We present the application of statistical language modeling methods for the prediction of the next dialogue act. This prediction is used by different modules of the speech-to-speech translation system VERBMOBIL. The statistical approach uses deleted interpolation of n-gram frequencies as basis and determines the interpolation weights by a modified version of the standard optimization algorithm. Additionally, we present and evaluate different approaches to improve the prediction process, e.g. including knowledge from a dialogue grammar. Evaluation shows that including the speaker information and mirroring the data delivers the best results.
Cite as: Reithinger, N., Engel, R., Kipp, M., Klesen, M. (1996) Predicting dialogue acts for a speech-to-speech translation system. Proc. 4th International Conference on Spoken Language Processing (ICSLP 1996), 654-657, doi: 10.21437/ICSLP.1996-165
@inproceedings{reithinger96_icslp,
author={Norbert Reithinger and Ralf Engel and Michael Kipp and Martin Klesen},
title={{Predicting dialogue acts for a speech-to-speech translation system}},
year=1996,
booktitle={Proc. 4th International Conference on Spoken Language Processing (ICSLP 1996)},
pages={654--657},
doi={10.21437/ICSLP.1996-165}
}