Grammatical category disambiguation by statistical optimization
Computational Linguistics
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
The EM algorithm for graphical association models with missing data
Computational Statistics & Data Analysis - Special issue dedicated to Toma´sˇ Havra´nek
Tagging English text with a probabilistic model
Computational Linguistics
TnT: a statistical part-of-speech tagger
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
A stochastic parts program and noun phrase parser for unrestricted text
ANLC '88 Proceedings of the second conference on Applied natural language processing
Parameter estimation for probabilistic finite-state transducers
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Implementing NFAS in a spreadsheet
Journal of Computing Sciences in Colleges
Making hidden Markov models more transparent
TeachNLP '05 Proceedings of the Second ACL Workshop on Effective Tools and Methodologies for Teaching Natural Language Processing and Computational Linguistics
TeachCL '08 Proceedings of the Third Workshop on Issues in Teaching Computational Linguistics
Models and training for unsupervised preposition sense disambiguation
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Exploiting partial annotations with EM training
WILS '12 Proceedings of the NAACL-HLT Workshop on the Induction of Linguistic Structure
Hi-index | 0.00 |
This paper offers a detailed lesson plan on the forward-backward algorithm. The lesson is taught from a live, commented spreadsheet that implements the algorithm and graphs its behavior on a whimsical toy example. By experimenting with different inputs, one can help students develop intuitions about HMMs in particular and Expectation Maximization in general. The spreadsheet and a coordinated follow-up assignment are available.