The Definitive Guide to Conversational AI with Dialogflow and Google Cloud: Build Advanced Enterpris
Lee Boonstra
Résumé
Build enterprise chatbots for web, social media, voice assistants, IoT, and telephony contact centers with Google's Dialogflow conversational AI technology. This book will explain how to get started with conversational AI using Google and how enterprise users can use Dialogflow as part of Google Cloud. It will cover the core concepts such as Dialogflow essentials, deploying chatbots on web and social media channels, and building voice agents including advanced tips and tricks such as intents, entities, and working with context.
The Definitive Guide to Conversational AI with Dialogflow and Google Cloud also explains how to build multilingual chatbots, orchestrate sub chatbots into a bigger conversational platform, use virtual agent analytics with popular tools, such as BigQuery or Chatbase, and build voice bots. It concludes with coverage of more advanced use cases, such as building fulfillment functionality, building your own integrations, securing your chatbots, and building your own voice platform with the Dialogflow SDK and other Google Cloud machine learning APIs.
After reading this book, you will understand how to build cross-channel enterprise bots with popular Google tools such as Dialogflow, Google Cloud AI, Cloud Run, Cloud Functions, and Chatbase.
What You Will Learn
- Discover Dialogflow, Dialogflow Essentials, Dialogflow CX, and how machine learning is used
- Create Dialogflow projects for individuals and enterprise usage
- Work with Dialogflow essential concepts such as intents, entities, custom entities, system entities, composites, and how to track context
- Build bots quickly using prebuilt agents, small talk modules, and FAQ knowledge bases
- Use Dialogflow for an out-of-the-box agent review
- Deploy text conversational UIs for web and social media channels
- Build voice agents for voice assistants, phone gateways, and contact centers
- Create multilingual chatbots
- Orchestrate many sub-chatbots to build a bigger conversational platform
- Use chatbot analytics and test the quality of your Dialogflow agent
- See the new Dialogflow CX concepts, how Dialogflow CX fits in, and what's different in Dialogflow CX
Who This Book Is For
Everyone interested in building chatbots for web, social media, voice assistants, or contact centers using Google's conversational AI/cloud technology.
Why do some chatbots fail?
Machine learning simply explained
Chatbots and machine learning
Machine learning and Google
About Dialogflow
Dialogflow essentials & Dialogflow CX
About Google Cloud
About Contact Center AI
Other Google conversational AI products
Actions on Google / Action Builder
AdLingo
Chatbase
Duplex
Meena
Summary
Reference
Chapter 2: Getting Started with Dialogflow Essentials
Creating a Dialogflow agent
Creating Dialogflow agents for enterprises
Configuring your Dialogflow project
Summary
Reference
Chapter 3: Dialogflow Essentials Concepts
Setting up intents
Creating custom entities
Creating intents with entities in training phrases
Keeping context
Testing in the simulator
Summary
Reference
Chapter 4: Building Chatbots with Templates
Creating prebuilt agents
Enabling small talk modules
Creating a FAQ knowledge base
Summary
Reference
Chapter 5: Reviewing your Agent
Validating your Dialogflow agent
Summary
Reference
Chapter 6: Deploying your Chatbot to Web & Social Media Channels
Integrating your agent with Google Chat
Integrating your agent with a web demo
Integrating your agent with a Dialogflow Messenger
Summary
Reference
Chapter 7: Building Voice Agents
Building a voice AI for a virtual assistant like the Google Assistant
Building a callbot with a phone gateway
Building bots for contact centers with Contact Center AI
Improving speech quality
Fine tuning voice bots with SSML
Summary
Reference
Chapter 8: Creating a Multilingual Chatbot
Building multilingual chatbots
Summary
Reference
Chapter 9: Orchestrate Multiple Sub Chatbots from One Chat Interface
Creating a mega agent
Summary
Reference
Chapter 10: Creating Fulfillment Webhooks
Building a fulfillment with the built-in editor
Building webhook fulfillments
Building multilingual webhook fulfillments
Using local webhooks
Securing webhooks
Summary
Reference
Chapter 11: Creating a Custom Integration with the Dialogflow SDK
Implementing a custom chatbot in your website front-end
Creating rich responses in your chatbot integration
Using markdown syntax & conditional templates in in your Dialogflow responses
Summary
Reference
Chapter 12: Implementing a Dialogflow Voice Agent in your Website or App Using the SDK
Building a client-side web application which streams audio from a browser microphone to a server
Building a web server which receives a browser microphone stream to detect intents
Retrieving audio results from Dialogflow and play it in your browser
Summary
Reference
Chapter 13: Collecting & Monitoring Advanced Agent Insights
Capturing conversation related metrics to store in BigQuery
Session Id
Date / time stamp
Sentiment score
Language & keyword
Platform
Intent detection
Building a platform for capturing conversation related metrics and redact sensitive information
Detecting user sentiment
Monitoring chat session & funnel metrics with Dialogflow , Chatbase or Actions on Google
Total Usage
The number of requests the intent was matched to and the percentage of all users that matched the intent.
Completion Rate & Drop off Rate / Drop off Place
User retention
Endpoint health
Discovery
Dialogflow Built-in Analytics
Monitoring metrics with Chatbase
Analytics on Actions on Google
Capturing chatbot model health metrics for testing the underlying NLU model quality
True positive - A correctly matched intent
False positive - A misunderstood request
True negative - An unsupported request
False negative - A missed request
Accuracy
Precision
Recall & fallout
F1 score
Confusion matrix
ROC curve
Improve the Dialogflow NLU model with built-in training
Summary
Reference
Lee Boonstra is a senior developer advocate at Google working with conversational AI. In this role she focuses on Dialogflow, Contact Center AI and speech technology. Lee is based in Amsterdam, the Netherlands, where she has been working with different technologies over the past 15 years, ranging from web/mobile, Ext JS, Sencha Touch, and Node.js, to conversational AI, Dialogflow, Actions on Google and Contact Centers.
Over the years she has helped many brands and enterprises to build and deploy conversational AI solutions (chatbots and voice assistants) at enterprise scale. She's worn different hats from engineer to technical trainer to sales engineer to developer advocate. Prior to Google, Lee worked at Sencha Inc.
You can find Lee on online via the Twitter handle: @ladysign.
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Apress |
| Auteur(s) | Lee Boonstra |
| Parution | 07/07/2021 |
| Nb. de pages | 408 |
| EAN13 | 9781484270134 |
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