Pros and Cons of Computational Linguistics

Computational linguistics is, beyond any shadow of a doubt, one of the most challenging branches in IT field. Whereas other branches work based on very precise principles, computational linguistics strives to recreate or to model natural communication languages. The directions computational linguistics goes are pretty stunning, as these solutions deal with voice recognition tools, translation services, grammar and spelling solutions. Even though each one is a true challenge, some of the recent innovations in this field seem to integrate more than one option, as to diversity the utility of the application and to serve better customers’ requests. we should outline form the very beginning that the semantic and grammatical areas are definitely the top priority of all computational linguists.

Their efforts are shaped up in so many ways, yet, it seems that many of them are not 100% viable, meaning that they run but they fail in signalizing certain types of errors. For instance, grammar check software application is quite often unable to identify common errors. Many cannot explain why, as that grammar rule is usually taught in primary school and an advanced software cannot recognize it. The clue lies in the fact that, a software cannot think, it processes the information in a totally different manner, always functioning on a pre-established pattern. To put it differently, the tool is functional when recognizes correct grammar and mistakes. If none of these happens, your grammar check software is very likely to consider a grammar mistake as being absolutely correct.

Although online spell check was one of the first attempts in computational linguistics, the way IT experts have processed natural languages, has gone even further, and the best proofs in this sense are translation tools which have been optimized to store certain patterns from both languages, more precisely, the way users translated certain words, the terminology, and certain phrases. And when the software identifies the same words or structures, it can automatically translate the new text into a lexical or grammatical structure already processed. Semantics is another branch that has fused quite well with computer science. At this chapter, the offer is much diversified since this segment relies more on databases. These tools can provide synonyms, antonyms, and anything that might generate the same meaning but with other words or new meanings in opposition to a certain term. The latest applications can even generate rhymes as computational linguistics can identify words with the same phonetic structure.