A large manual effort is required to collect dialogue flows and intent training data needed to design an effective dialogue system. We extract intents, flows, slots, and training data from existing customer service call transcriptions and chat logs (corpora). This session surveys the state of art, direction of research, and review product offerings from companies including Facebook, Google, Nuance, Microsoft, IBM, and Discourse.ai.

Customer service AI chatbots (bots) are being unleashed into the world without sufficient testing. This talk covers the new approaches to AI bot validation and how to prevent your customers from being customer experience guinea pigs. The most thorough way to test bots is with bots. Attendees learn how to use technology to create virtual customers, approaches to generate additional training and testing data, and how humans fit in the loop.

The MRS “Adam Team” describes how we built an AI-enhanced call center. From an initial idea using a Raspberry Pi to a virtual agent which has collected more than $2 million in payments during the last 18 months, Adam, a multi-cloud solution based on IBM Watson, has radically changed our company and has the potential to disrupt the call center industry. By partnering with IBM Watson, MRS has significantly grown and improved Adam.

We cover some of the top tips and pitfalls learned by bringing hundreds of AI voice applications to production at Google Cloud. While we use Google products as an example, the concepts in this session are universal to all AI-based voice applications. We focus on realworld, production-level product management, engineering, and operational issues and developing, deploying, and managing AI-based voice apps from project inception to maintenance in production.

Open to all full-conference attendees and Networking Pass holders. Check SpeechTEK.com for details or follow #SpeechTEK on Twitter.

This talk details how Discover Financial Services achieved its implementation goals for a conversational assistant for customer service. Discover’s requirements were as follows: Provide a low-effort customer experience with a conversational UI; reduce Average Handle Time (AHT); reduce transfer rate; increase IVR containment; and achieve a No. 1 customer satisfaction ranking with J.D. Power. This talk describes the Discover project implementation and explains how these goals were met.

Customers today expect personalization and are increasingly comfortable interacting with virtual assistants like Alexa and Siri. Customers prefer self-service to the often-frustrating experiences of navigating traditional IVR systems and/or repeating themselves to strained live agents who must search for needed information. We’re designing a solution to improve call center operations by creating a more user-friendly customer experience that increases self-service across platforms, expedites call resolution times, and derives customer insights through call analysis.

All commercial conversational platforms provide an NLU engine that can be trained based on sample sentences for each intent in the application, but they typically do not provide good guidelines on how to make sure that NLU engine produces the best possible accuracy. This results in a poor conversational user experience. This presentation describes techniques that have been successfully used to improve NLU accuracy and presents experimental results obtained with different NLU engines and task domains.

Planning to create a voice application and you need to support both Alexa and Google Actions? What are the similarities and differences in their stacks, security models, and hosting architecture? What are the most important technical considerations before designing a voice-first, cross-platform experience? Learn from Microsoft Alums and AWS Certified Skill Builders how to overcome the challenges in a multi-platform environment, from design to implementation. Take home tips and tricks you can use for your next project.

This talk highlights how the introduction of natural language not only benefits the bottom line, but dramatically improves the customer and employee experience. We discuss how a firm focused on worldclass, award-winning care can actually improve the experience while delivering deeper omnichannel analytics and innovative routing and treatment strategies with voice. This talk includes tips on how others can raise their utilization in a customer-friendly way and how we made the case to the C-suite.

Learn more about the latest technological developments in speech technology from leading-industry companies. These sessions are open to all full-conference attendees and Networking Pass holders. Check SpeechTEK.com for details or follow #SpeechTEK on Twitter.

An essential focus of Nu Echo is to develop advanced conversational IVR applications offering sophisticated mixed initiative dialogues with a natural and effective user experience. To meet these objectives, we have explored dialogue management capabilities offered by the Rasa solution and its integration with VoiceXML. During this presentation, we describe the rationale behind the Rasa-VoiceXML solution, the use cases that were explored, and how we leveraged both deterministic dialogue strategies and machine learning capabilities.