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Incremental processing of noisy user utterances in the spoken language understanding task

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Figure

Figure 1: model-agnostic approach
Figure 3: adapted Levenshtein distance
Table 1: CO-MC F1-scores / intents accuracies of the first 100 %, 75 %, 50 %, and 25 % of the tokens of theutterances of the test dataset of the cleaned human transcribed full utterances
Table 6: Intents accuracies / percentages of the used tokens for predicting the intents using the first partial utteranceof the test dataset of the automatically transcribed incremental utterances for which the system has a confidence ofmore or equal than 95 %, 90 %, 85 %, and 80 %, if the confidence is not reached, the full utterance is used
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