Computational linguistics involves psychology, linguistics, logic, and computer science to improve automation of translation, generation, speech, and understanding. It was born after failed attempts at machine translation in the late 1940s. The field has made progress in machine translation, speech recognition, speech generation, and automated grammar proofing systems. It draws on a diverse range of disciplines and has exciting futurist visions.
Computational linguistics is a general field that encompasses many aspects of psychology, linguistics, logic, and computer science. It is involved in helping computers understand linguistic issues to improve in the automation of translation, generation, speech and understanding aspects.
Computational linguistics was born after a series of failed attempts at machine translation. In the late 1940s, the US government saw the need for machine translation of texts, especially Russian texts. It was assumed, given the ease with which computers had been adapted to handle mathematical problems, that teaching them to translate language would be a simple affair. It soon became apparent that the problem was much more difficult, however, and the discipline of computational linguistics was created.
In the early days of computational linguistics, the field was dominated by computer scientists. Since the 1970s, however, it has become apparent how complex language actually is, and contemporary computational linguistics employs experts from different fields.
Machine translation has always been a major focus of computational linguistics and in which the field has made tremendous progress. The task is very complex and requires identification of the parts of speech, understanding of grammar, a large vocabulary and mechanisms for dealing with colloquialisms and slang. Machine translation is far from perfect, but every year the translations get more accurate and less forced.
Speech recognition is another area of computational linguistics that has seen a lot of public interest. After a few failed attempts at mainstream speech recognition software in the mid-1990s, the field fell silent for a while. In the early 21st century, however, a number of new speech recognition software suites have come onto the market that boast extensive learning systems and high accuracy rates. This has led to a renewed interest in speech recognition software from the general public and a consequent increase in funding and research.
Speech generation is a related field of computational linguistics that has seen steady development since the 1980s. Achieving a natural reading of written text is a very difficult problem, but one that offers huge potential benefits. For visually impaired users, speech generation software can be critical to enjoying the fruits of the digital age.
Computational linguistics also plays an important role in automated grammar proofing systems, such as those built into popular word processors. An accurate grammar checker requires a sophisticated ability to identify parts of speech and a comprehensive list of grammar rules and exceptions. While most of the traditional grammar checkers still have a lot of problems, they are already becoming indispensable for many in the new generation.
Computational linguistics is an exciting field that draws on a diverse range of disciplines. The problems he faces are many and none simple. The futurist visions that await, however, make it a worthwhile fight. From dreaming of a universal translator to perfect speech recognition, the goals of computational linguistics can’t help but inspire a sense of wonder.
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