In this paper a method for the automatic construction of a lexicon with multiple entries per word is described. The basic idea is to transform a reference word transcription by means of stochastic pronunciation rules that can be learned automatically. This approach already proved its potential (Cremelie & Martens, 1999), and is now brought to a much higher level of performance. Relative reductions of the word error rate (WER) of 20 % (open vocabulary) to 45 % (closed vocabulary) are now within reach.
N. Cremelie, J.P. Martens. "In search for better pronunciation models for speech recognition," Speech Communication 29, 115-136, 1999.
Cite as: Yang, Q., Martens, J.-P. (2000) Data-driven lexical modeling of pronunciation variations for ASR. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 1, 417-420, doi: 10.21437/ICSLP.2000-103
@inproceedings{yang00c_icslp,
author={Qian Yang and Jean-Pierre Martens},
title={{Data-driven lexical modeling of pronunciation variations for ASR}},
year=2000,
booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
pages={vol. 1, 417-420},
doi={10.21437/ICSLP.2000-103}
}