Furthermore, the processes of stemming (reduction of inflected words to a basic form) and lemmatization (removal of inflectional endings and return of the word to the basic form) are also part of this phase.
Named Entity Recognition (NER) and Sentiment Analysis (which we will discuss in more detail in the paragraphs below) complete the list of activities included in this phase.