Improved strategies for a zero oov rate LVCSR system
M. Ali Basha Shaik, Amr El-Desoky Mousa, Stefan Hahn, Ralf Schlüter, Hermann Ney
Abstract
In this work, multiple hierarchical language modeling strategies for a zero OOV rate large vocabulary continuous speech recognition system are investigated. In our previously proposed hierarchical approach, a full-word language model and a context independent character-level LM (CLM) are directly used during search. The novelty of this work is to jointly model the character-level prior and the pronunciation probabilities, to introduce across-word context into the characterlevel LM, and to properly normalize the character-level LM using prefix-tree based normalization for the hierarchical approach. Significant reductions in-terms of word error rates (WER) on the best full-word Quaero Polish LVCSR system are reported.
BibTeX
@inproceedings{icassp2015_improvedstrategi,
title = {Improved strategies for a zero oov rate LVCSR system},
author = {M. Ali Basha Shaik and Amr El-Desoky Mousa and Stefan Hahn and Ralf Schlüter and Hermann Ney},
booktitle = {ICASSP 2015},
year = {2015}
}