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Natural-language makes more sense in a mobile environment than in a desktop environment because the users of mobile devices are on the go and

  

Natural-language makes more sense in a mobile environment than in a desktop environment because the users of mobile devices are on the go and want to use their hands as little as possible. NLP adds a user friendly environment and enhances data entry and data input for mobile users. And the increased memory and speed of mobile devices (as well as the increased speed of mobile and wireless networks) make them good candidates for NLP. As a result, voice-acti- vated functions, speech-to-text dictation, and voice-activated dialing are now available for most smartphones, and voice- driven apps are getting smarter. For example, instead of say- ing "Call 551-535-1922" to dial a phone number, users can now say "Dial Dad" or "Phone my father." Nuance's Dragon Dictation, available as an iPhone app. allowsuserstodictateeverythingfrommemosande-mailsto Twitter updates; Dragon for E-mail offers similar capabilities for the BlackBerry. Also for the iPhone, Jibbigo (http://apple vshare.com/528691646.html) translates words, phrases, and simple sentences. Voice-driven apps such as Google Voice Search, Bing Voice Search, and Microsoft Tellme are among the more popular smartphone applications. Vlingo (www.vlingo.com), a multiplatform app, serves as a "virtual processing assistant" and is being used for such services as mak ing restaurant reservations (Opentable, www.opentable. com/) and booking movie tickets (Fandango, www.fan- dango.com). Apple's Siri, available on IPhone 45 and beyond, and Google Assistant, available on Google's Pixel and other Android phones, are other entrants in the fast-growing voice-activated mobile-device market. One of the chal- lenges with voice-activated mobile devices is to get the device to understand what you mean, not just what you say. Other challenges include the use of foreign names, accents, and maintaining accuracy in noisy environments.4 Answer the following questions: 1. How can NLP make a smartphone smarter? 2. What are some examples of voice-based software used by iPhone? 3. What are some of the challenges to be overcome before achieving a full-featured voice-activated mobile device? 4. Compare and contrast Apple's Siri and Pixel's Google Assistant. Which one do you prefer and why?

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