Getting Started with NLP: The What, Why, and How Quiz Quiz

1. Defining NLP

   Which of the following best describes Natural Language Processing (NLP)?

   1. A method for machines to process and analyze human language.
   2. A way to grow plants without soil.
   3. A technique for making computer graphics smoother.
   4. A process to enhance physical networking in computers.
   5. A type of programming for operating household appliances.

2. The Need for NLP

   Why is NLP important in modern technology?

   1. It helps computers understand spoken and written human languages.
   2. It allows robots to move their arms faster.
   3. It improves battery life in mobile devices.
   4. It makes computer hardware lighter.
   5. It reduces the cost of internet service.

3. Basic Application Example

   Which of the following is an example of NLP in everyday life?

   1. A smart assistant responding to voice commands to set reminders.
   2. A camera automatically adjusting focus.
   3. A calculator solving mathematical equations.
   4. A printer connecting with Wi-Fi.
   5. A fitness tracker counting steps.

4. Common NLP Task

   What is sentiment analysis in NLP?

   1. Detecting the emotion or opinion behind a text, like labeling a movie review as positive or negative.
   2. Translating text from one language to another.
   3. Sorting emails alphabetically.
   4. Matching colors in an image.
   5. Calculating the speed of network traffic.

5. How Machines Understand Text

   What does 'tokenization' mean in NLP?

   1. Dividing a sentence into individual words or parts called 'tokens'.
   2. Making digital tokens for electronic payments.
   3. Adding security tokens to user accounts.
   4. Spinning a coin to randomize results.
   5. Fusing multiple sentences into one paragraph.

6. Ambiguity in Language

   Why can NLP be challenging when understanding words like 'bat' in 'He saw a bat by the lamp'?

   1. Because many words have multiple meanings depending on context.
   2. Because computers can only process numbers.
   3. Because 'bat' is always slang and must be translated.
   4. Because machines ignore any words with three letters.
   5. Because all animal names are skipped during analysis.

7. NLP Data Source

   Where does NLP usually obtain its input data from?

   1. Texts such as books, emails, articles, and speech transcripts.
   2. Wind speed measurements.
   3. Blueprints of buildings.
   4. Satellite images only.
   5. Chemical formulas.

8. NLP and Translation

   Which task demonstrates the use of NLP in language translation?

   1. Automatically converting an English sentence into Spanish on a website.
   2. Drawing a picture based on a description.
   3. Playing music when the user smiles.
   4. Turning off the lights at sunset.
   5. Mixing different paint colors automatically.

9. Speech and NLP

   How does NLP handle spoken language, such as in voice searches?

   1. It converts speech to text and then processes the textual input.
   2. It changes voice pitches to sound robotic.
   3. It stores audio clips without processing.
   4. It only works with handwritten notes.
   5. It creates random melodies from speech.

10. Acronym Recognition

    If you see 'NLP' mentioned in a computer science book, what does it most likely mean?

    1. Natural Language Processing
    2. Network Layer Protocol
    3. Numeric Linear Prediction
    4. Non-Linear Programming
    5. Near-Lossless Packing