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AI-driven speech technology applications are seen primarily in contact centers, but this is not the only use case for the technology. The most interesting use cases of speech technology are forms of person-to-machine communication. Plenty of speech technology applications for conventional use cases exist -- namely person to person -- but the innovation these days focuses mostly on person-to-machine communication.
Speech applications are still in their infancy when it comes to machines engaging with both people and other machines. This is mainly because speech recognition technology has only recently evolved to the point where AI-driven speech is reaching the same complexity as human speech. The utility of speech technology increases as parity gets closer, which will allow for applications to reach beyond the contact center.
The next frontier is workplace applications, and a lot of offerings will start to emerge in 2019. A key reason is the use of machine learning, where speech applications are trained by each worker to recognize individual patterns and preferences. As the quality of these interactions improves, workers will build trust that opens up possibilities for automating tasks and managing workflows. At a high level, enterprise speech technology applications have two distinct use cases outside the contact center:
- Personal digital assistants. If Amazon's Alexa has found a helpful spot in your home, it won't be long until it finds a similar place at work. Alexa for Business is here now, and it's part of the first wave of desktop appliances that can provide workers with a simple personal digital assistant. For now, it's a voice-only interface. But video is coming, and it won't take long before you just need speech commands to update your calendar, schedule meetings, edit documents, dictate email messages and initiate conference calls.
- Knowledge management. With so many communication channels available and so many sources of information to work with, most workers are overwhelmed and struggle to stay productive while managing multiple information sources.
AI-driven speech technology has become conversational, to the point where workers can instruct chatbots to extract key forms of information from a mass of sources, such as email messages, voicemails, project files or even content culled from the web.
Initial use cases may still be basic, but the technology has great potential for making the everyday barrage of information more manageable, freeing up workers to be more productive.
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