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Number 3 - September 2013
Volume 23 - 2013
Pipelined language model construction for Polish speech recognition
Jerzy Sas, Andrzej Żołnierek
Abstract
The aim of works described in this article is to elaborate and experimentally evaluate a consistent method of Language
Model (LM) construction for the sake of Polish speech recognition. In the proposed method we tried to take into account
the features and specific problems experienced in practical applications of speech recognition in the Polish language, reach
inflection, a loose word order and the tendency for short word deletion. The LM is created in five stages. Each successive
stage takes the model prepared at the previous stage and modifies or extends it so as to improve its properties. At the first
stage, typical methods of LM smoothing are used to create the initial model. Four most frequently used methods of LM
construction are here. At the second stage the model is extended in order to take into account words indirectly co-occurring
in the corpus. At the next stage, LM modifications are aimed at reduction of short word deletion errors, which occur
frequently in Polish speech recognition. The fourth stage extends the model by insertion of words that were not observed
in the corpus. Finally the model is modified so as to assure highly accurate recognition of very important utterances. The
performance of the methods applied is tested in four language domains.
Keywords
automatic speech recognition, hidden Markov model, adaptive language model