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               <th>[[Tendances_Technologiques|Tendances Technologiques]]</th>
 
               <th>[[Tendances_Technologiques|Tendances Technologiques]]</th>
 
               <th> / </th>
 
               <th> / </th>
               <th>[[Tendances_Technologiques/Assistants_Numeriques|Assistants Numériques]]</th>
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               <th>Assistants Numériques<!--[[Tendances_Technologiques/Plateforme_de_Gestion_Infonuagique|Plateforme de Gestion Infonuagique]]--></th>
 
             </tr>
 
             </tr>
 
           </table>
 
           </table>
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       <tr>
 
         <th>Status</th>
 
         <th>Status</th>
         <td>Published</td>
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         <td>Translation</td>
 
       </tr>
 
       </tr>
 
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       <tr>
 
         <th>Latest version</th>
 
         <th>Latest version</th>
         <td>February 5, 2020</td>
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         <td>February 14, 2020</td>
 
       </tr>
 
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   <p class="inline">Digital assistants are a software agent that performs various tasks and services for its user. DAs, such as Samsung’s Bixby<ref>Agence France-Presse. (2017, April 6). <i>[https://www.scmp.com/lifestyle/article/2085067/samsungs-new-personal-digital-assistant-bixby-faces-few-tough-challenges Samsung's new personal digital assistant Bixby faces a few tough challenges]</i>. Retrieved from scmp.com</ref>, use voice commands to control applications and handle these requests. This recent development of virtual assistants makes it relatively easy for end users to master the software usage. Digital Assistants also have skills, which are apps that can be acquired through a skill store. This allows users to install the skills that would be most useful to them.</p><p class="inline expand mw-collapsible-content"> These skills include things like a weather skill, a podcast skill, and a workout skill. Some of these skills are free and some cost money. Some are built by vendors, some are built by the community, and it’s possible for you to build your own skills.</p>
 
   <p class="inline">Digital assistants are a software agent that performs various tasks and services for its user. DAs, such as Samsung’s Bixby<ref>Agence France-Presse. (2017, April 6). <i>[https://www.scmp.com/lifestyle/article/2085067/samsungs-new-personal-digital-assistant-bixby-faces-few-tough-challenges Samsung's new personal digital assistant Bixby faces a few tough challenges]</i>. Retrieved from scmp.com</ref>, use voice commands to control applications and handle these requests. This recent development of virtual assistants makes it relatively easy for end users to master the software usage. Digital Assistants also have skills, which are apps that can be acquired through a skill store. This allows users to install the skills that would be most useful to them.</p><p class="inline expand mw-collapsible-content"> These skills include things like a weather skill, a podcast skill, and a workout skill. Some of these skills are free and some cost money. Some are built by vendors, some are built by the community, and it’s possible for you to build your own skills.</p>
 
    
 
    
   <p class="expand mw-collapsible-content">However, questions must still be clearly formatted for the DA to understand it. The device’s built in microphone parses a user’s voice to be registered using natural language processing (NLP). The requests made by users are stored in data centres, which aid in the service delivery to the software’s users. Based on a user’s request history, digital assistants are now using pre-existing information to deliver services to users with higher accuracy. For example, “several times a day, Amazon uses the entire stack of Alexa queries to educate its A.I. about dialects and casual speech.<ref>Moynihan, T. (2016, December 5). Alexa and Google Home Record What You Say. But What Happens to That Data? Retrieved from wired.com: https://www.wired.com/2016/12/alexa-and-google-record-your-voice/</ref></p>
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   <p class="expand mw-collapsible-content">However, questions must still be clearly formatted for the DA to understand it. The device’s built in microphone parses a user’s voice to be registered using natural language processing (NLP). The requests made by users are stored in data centres, which aid in the service delivery to the software’s users. Based on a user’s request history, digital assistants are now using pre-existing information to deliver services to users with higher accuracy. For example, “several times a day, Amazon uses the entire stack of Alexa queries to educate its A.I. about dialects and casual speech”.<ref>Moynihan, T. (2016, December 5). Alexa and Google Home Record What You Say. But What Happens to That Data? Retrieved from wired.com: https://www.wired.com/2016/12/alexa-and-google-record-your-voice/</ref></p>
 
    
 
    
 
