Natural Language Processing – Artiwise

Natural Language Processing

What is Natural Language Processing?

Since natural language processing is a comprehensive problem, it is examined in different phases and natural language processing applications are developed by combining these phases. Each of the following layers contains separate specialties.

If it is desired to analyze and understand a written data, there is a need for dominant tools from these layers in morphology, syntax and semantics. However, if the data is in the form of an audio file, in addition to these layers, support should be obtained from the phonetic and phonology layers.

Natural Language Processing Phases


The layer that deals with what sounds people use when speaking the language


The layer that deals with the sound associations that make up the language


The layer that examines the structures (affix-root) of words in the language


The layer that deals with sentence structures


The layer that deals with sentence structures

Ease of Natural Language Processing in Written and Audio Content with Artiwise Analytics

Artiwise Analytcis allows you to use natural language processing techniques such as root reduction, stemming, morphological analysis, Turkish character correction and named asset detection without the need to code and develop technically. Artiwise aims to develop its natural language processing studies, which are specific to Turkish, English, Arabic, German, French and Spanish languages, for other languages that are used widely in the world.

Natural language processing sub-discipline aims to imitate people’s ability to speak and especially understand what is spoken. The greatest talents that make people human are speaking and understanding each other. There are many sayings 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, the most important features of these computers are that they can understand people’s speech and take actions based on what they understand. At the same time, many details, such as the distinctive differences that arise when people use the language, make it difficult to solve this problem.

The greatest motivation of this branch of science has always been how people learn a language. Scientists, who have been trying to solve this work by transferring the rules of languages to the computer environment for years, have seen the impossibility of reaching a definitive conclusion with these methods and have tried the use of artificial intelligence techniques in many types. This problem has not been solved completely today. Languages live, evolve and change with humans. For this reason, these studies will continue to be carried out as long as people exist.