Do you sometimes wish your computer understood English? That you could just tell it something as if you were having a conversation with a friend and it would understand exactly what you mean? That is the goal of Natural Language Processing (NLP) research in the computer science field. At the nexus of artificial intelligence, machine learning, and computational linguistics, researchers are studying how to better the human-computer interaction.

Taking on a language as complex as English is definitely not easy. Almost every English speaker understands the struggle of speaking this language filled with numerous nuances in sentence structure and word spelling. Making English understandable to a computer so that it can interpret what we mean in context is incredibly hard and is only just now being explored. Companies such as Microsoft and Google have specialized research groups focused on various aspects of understanding NLP from “predict[ing] part-of-speech tags for each word in a given sentence,”1 to applications such as  “text critiquing, information retrieval, question answering, summarization, gaming, and translation.”2 Many research universities and other research institutions are delving into this interesting niche area.

One of the more fascinating things related to natural language processing is the website www.cleverbot.com. It is designed to “imitate the human sense of discussion in a sophisticated way.”3 By storing information from other users who interact with a chat box, Cleverbot comes up with an appropriate response to your questions or statements. If you are ever bored or are simply fascinated by this technology, I recommending heading to the website and seeing the accuracy in Cleverbot’s responses. It’s pretty good at answering questions, but you will probably not be able to hold a sustaining conversation since the cleverbot only responds to statements you’ve just made with no recollection of your ongoing conversation. However, being able to converse with humans is not the only possible application of NLP. John Rehling, an NLP expert at Meltwater Group, said in How Natural Language Processing Helps Uncover Social Media Sentiment, “[by] analyzing language for its meaning, NLP systems have long filled useful roles, such as correcting grammar, converting speech to text and automatically translating between languages.”4 Ultimately, there is great potential for this research to help people in a variety of fields, from  marketing to sociology, understand more about the human nature and our interaction with technology.

Resources:

  1. "Natural Language Processing." Natural Language Processing - Research at Google. Google, n.d. Web. 11 Nov. 2016. 
  2. "Natural Language Processing." Microsoft Research: Natural Language Processing. Microsoft, 27 June 2016. Web. 11 Nov. 2016.

  3. Lion, Matthieu. "Natural Language Processing." Alan-shapiro.com, 3 Sept. 2014. Web. 11 Nov. 2016.

  4. Kiser, Matt. "Introduction to Natural Language Processing (NLP) 2016 - Algorithmia." Algorithmia. N.p., 11 Aug. 2016. Web. 11 Nov. 2016. 

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