Finite state language models smoothed using n-grams

International Journal of Pattern Recognition and Artificial Intelligence

Volumn 16, Issue 3, 2002, Pages 275-289

  Llorens, David ^a   Vilar, Juan Miguel ^a   Casacuberta, Francisco ^b  

^a UNIVERSITAT JAUME I   (Spain)

^b UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

Author keywords

Language modeling; Smoothing; Stochastic finite state automata

Indexed keywords

FORMAL LANGUAGES; MATHEMATICAL MODELS; PROBABILITY DISTRIBUTIONS; PROBLEM SOLVING; RANDOM PROCESSES; SPEECH RECOGNITION;

LANGUAGE MODELING;

FINITE AUTOMATA;

EID: 0036564911     PISSN: 02180014     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218001402001666     Document Type: Conference Paper

References (6)

1. Learning deterministic regular grammars from stochastic samples in polynomial time
2. An empirical study of smoothing techniques for language modeling
3. Statistical language modeling using the CMU-Combridge Toolkit
4. Smoothing probabilistic automata: An error-correcting approach
5. Estimation of probabilities from sparse data for the language model component of a speech recognizer
6. The estimation of powerful language models from small and large corpora