Natural Language Processing: Crash Course Computer Science

Natural Language Processing: Crash Course Computer Science

Assessment

Interactive Video

Computers

9th - 10th Grade

Practice Problem

Hard

Created by

Wayground Content

FREE Resource

The video explores natural language processing (NLP), discussing its history, challenges, and applications. It covers parts of speech, grammar rules, and the construction of parse trees. The video also delves into natural language tasks, highlighting the limitations of early chatbots and the advancements in machine learning. Additionally, it examines speech recognition and synthesis, explaining how computers process and generate speech. The video concludes with the growing ubiquity of voice interfaces and their impact on human-computer interaction.

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10 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a key difference between programming languages and natural languages?

Programming languages have large vocabularies.

Natural languages are used only by computers.

Natural languages follow strict syntactic rules.

Programming languages require error-free syntax.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is NOT a part of speech?

Noun

Conjunction

Adjective

Phrase

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a parse tree used for in NLP?

To translate languages

To store vocabulary

To compile code

To tag words with parts of speech and show sentence structure

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a common limitation of early chatbots?

They could only operate offline.

They were unable to recognize any speech.

They could not process any user input.

They relied heavily on predefined rules.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How do modern chatbots improve their responses?

By using only predefined responses

By ignoring user input

By manually updating rules

By using machine learning on large datasets

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What was the first speech recognition system capable of recognizing?

Complex sentences

Numerical digits

Only vowels

All English words

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the role of a language model in speech recognition?

To convert text to speech

To store phonetic components

To generate robotic sounds

To improve transcription accuracy by predicting word sequences

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