In the Heart of Silicon Valley
SAVE THE DATE - Feb 5-6, 2018
CONFERENCE TOPICS
Sessions from the previous conference suggest just
some of the topics we’ll cover in 2018!
Digital assistants and bots: A range of options
What are the options in interacting with digital systems with human ("natural") language? How does one judge the tradeoffs, channels, and platforms?
Customer service: Automation with natural language
Customers are frustrated with IVR menus and chat bots that make the service experience difficult for them.
Building bots and digital assistants for the messaging services and home devices
Interaction with "things" is increasingly through natural language, including internet-connected devices in the home.
Digital assistants in customer service
Company-specific digital assistants can interact on mobile devices or web sites by voice or text to make it easier for a customer to use self-service.
Options in user interface design
Natural language interaction doesn't stand alone. It can be supported by GUIs and other options. And connecting with "things" creates a challenge.
The voice and personality of your application
The quality, naturalness, and "personality" of speech from an automated system can be a major determinant of its effectiveness.
Bot strategies in customer service
Chatbots are an efficient way to deal with customers, but one can create bots that either make a customer interaction simpler and save agent costs, or bots that too often drive a customer to an agent.
Customer service with natural language
Customer service should engage customers and help them meet their objectives. Natural language interaction by voice or text can be effective if done properly.
Digital Assistants in the Enterprise
Digital assistants can make employees more efficient, making the use of enterprise software and operations easier and thus fully utilized.
Major trends in conversational applications
There are many options in conversational systems. What are the major trends and options available?
Natural language tools
Discussions of machine learning sometimes imply that large amounts of labelled data are required to create advanced natural language interfaces. But a number of vendors offer solutions that require fewer examples.
Options you should know about
Options that can be critical to the success of an application.
Case studies: Conversational apps
Examples often make clear the advantages of a conversational system. This session contains such examples of deployed systems and their results.
Fitting the context of the natural language interaction
Voice options are almost a requirement in automobiles for safety reasons. And handling multiple languages may be a requirement in general.
Alternatives in natural language processing
Options in natural language processing range from those that require "big data" with machine learning to those that work with "small data" and extrapolate
from limited examples.
Building "bots" for messaging applications
Messaging applications are supporting connections to outside companies. How do you make bots for these services that satisfy users?
Building natural language applications
Natural language in human use involves a range of subtleties beyond simple understanding. That can be the case when interacting using automated processing if the technology supports it.
Putting it all together
A full natural language solution often requires integration that includes multiple services and works across multiple channels.
Creating effective Conversational User Interfaces
"Conversational" interfaces raise expectations. We must be careful in meeting those expectations.
Practical considerations in building conversational systems
Goals can vary for a conversational system. Choosing them appropriately can help direct your development and choice of platforms.
Automating a conversation: Approaches to a full dialog
A true "conversation" involves continued interaction, rather than a simple request and response. Maintaining context is key. What technology is necessary to support a dialog?
Your assistant in the home
Devices such as the Amazon Echo can provide general information and music services by voice interaction at a distance, but also control connected devices in the home. What is available today, and how will home assistants evolve?
Analytics: Understanding and categorizing user behavior
Understanding what customers ask is key to effective automation. Speech analytics can help understand what answers customers want and what frustrates them.
Making text entry on mobile devices more efficient
One aspect of natural language processing technology is that it can make typing text on a mobile device more efficient.
Building conversational systems
Speech recognition is a front end for conversational systems that interact by voice. This session describes alternatives for voice processing.
Interactive advertising and conversations with customers
Truly engage a prospect with an interactive natural language application, potentially an "ad" that can go on forever.
Plus Keynote talks and panels with people you will want to hear!