Amazon on Monday announced the general availability of Alexa Conversations, a deep learning-based dialog manager for the Alexa Skills Kit. The tool, first introduced in preview in 2019, helps developers create more natural conversations with customers.
"Natural language is actually a very difficult thing to emulate," Nedim Fresko, Amazon's VP of Alexa Devices and Developer Technologies, told ZDNet last year. "When people speak naturally, they change direction, they make contextual references to things they said. Sometimes they over-supply information, sometimes they under-supply it -- when that happens, consumers revert to robotic language and simple phrases, and developers just give up."
To use Alexa Conversations, developers give Amazon a few sample phrases of their conversations as well as some APIs that implement the services they're trying to achieve. From those samples, Amazon's AI system tries to anticipate all the possible conversation paths the user might take. It reduces the amount of back end code developers have to create and the amount of training data they have to provide.
Since its introduction and move into beta, thousands of developers have tried Alexa Conversations, including large brands like iRobot, professional Alexa skill builders and hobbyists.
Based on beta feedback, Alexa Conversations now has improved error messages, as well as dialog cloning, new command line interface support and enhanced authoring workflows.
Meanwhile, there are two new Alexa Skills Kit (ASK) features in beta that support Alexa Conversations.
The new Alexa Conversations Description Language (ACDL) allows experienced developers to author Alexa Conversations dialogs in a declarative manner. Second, the new Alexa Entities (beta) feature lets you resolve strings in a customer's utterance to popular entities from Alexa's Knowledge Graph (including people, places and things), using those entities as an entry point to traverse Alexa's structured knowledge.