Blog: Learn Machine Learning from a Google AI Engineer
Building Your Own Conversational Voice AI With Dialogflow & Speech to Text in Web Apps. (Part I)
This is the first blog in the series:
A best practice for streaming audio from a browser microphone to Dialogflow & Google Cloud Speech To Text.
In this first blog, I will address why customers would integrate their own conversational AI compared to building for the Google Assistant. I will introduce all the conversational AI components in Google Cloud and where you would use each component for.
This is the first blog in the series:
A best practice for streaming audio from a browser microphone to Dialogflow & Google Cloud Speech To Text.
In this first blog, I will address why customers would integrate their own conversational AI compared to building for the Google Assistant. I will introduce all the conversational AI components in Google Cloud and where you would use each component for.
Lee Boonstra
Lee Boonstra (they/them) has been a presence in the tech world since 2007, wearing many hats from AI software engineer to prompt engineer, web developer to technical trainer, and developer advocate.
With eight years of experience at Google (and AI) under their belt, they now hold the role of AI Software Engineer (SWE) at the Google Cloud office of the CTO. Leading innovation projects, Lee aims to disrupt markets and foster collaboration globally. Their expertise in Conversational and Voice technology, alongside (Generative) AI, has led to recognition as a respected public keynote speaker and published author for O’Reilly and Apress. Lee eases tech headaches and celebrates those light bulb moments.
Lee has written the Google/Kaggle Prompt Engineering whitepaper and two books: "Hands-on Sencha Touch 2" (O'Reilly) and their more recent work, "The Definitive Guide to Conversational AI with Dialogflow and Google Cloud" (Apress).
