Document ID: CGR-VAB19 | Last Updated: August 31, 2019
Voice assistants are voice-based conversational interfaces paired with intelligent cloud-based back-ends. The device itself provides basic Natural Language Processing (NLP) and Natural Language Generation (NLG) capabilities, and the back-end intelligence gives these devices AI-powered intelligence. Examples of voice assistants include Amazon Alexa, Apple Siri, Google Home, and Microsoft Cortana.
Cognilytica is focused on the application of AI to the practical needs of businesses, and because we believe voice assistants can be useful to those businesses. As such, we need to understand the current state of the voice assistant market. We care about what happens when the NLP does its processing and those outputs are provided as input to an intelligent back-end system. Some vendors are demoing their devices being used to make real-world calls to real-world businesses to perform real-world tasks. This is not just playing music or telling you the weather. This requires at least a minimum level of intelligence to perform without frustrating the user. And so, without an understanding of what the limitations of these devices intelligence really are, we’re left wondering what sort of applications these voice assistants are best suited for.
In this report, Cognilytica evaluates the intelligence and knowledge graph capabilities of four voice assistants: Amazon Alexa, Google Assistant (Home), Apple Siri, and Microsoft Cortana. We want to know — just how intelligent is the AI back-end?
See more details including video highlights in the Key Findings tab below.