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Building Robots with TJBot Cognitive Class Exam Quiz Answers

Building Robots with TJBot Cognitive Class Certification Answers

Question 1: What does the see method return? Select all that apply.

  • Names of objects
  • Names of colors
  • Names of people
  • An image taken with the camera

Question 2: Which of these statements are true about TJBot? Select all that apply.

  • TJBot is a product sold by IBM.
  • TJBot is an open-source project.
  • TJBot is powered by artificial intelligence.
  • TJBot has a community of contributors who contribute recipes.

Question 3: What programming languages are supported by the TJBot libraries mentioned in this course? Select all that apply.

  • Node.js
  • Node-RED
  • Swift
  • Python

Question 4: Which one of these Watson services does not have a corresponding method in the TJBot library.

  • Speech to Text
  • Language Translator
  • Discovery
  • Text to Speech
  • Visual Recognition
  • Watson Assistant
  • Tone Analyzer

Question 5: Which method can be passed a duration value to specify how long the LED light should stay on?

  • shine
  • blink
  • pulse
  • turnOn

Question 1: In which order do these methods described in the course make the most logical sense?

  • isTranslatable, identifyLanguage, translate
  • translate, identifyLanguage, isTranslatable
  • identifyLanguage, isTranslatable, translate
  • isTranslatable, translate, identifyLanguage

Question 2: var TJBot = require(“tjbot”);

var tj = new TJBot( 

  [“camera”], 

  {}, 

  {

     visual_recognition: {

       apikey: “”   

     }

  });

tj.see(function(response) { 

  console.log(response);

});

  • Names of people
  • An array of objects containing names of objects and colors seen by the TJBot camera
  • An image captured by TJBot
  • Faces of people

Question 3: Which number points in the following Node.js code (#1, #2, #3, #4) should be corrected so that TJBot can say “Hello World” in English? Select all that apply.

var TJBot = require(“tjbot”);

var tj = new TJBot( 

  [“microphone”],  // #1

  {

    robot: {

      gender: “female” // #2

    },

    speak: {

      language: “fr-FR” // #3

    }

  },

  {

    text_to_speech: { // #4

      username: “cf63b1f3-ef18-4628-86c8-6b1871e076b9”,        

      password: “MWNwz3qcdIab”

    }

  });

tj.speak(“Hello World”);

  • #1
  • #2
  • #3
  • #4

Question 4: Review the following Node.js code. Which number points (#1, #2, #3, #4) in the following code should be corrected to make TJBot take a picture and speak out what is seen? Select all that apply.

var TJBot = require(“tjbot”);

var tj = new TJBot( 

  [“speaker”],  // #1

  {

    robot: {

      gender: “female” // #2

    },

    speak: {

      language: “en-US” // #3

    }

  },

  { // #4

    text_to_speech: {

      username: “cf63b1f3-ef18-4628-86c8-6b1871e076b9”,        

      password: “MWNwz3qcdIab”

    }

  });

tj.see(function(response) {

  tj.speak(“I see “+response.map(i => i.class).join(“, “));

}); 

  • #1
  • #2
  • #3
  • #4

Question 5: Which of the following blocks will speak out the phrase “Hello World” followed by pulsing the LED light the color green?

CODE BLOCK 1:

tj.speak(“hello world”).then(function() {

  tj.pulse(“green”, 1);

});

CODE BLOCK 2:

tj.speak(“hello world”);

tj.pulse(“green”, 1);

CODE BLOCK 3:

tj.speak(“hello world”).then(function() {

tj.pulse(1, “green”);

});

CODE BLOCK 4:

tj.pulse(“green”, 1);

tj.speak(“hello world”);

  • CODE BLOCK 1
  • CODE BLOCK 2
  • CODE BLOCK 3
  • CODE BLOCK 4

Question 1: What is the best way to determine whether a model is available in the Watson Language Translator service?

  • Use the translate method
  • Use the isTranslatable method
  • Check the Watson Language Translator documentation

Question 2: The TJBot capabilities can be extended both physically and in code by using third-party libraries or by writing custom code.

  • True
  • False

Question 3: The converse method can be used to do which tasks? Select all that apply.

  • Parse and process natural language
  • Have TJBot respond by voice
  • Provide a response to a user’s natural language input
  • Extract intents and entities trained in Watson Assistant

Question 4: TJBot can recognize the verbal emotions by using the method analyzeTone.

  • True
  • False

Question 5: Which methods can be chained together with the converse method? Select all that apply.

  • listen
  • speak
  • translate
  • analyzeTone

Question 6: What is the correct order of the following three arguments that are passed to the TJBot constructor?

