Over the years, sophisticated techniques for utilizing the prior knowledge in the form of text-derived language model and in pronunciation lexicon evolved. However, their use has an undesirable effect: unexpected lexical items (words) in the phrase are replaced by acoustically acceptable in-vocabulary items [1]. This is the major source of error since the replacement often introduces additional errors [2, 3]. Improving the machine ability to handle these unexpected words would considerably increase the utility of speech recognition technology.
Cite as: Ketabdar, H., Hannemann, M., Hermansky, H. (2007) Detection of out-of-vocabulary words in posterior based ASR. Proc. Interspeech 2007, 1757-1760, doi: 10.21437/Interspeech.2007-492
@inproceedings{ketabdar07_interspeech,
author={Hamed Ketabdar and Mirko Hannemann and Hynek Hermansky},
title={{Detection of out-of-vocabulary words in posterior based ASR}},
year=2007,
booktitle={Proc. Interspeech 2007},
pages={1757--1760},
doi={10.21437/Interspeech.2007-492}
}