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.
VERBMOBIL REF is a system for speech-to-speech translation, in which statistical language modelling methods are employed for the prediction of the next dialogue act (by computing the probability of a sequence of dialogue acts).
Predicting dialogue acts for a speech-to-speech translation system
Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96
Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96
Computer Science