Natural Language
Processing

What is Natural Language Processing ?

Since Natural Language Processing is a comprehensive problem, it is examined in different phases. By combining these phases, natural language processing applications are being developed.

Each of the following layers has separate specialties within themselves.

If it is desired to analyze and understand written data, tools in the fields of morphology, syntax and semantics are needed. However, in the case of data audio files, support should be obtained from phonetic and phonology layers in addition to these layers.

Natural Language Processing Phases

Phonetics

Layer of what people use when they speak language

Phonology

The layer that deals with audio associations that form the language

Morphology

The layer that examines additional structures and root structures of words in language

Syntax

The layer that deals with sentence structures

Semantics

The layer that deals with the meanings in the texts

Natural Language Processing in Written Content with Artiwise

Artiwise Text Analytics Platform enables you to use natural language processing techniques such as root reduction, trunking, morphological analysis, stemming without developing code. Artiwise currently supports English, Turkish, German, French and Spanish at linguistics level and has a plan to extend its capability with most known and spoken other languages.

The Natural Language Processing sub-discipline aims to mimic the ability of human to speak and especially to understand the spoken. The greatest talents that make people human are speaking and understanding. There are many words in the society that this is the most important feature that distinguishes man from other beings. For this reason, if we are talking about a humanoid computer, it is the most important features that the computer can understand and perform the speech of people. At the same time, many details, such as the differences in people’s use of language and their specificity, make this problem harder to solve.

The greatest motivation of this discipline is how people learn a language. For years, scientists who have tried to solve this language by transferring the rules of languages to computer environment have seen the impossibility of reaching a definite conclusion with these methods and have tried many kinds of artificial intelligence techniques. This problem is not a problem we can say today is fully solved. Languages live and change with people. Therefore, as long as people exist, these studies will continue.