20240926 - TA - Language Modeling

The video discussed the applications and limitations of language modeling, including its use in various tasks such as machine translation and classification, while highlighting the differences between unigram and diagram models.
Language modeling is a system that predicts upcoming words and assigns probabilities to potential next words.
Language models have various applications, including machine translation, spell correction, speech recognition, and summarization.
Bag-of-words text representation has limitations in handling word similarities and sentence structure, while language modeling allows for sequence and order analysis.
Language modeling can be used for binary or multiple-class classification and structure prediction. Neural networks are commonly used for complex predictions.
A n-grams calculate the frequency of word appearances and the probability of words appearing after each other.
Unigram language models only consider the probability of individual words, while diagram models consider the probability of word pairs.
The highest probability sentence in a unigram model is "I like ice cream," while in a diagram model it is "I want Chinese food."