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Questions and Answers
What is the main purpose of language modeling?
What is the main purpose of language modeling?
- To translate between different natural languages
- To model the probability of sequences of words or characters (correct)
- To analyze the structure and grammar of languages
- To generate synthetic research papers
What is the maximum likelihood solution for a multinomial distribution used to model text data?
What is the maximum likelihood solution for a multinomial distribution used to model text data?
- The probability of each word is equal to the square root of its frequency in the data
- The probability of each word is equal to the logarithm of its frequency in the data
- The probability of each word is inversely proportional to its frequency in the data
- The probability of each word is proportional to its frequency in the data (correct)
What is an N-gram model used for in language modeling?
What is an N-gram model used for in language modeling?
- To model the probability of entire documents
- To model the probability of sentences
- To model the probability of sequences of N words (correct)
- To model the probability of individual words
What is a common application of language modeling mentioned in the text?
What is a common application of language modeling mentioned in the text?
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What is an example of a task that generates synthetic text, as mentioned in the text?
What is an example of a task that generates synthetic text, as mentioned in the text?
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Study Notes
Language Modelling
- Language modelling has applications in machine translation, speech recognition, spell checking, natural language generation, and more.
Introduction to Lecture
- The lecturer mentions having a warm conversation with the class, which includes "amazing ladies and gentlemen".
- The lecturer had a delicious tea and mentions the weather (large winds tonight) and a popular book (The tail of two cities).
Real-World Examples of Language Modelling
- Google autocompletion is a real-world example of language modelling.
- Google Translate is another example of language modelling.
Natural Language Generation
- An example of natural language generation can be found at https://pdos.csail.mit.edu/archive/scigen/#generate.
Modelling Text with Multinomial Distribution
- Multinomial models the outcome of a single event out of K possibilities.
- The parameter of a multinomial model is the probability of each possibility.
- In the context of text data, K represents the vocabulary size.
- At each position in the text, one of the words in the vocabulary appears.
Maximum Likelihood Solution
- Assume word i appeared mi times, and let the total number of words in a document be N.
- The maximum likelihood solution is calculated based on the probability of each word.
Probabilistic Modelling
- Probabilistic modelling is a key concept in language modelling.
- Conditional probabilities are used in language modelling.
Language Modelling with N-Grams
- N-Grams are used in language modelling.
- Conditionals are an important aspect of language modelling with N-Grams.
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