plications. For example, natural language systems recognize "Turn on the Alarm" as well as "Set the alarm." Digital Assistant products such as Amazon's Alexa are capable of recognizing natural language commands. These systems are speaker independent systems. High-speed computer processors perform the digitization and comparisons in milliseconds. They also take into account gender differences and regional accents. Speech recognition software contains different databases of expected responses based on the application. A corporate directory has a different speech database than one for airline scheduling or lost-luggage applications. Until recently, Nuance had somewhat of a monopoly on speech recognition software. But, currently machine learning and computer chips with larger memories and faster transistors have led research universities and large companies including Microsoft and IBM to develop speech recognition, particularly for wearable devices such as Hoboken, NJ-based Essence Group's emergency alert devices that enable an incapacitated elderly person to call for help by voice commands without using his or her hands. Speech recognition is integrated in: www.TechnicalPDF.com Home digital assistants Amazon's Echo and Dot Alphabet's Google Home Microsoft's Cortana, Apple's Siri Baidu's Raven . Samsung's ViV Set-top boxes . Apple TV . Roku . Comcast X1 Speech Recognition in Home Automation Devices A digital assistant is essentially a computerized home assistant that supplies information in response to spoken questions and requests for information asked by users. Digital assistants are made possible by natural language speech recognition, high-speed computer networks, and machine learning. (See Chapter 1 for "Machine Learning.") The large amounts of captured speech and information gathered on search engines and computers are key to the development of digital assistants. For example, Google has troves of data with commonly requested search requests. In addition, as digital assistants' databases of known utterances gro