WITHDRAWN Dive Inside a Digital Assistant Brain

Music City Center 

In this talk, the speaker will introduce the topic of language model in conversational digital assistant. I will dive in the language model and present the data science lifecycle pertaining to the virtual assistant chat-bot starting from designing the skills, populating the utterances through the entire process of building, training and testing the model on endpoints. I will introduce the audience to virtual assistant terminology that includes an utterance, skill, intent, entity, synonyms, features (or phrase lists) and patterns and how they enhance the accuracy of the chatbot. The language model provides a single service for intent recognition, routing and entity extraction. I will go over concepts such as staging, development and production for live usage. The pigeonhole classification model follows a train-test-publish process. Topics such as active learning, real-user and synthetic utterance sets will be discussed to improve the performance of the language model. In addition, continuous monitoring in production and maintenance phases complete the loop of the life cycle. Finally, I will briefly discuss applications of virtual assistants in patient safety and healthcare.

natural language processing

digital (virtual) assistant

language model

utterance

intent recognition and entity extraction

classification 

Section on Statistical Learning and Data Science