Advancements in Natural Language Processing for Chatbots

  • May 11, 2018

    Advancements in Natural Language Processing for Chatbots

    Despite continual advancements in AI, conversing with a chatbot still feels like communicating with a machine. They don’t fool us. This is partly due to a computer’s ability to respond to novel situations or recognize figures of speech. Chatbot language sounds well, like a robot!

    To successfully obtain an answer from a chatbot or virtual assistant, one must use deliberate, unambiguous diction. Some innovative companies are looking to change that.

    Making Inferences from Ambiguity

    A recent article published in the MIT Technology Review discusses how uncertainty can help a bot hold a more eloquent or natural conversation. The article features Gamalon, an AI startup, working on making computers respond more naturally to ambiguity. Standard chatbots typically follow rules for answering certain types of questions. They are often preprogrammed to serve a particular purpose. Gamalon programs chatbots to infer what a user might mean by a certain utterance. It gives the chatbot the power to make a judgement call through probabilistic techniques.

    A Chatbots Magazine article outlines the mechanics of natural language processing or NLP. The chatbot leverages AI to make inferences from diction, sentence structure and idioms to recognize the intent behind the user’s input.

    Do Bots Need to Sound Natural?

    Companies that develop chatbots that can process natural language will reap high returns. But do chatbots really need to sound natural? It all depends on what you aim to accomplish with your chatbot.

    In certain customer service environments, natural language processing may help customers who are unfamiliar with communicating with bots. It will also make the customer to feel as if they are really communicating with someone versus clumsily navigating software. NLP chatbots can also help sell more products. By processing inferences, a bot can present a customer with a product targeted for their needs versus presenting them with a menu with too many options.

    NLP is still nascent. Thus, investing in NLP now may not be worth the cost unless it aligns immediately with your key initiatives. As AI improves, so will NLP and the cost for implementing NLP chatbots will become more economical.