   <p>Generally, voice activated digital assistants are constantly operating at a low processing rate until a key word is heard to notify the DA that a request is about to be made. For example, Google Home listens to its surroundings until the words “Ok Google” are said aloud. Digital assistants then translate a user’s proceeding commands into text that is analyzed by multiple algorithms to execute a task. These algorithms break up the requests into key parts, which make it easy to send emails, messages, or store records.</p>
 
   <p>Generally, voice activated digital assistants are constantly operating at a low processing rate until a key word is heard to notify the DA that a request is about to be made. For example, Google Home listens to its surroundings until the words “Ok Google” are said aloud. Digital assistants then translate a user’s proceeding commands into text that is analyzed by multiple algorithms to execute a task. These algorithms break up the requests into key parts, which make it easy to send emails, messages, or store records.</p>
 
    
 
    
   <p class="expand mw-collapsible-content"></p>There are three main types of algorithms that are used to analyze your request: Natural Language Processing (NLP)<ref>Wikipedia. (2019, September 15). Natural language processing. Retrieved from en.wikipedia.org: https://en.wikipedia.org/wiki/Natural_language_processing</ref>, Natural Language Understanding<ref>Wikipedia. (2019, August 24). Natural-language understanding. Retrieved from en.wikipedia.org: https://en.wikipedia.org/wiki/Natural-language_understanding</ref>, and Natural Language Generation (NLG)<ref>Wikipedia. (2019, September 6). Natural-language generation. Retrieved from en.wikipedia.org: https://en.wikipedia.org/wiki/Natural-language_generation</ref>. NLP deals with how to write computer programs to collect and process large amounts of natural language data. This can be a difficult task when some languages like Japanese and Chinese use characters that represent words and letters with no spaces between which makes it harder for the computer to understand what’s being said. It is easier in languages like English to identify words since they are almost always separated by a space. Another challenge is when the same word can be used as a different part of the sentence (noun, verb, etc). For example, you can turn on a light (noun), something can be light (adjective) (not heavy), you can light a candle (verb).</p>
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   <p class="expand mw-collapsible-content"></p>There are three main types of algorithms that are used to analyze your request: Natural Language Processing (NLP)<ref>Wikipedia. (2019, September 15). Natural language processing. Retrieved from en.wikipedia.org: https://en.wikipedia.org/wiki/Natural_language_processing</ref>, Natural Language Understanding<ref>Wikipedia. (2019, August 24). Natural-language understanding. Retrieved from en.wikipedia.org: https://en.wikipedia.org/wiki/Natural-language_understanding</ref>, and Natural Language Generation (NLG).<ref>Wikipedia. (2019, September 6). Natural-language generation. Retrieved from en.wikipedia.org: https://en.wikipedia.org/wiki/Natural-language_generation</ref> NLP deals with how to write computer programs to collect and process large amounts of natural language data. This can be a difficult task when some languages like Japanese and Chinese use characters that represent words and letters with no spaces between which makes it harder for the computer to understand what’s being said. It is easier in languages like English to identify words since they are almost always separated by a space. Another challenge is when the same word can be used as a different part of the sentence (noun, verb, etc). For example, you can turn on a light (noun), something can be light (adjective) (not heavy), you can light a candle (verb).</p>
 
    
 
    
 
   <p class="expand mw-collapsible-content">Natural Language Understanding (NLU)<ref>Rouse, M. (2019, September 20). natural language understanding (NLU). Retrieved from searchenterpriseai.techtarget.com: https://searchenterpriseai.techtarget.com/definition/natural-language-understanding-NLU</ref> refers to understanding input to a computer in the form of spoken words or text. It enables computers to understand human speech without using a pre-programmed syntax and allows computers to respond to the commands or questions in an intelligent and coherent manner. NLU is what’s behind chat bots that interact with humans without intervention.</p>
 
   <p class="expand mw-collapsible-content">Natural Language Understanding (NLU)<ref>Rouse, M. (2019, September 20). natural language understanding (NLU). Retrieved from searchenterpriseai.techtarget.com: https://searchenterpriseai.techtarget.com/definition/natural-language-understanding-NLU</ref> refers to understanding input to a computer in the form of spoken words or text. It enables computers to understand human speech without using a pre-programmed syntax and allows computers to respond to the commands or questions in an intelligent and coherent manner. NLU is what’s behind chat bots that interact with humans without intervention.</p>
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