'Gram counts' presentation slideshows

Random Forests and the Data Sparseness Problem in Language Modeling

Random Forests and the Data Sparseness Problem in Language Modeling. Shih-Hsiang Lin ( ??? ) Department of Computer Science & Information Engineering National Taiwan Normal University. Reference:

693 views • 53 slides

Penalized EP for Graphical Models Over Strings

Penalized EP for Graphical Models Over Strings. Ryan Cotterell and Jason Eisner. Natural Language is Built from Words. Can store info about each word in a table. Problem: Too Many Words!. Technically speaking, # words = ? Really the set of (possible) words is ?* Names Neologisms Typos

447 views • 43 slides

iVector approach to Phonotactic LRE

iVector approach to Phonotactic LRE. Mehdi Soufifar 2 nd May 2011. Phonotactic LRE. Extract n-gram statistics. Train :. Phoneme sequence. N-gram counts. Train Classifier LR, SVM, LM GLC,. L. L. Classifier. Recognizer ( Hvite,BUTPR ,...). Recognizer ( Hvite,BUTPR ,...).

373 views • 25 slides

Phonotactic Language Recognition using i -vectors and Phoneme Posteriogram Counts

301 views • 13 slides