Natural Language Processing: Crash Course Computer Science

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.

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.

Which of the following is NOT a part of speech?

• Noun

• Conjunction

• Adjective

• Phrase

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

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.

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

What was the first speech recognition system capable of recognizing?

• Complex sentences

• Numerical digits

• Only vowels

• All English words

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

What is a spectrogram used for in speech recognition?

• To visualize sound frequencies over time

• To amplify sound waves

• To convert text to sound

• To store audio files

What is a key challenge in speech synthesis?

• Storing large datasets

• Recognizing spoken words

• Blending phonemes smoothly

• Creating a robotic sound

What is driving the improvement of voice user interfaces?

• Decreased use of voice interaction

• Limited data for training

• Lack of interest in voice technology

• Positive feedback loop from increased usage