A Blog: Perspectives in Computational Linguistics

https://www.linguisticsociety.org/content/computers-and-languages

For the past, twenty or so years software developers have been working on developing computers that can understand human language. Whether that involves scanning written words or understanding spoken language through a microphone. I thought that this was very interesting especially because the author presents numerous problems with the development of these programs that I had not considered before. 

The most prominent and important difficulties for their programs are ambiguities in language. For example the sentence "I saw a man in a park with the telescope" couple mean a number of things. In this phrase for example you cannot tell whether I, the man or the park have the telescope. This results in a conundrum that is impossible for a computer to solve on its own. Another example of this with bigger real-world consequences is the phrase "There's a pile of inflammable trash next to your car. You are going to have to get rid of it." could mean a number of things. In this phrase for example a computer cannot tell whether the car or the trash is what needs to be removed. For us humans, this is a relatively easy problem to solve because of our knowledge of the world and the context of the setting. But for a computer, this is near impossible without extra data. When it comes to these kinds of problems there are two tracks a programmer can take. He can either take a knowledge-based approach and try to encode the value of cars and trash. The issue with this approach is that it would take huge amounts of work and would be very inefficient. The other approach is a statistics-based approach. And how often certain pairs of words mean certain things more often than others. Both of these approaches would be incredibly difficult and involve huge amounts of work processing power and data. This makes the human brain that much more impressive and I found this article incredibly interesting.

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