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Harald Sack

Next step in our brief timeline of (large) from our lecture was statistical language modeling with n-grams based on large text corpora as introduced and popularized by Frederick Jelinek and Stanley F. Chen using statistical tricks like Bayes Theorem, Markov Assumption, and Maximum Likelihood Estimation, etc.
Slides: drive.google.com/file/d/1atNvM
@fizise

Slide from the Information Service Engineering 2023 lecture. Brief Timeline of (Large) Language Models about statistical N-gram models. "1990s: N-grams for statistical language modeling were introduced and popularized by Frederick Jelinek and Stanley F. Chen from IBM Thomas J. Watson Research Center, who developed efficient algorithms and techniques for estimating n-gram probabilities from large text corpora for speech recognition and machine translation." Furthermore, the formula to compute the conditional probability of an n-gram is given with a depiction of the N-gram Shakespeare generator with 1-grams, 2-grams, 3-grams and 4-grams. The picture of WIlliam Shakespeare has been created via ArtBot. Bibliography: F. Jelinek (1997), Statistical Methods for Speech Recognition, MIT Press, Cambridge, MA.
Aug 03, 2023, 09:31 AM·Public·Web
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