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Home > Practical AI > Real-time conversational insights from phone call data


	Podcast:		Practical AI
	Episode:		Real-time conversational insights from phone call data
	Category:		Technology
	Duration:		00:51:46
	Publish Date:		2020-02-17 11:00:00
	Description:		Daniel and Chris hang out with Mike McCourt from Invoca to learn about the natural language processing model architectures underlying Signal AI. Mike shares how they process conversational data, the challenges they have to overcome, and the types of insights that can be harvested. Discuss on Changelog News Sponsors Linode – Our cloud of choice and the home of Changelog.com. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code `changelog2019` OR `changelog2020`. To learn more and get started head to linode.com/changelog. Brain Science – For the curious! Brain Science is our new podcast exploring the inner-workings of the human brain to understand behavior change, habit formation, mental health, and being human. It’s Brain Science applied — not just how does the brain work, but how do we apply what we know about the brain to transform our lives. Featuring Mike McCourt – GitHub, LinkedIn Chris Benson – Twitter, GitHub, LinkedIn, Website Daniel Whitenack – Twitter, GitHub, Website Notes and Links Mike McCourt \| Invoca Employee Spotlight Invoca Signal AI Zipf’s law Meet the Data Scientists Behind Invoca’s Conversational Analytics Algorithms -Invoca raises $56 million to apply AI and analytics to voice calls -Invoca’s Signal Discovery uses machine learning to conduct conversational analysis on inbound calls -Invoca - What Will You Discover?
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