| 摘要 |
The invention concerns a process for semantic speech analysis, wherein by sequential comparison of word and label the verifiability of the data is increased and the production of larger amounts of data is accelerated, which data are required in stochastic modeling. Besides this, the inventive process makes possible the problem-free combination of semantic and syntactic labels. This flexible production of training data with scaleable information content is important for an experimental determination of optimal model characteristics of the labeling process.
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