Talking with Robots: Opportunities and Challenges

Commencing in the 1980s with the appearance of specialised isolated-word recognition (IWR) systems for military command-and-control equipment, spoken language technology has evolved from large-vocabulary continuous speech recognition (L VCSR) for dictating documents (such as Dragon's Naturally Speaking and IBM's Via V oice) released in the late 1990s, through telephone-based interactive voice response (IVR) systems to the launch of Siri (Apple's voice-enabled personal assistant for the iPhone) in 2011. Siri was quickly followed by Google Now and Microsoft's Cortana. The following years heralded a new era of smart speaker based voice assistants, starting with Amazon's 2015 release of Alexa followed later by Google Home, Apple's HomePod and Sonos One. These contemporary systems not only represent the successful culmination of over 50 years of laboratory-based speech technology research (Pieraccini, 2012), but also signify that speech technology had finally become "mainstream" (Huang, 2002) (at least, in the English-speaking world). Indeed, the market penetration of these smartphone and smart speaker based voice assistants is astounding. For example, Siri has had over 40 million monthly active users in the U.S. since July 2017, Google Assistant is available on over 225 home-control brands and more than 1,500 devices, and tens of millions of Alexa-enabled devices were sold worldwide over the 2017 Christmas holiday season (Boyd, 2018). Also, a study by Juniper Research (Smith, 2017) estimated that the number of voice assistant devices across all Figure 1: The evolution of spoken language processing applications from specialised military'command-and- control' systems of the 1980/90s to contemporary'voice-enabled personal assistants' (such as Siri and Alexa) and future'autonomous social agents', i.e. robots.