Conversational user interface: Difference between revisions

Revision as of 13:53, 24 August 2019

Revision as of 14:06, 24 August 2019

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==Voice Assistants==

[[Voice assistant]]s are interfaces that allow a user to complete an action simply by speaking a command. Introduced in October 2011, Apple’s [[Siri]] was one of the first voice assistants widely adopted. Siri allowed users of iPhone to get information and complete actions on their device simply by asking Siri.

Further development has continued since Siri’s introduction to include home based devices such as [[Google_Home|Google Home]] or [[Amazon_Echo|Amazon Echo]] (powered by Alexa) that allow users to “connect” their homes through a series of smart devices to further the options of tangible actions they can complete. Users can now turn off the lights, set reminders and call their friends all with a verbal queue.

These conversational interfaces that utilize a voice assistant have become an efficient and popular way for businesses to interact with their customers as the interface removes the typical friction in a customer journey. Customers no longer need to remember a long list of usernames and passwords to their various accounts; they simply link each account to Google or Amazon once, and gone are the days where you needed to wait on hold for an hour to ask a simple question.

==Chatbots==

[[Chatbot]]s are web or mobile based interfaces that allow the user to ask questions and retrieve information. This information can be generic in nature such as the Google Assistant chat window that allows for internet searches, or it can be a specific brand or service which allows the user to gain information about the status of their various accounts. Their backend systems work in the same manner as a voice assistant, with the front end utilizing a visual interface to convey information. This visual interface can be beneficial for companies that need to do more complex business transactions with customers, as instructions, deep links and graphics can all be utilized to convey an answer. The complexity to which a chatbot answers questions depends on the development of the back end. Chatbots with hard-coded answers has a smaller base on information and corresponding skills. Chatbots that leverage machine learning will continue to grow and develop larger content bases for more complex responses <ref>{{cite web | author=Onlim | title=How do Chatbots Work? – Chatbots Life | website=Chatbots Life | date=2017-03-22 | url=https://chatbotslife.com/how-do-chatbots-work-fe49ef32598f | ref=harv | access-date=2018-05-23}}</ref>.

More frequently, companies are leveraging chatbots as a way to offload simple questions and transactions from human agents. These chatbots provide the option to assist a user, but then directly transfer the customer to a live agent within the same chat window if the conversation becomes too complex.

== See also ==

* [[chatbot]]

* [[natural language processing]]

* [[natural language understanding]]

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== References ==

{{Fixed Typoreflist}}

[[Category:Human–computer interaction]]

[[Category:Natural language processing]]