What Does A Mathematical Linguist Do?
"I am confused. If linguistics has to do with the science of language, how does mathematical linguistics fit into the picture? The term seems like an oxymoron. "
asked by Carmen from Taos, NM
At first glance, Mathematical Linguists probably does seem like an oxymoron. However, it can best be defined as a sub discipline of artificial intelligence. Computational linguistics (Mathematical Linguistics) comprises programming computers to generate language in the same manner as a human being.
Computational linguistics employ branch of learning such as math, linguistics and computer science. Linguists who choose to work in this field are able to find employment in the areas of technology, research and academia. A master’s degree, at the very least, is required to get your foot in the door.
Conventionally, computational linguistics was, for the most part, executed by computer scientists whose expertise lies in the implementation of computers for natural language generation. In general, computational linguistics require the contributions of among others, linguists, sages in artificial intelligence, computer science experts, logicians, mathematicians, philosophers, neuroscientists, cognitive psychologists and scientists, anthropologists and psycholinguists.
This sub discipline encompasses both theoretical and applied elements, whereas theoretical computational linguistics speaks toward matters in theoretical linguistics and cognitive science. Conversely, applied computational linguistics addresses the concrete results of forming human language usage.
Computational linguistics precedes artificial intelligence—a field in which it is frequently categorized. Computational linguistics was developed due to the United States’ endeavors to use computers as a vessel proficient at automatically translating data from foreign languages—chiefly Russian scientific journals–into English.
Because computers are able to make algebraic calculations quickly and more precisely than humans, it was prematurely assumed that it would only be a matter of time before technological advancements would facilitate the comparable extraordinary aptitude to manage language.
Hence, when mechanical translation was unsuccessful in producing immediate, accurate translations, it became clear that the automatic production of human languages was much more complex than initially presumed. Computational linguistics came to be the name of that field of study dedicated to creating algorithms and software that would judiciously and accurately process language files.
In the 1960s, when artificial intelligence was born, the computational linguistics field developed into that sub-discipline of artificial intelligence that concerned itself with human-quality production and understanding of natural languages.
To be able to translate languages one to another, the necessity of having knowledge of both languages’ grammar systems became obvious. It follows then, that the understanding of both languages’ morphology (word forms) and syntax (sentence structure), was also required. To continue, if one wished to understand syntax, knowledge of the lexicon and semantics of the languages was also a prerequisite, as was the pragmatics of how people use language.
As a result, what began as an attempt at translation between languages developed into a full-blown discipline dedicated to discerning the manner in which computers facilitate the representation and processing of natural languages.
Today, research within the microcosm of this discipline is performed in computational linguistics’ departments and laboratories, and in computer science and linguistics’ departments.
As our understanding about the way a person’s language and linguistic abilities perpetually change and improves throughout their lifetime due to the usage of neural networks and robotics, we must keep in mind that languages develop and evolve over time, as well.
Computational methodologies to aid in the comprehension of this wonder have uncovered fascinating information. Researchers have generated a system that not only calculates future linguistic progression, but also provides insight to the history and evolution of the languages we speak today.
What would have otherwise been impossible was accomplished through this computational linguistics-modeling endeavor.
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