1. Hardware, a JavaScript array of strings, i.e. speaker, microphone, camera

2. A JavaScript object with Watson service credentials

3. A JavaScript object with configuration settings like the language to speak

Select an option

  • #1 #3 #2
  • #1 #2 #3
  • #3 #2 #1
  • #2 #1 #3

Question 7: Jane wrote this code in Node.js, but the code is not working as expected. Which number points in the code identify the code that should be corrected? Select all that apply.

var TJBot = require(“tjbot”);

var tj = new TJBot( 

  [“speaker”],  // #1

  {

    listen: {

      language: “en-US” // #2  

    }

  }, 

  {

    speech_to_text: {

      username: “”,  // #3  

      password: “” // #4

    }

  });

tj.listen(function(text) { 

  console.log(text); 

});

tj.stopListening(); // #5 

  • #1
  • #2
  • #3
  • #4
  • #5

Question 8: Select all the core hardware that is supported by TJBot by default.

  • Raspberry Pi
  • Microphone
  • Thermometer
  • Speaker
  • Camera
  • LED light
  • Servo

Question 9: What is the variable workspaceId used for in the following code?

var TJBot = require(“tjbot”);

var tj = new TJBot(

  [“microphone”,”speaker”],

  {

    robot: {

      gender: “male”

    },

    speak: {

      language: “en-US”

    }

  },

  {

    speech_to_text: {

      username: “”,

      password: “”

    },

    conversation: {

      username: “”,

      password: “”

    },

    text_to_speech: {

      username: “cf63b1f3-ef18-4628-86c8-6b1871e076b9”,

      password: “MWNwz3qcdIab”

    }   

  }

);

var workspaceId = “”;

function processText(text) {

  console.log(text);

  tj.stopListening();

  tj.converse(workspaceId, text, response => {

    console.log(response);

    tj.speak(response.object.output.text.join(” “)).then(function(){

      tj.listen(processText);

    });

  });

}

tj.listen(processText);

  • It segregates multiple user’s conversations with TJBot.
  • It references a specific Watson Assistant service instance workspace that processes the natural language input
  • It is an identifier that is used to continue the interaction with a single user over multiple calls

Question 10: Review the following code. Then, review the code blocks. Select the code block number that you must change to add in the placeholder labeled TODO to complete this program?

var TJBot = require(“tjbot”);

var tj = new TJBot(

  [“camera”,”speaker”],

  {

    robot: {

      gender: “male”

    },

    speak: {

      language: “en-US”

    }

  },

  {

    // TODO: answer the question

    text_to_speech: {

      username: “”,

      password: “”

    }

  });

tj.see(function(objects) {

  console.log(objects);

  var text = “T J Bot sees ” + objects.map(item => item[“class”]).join(“, “);

  console.log(text);

  tj.speak(text);

});   

CODE BLOCK 1

visual_recognition: {

  username: “”,

  password: “”

},

CODE BLOCK 2

visual_recognition: {

  apikey: “”

},

CODE BLOCK 3

No code changes are required. This program will run correctly without any changes.

  • CODE BLOCK 1
  • CODE BLOCK 2
  • CODE BLOCK 3

Introduction to Building Robots with TJBot

Building robots with TJBot is an exciting endeavor that combines programming, electronics, and creativity. TJBot is an open-source project created by IBM that provides a framework for building your own AI-powered robot using a Raspberry Pi and various other components. It’s designed to be an accessible platform for beginners to learn about artificial intelligence, robotics, and programming.

Here’s a basic introduction to building robots with TJBot:

  1. Hardware Components: To build a TJBot, you’ll need a few key hardware components:
    • Raspberry Pi: A credit card-sized computer that serves as the brain of the robot.
    • Microphone: For capturing audio input.
    • Speaker: For providing audio output.
    • LED: To display various colors and statuses.
    • Servo Motor: Optional component for moving TJBot’s arm.
  2. Software Stack: TJBot runs on the Raspberry Pi using a combination of open-source software tools and libraries. Some of the key software components include:
    • Node.js: TJBot’s programming language, allowing you to write code to control its behavior.
    • Watson Developer Cloud services: IBM’s suite of AI services, including Watson Assistant for conversation, Watson Speech to Text for speech recognition, and Watson Text to Speech for speech synthesis.
    • Open-source libraries: Various Node.js libraries tailored for controlling hardware components like LEDs and servo motors.
  3. Assembly: Once you have all the necessary hardware components, you’ll need to assemble them according to the instructions provided by the TJBot project. This typically involves connecting the microphone, speaker, LED, and any other components to the Raspberry Pi.
  4. Programming: With the hardware assembled, you can start programming TJBot to perform various tasks. This could include:
    • Creating conversational interfaces using Watson Assistant to interact with users.
    • Implementing speech recognition and synthesis to enable voice commands and responses.
    • Controlling the LED to provide visual feedback based on TJBot’s state or user interactions.
    • Adding additional capabilities like object recognition, sentiment analysis, or weather forecasting using Watson services or other APIs.
  5. Customization and Expansion: One of the great things about TJBot is that it’s highly customizable and extensible. Once you have the basic functionality up and running, you can experiment with adding new hardware components, integrating additional software services, or modifying TJBot’s behavior to suit your needs or interests.

Overall, building robots with TJBot is a fun and educational way to learn about robotics, artificial intelligence, and programming. Whether you’re a beginner looking to get started in the world of robotics or an experienced maker wanting to explore new technologies, TJBot offers a rewarding and accessible platform for experimentation and creativity.

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