Introduction to NLP: The Noisy Channel Model and Applications
Delve into the intriguing field of Natural Language Processing (NLP) with an exploration of the Noisy Channel Model. Understand how encoding, decoding, and translation models play a crucial role in language processing tasks. Explore examples, such as translating phrases and correcting spelling, to grasp the model's application in handwriting recognition, text generation, and machine translation. Discover the significance of the Noisy Channel Model in modern communication technologies and its potential for enhancing various linguistic processes.
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Introduction to NLP The Noisy Channel Model
The Noisy Channel Model Example: Input: Written English (X) Encoder: garbles the input (X->Y) Output: Spoken English (Y) More examples: Grammatical English to English with mistakes English to bitmaps (characters) P(X,Y) = P(X)P(Y|X)
Encoding and Decoding Given f, guess e f e e E F encoder F E decoder e = argmax P(e|f) = argmax P(f|e) P(e) e e translation model language model
Example Translate la maison blanche P(f|e) P(e) cat rat piano house white the the house white the red house the small cat the white house
Example Translate la maison blanche P(f|e) - + P(e) - - cat rat piano house white the the house white the red house the small cat the white house
Example Translate la maison blanche P(f|e) - + + - - + P(e) - - - + + + cat rat piano house white the the house white the red house the small cat the white house
Uses of the Noisy Channel Model Handwriting recognition Text generation Text summarization Machine translation Spelling correction See separate lecture on text similarity and edit distance
Spelling Correction From Peter Norvig: http://norvig.com/ngrams/ch14.pdf