Enterprises that are building Knowledge Graphs are rapidly getting a grip on unstructured data with current advances in Natural Language Processing (NLP) techniques. But there is still a large mass of unstructured data that is untapped and that is spoken conversations with customers. Speech to text for general-purpose conversations (e.g. Google, Alexa, Siri) have proven themselves in the market to be highly accurate. However, speech recognition technology for domain-specific industries with lots of product names, industry lingo, and acronyms often creates a challenge for accuracy and usefulness of the content. In this presentation, we will demonstrate how taxonomy-driven speech recognition helps solve these industry-specific terminology challenges for real-time voice capture and how this process augments an Enterprise Knowledge Graph for customer insights enabling real-time decision support.