A recurring problem in speech and language modelling is the estimation of context-specific probability distributions from sparse data. Robust estimates can be obtained by interpolating the probability estimates obtained from context-specific statistics with more general ones. An interpolation technique is described here which, is based on a least-squares weighting formula but with deleted estimation incorporated to optimise its parameters. Perplexity results are given for various statistical language models incorporating this interpolation technique.
Cite as: McInnes, F.R. (1992) An enhanced interpolation technique for context-specific probability estimation in speech and language modelling. Proc. 2nd International Conference on Spoken Language Processing (ICSLP 1992), 1491-1494, doi: 10.21437/ICSLP.1992-187
@inproceedings{mcinnes92_icslp,
author={Fergus R. McInnes},
title={{An enhanced interpolation technique for context-specific probability estimation in speech and language modelling}},
year=1992,
booktitle={Proc. 2nd International Conference on Spoken Language Processing (ICSLP 1992)},
pages={1491--1494},
doi={10.21437/ICSLP.1992-187}
}