Download Estimating Spoken Dialog System Quality with User Models by Klaus-Peter Engelbrecht PDF

By Klaus-Peter Engelbrecht

Spoken conversation structures have the aptitude to supply hugely intuitive consumer interfaces, as they enable structures to be managed utilizing normal language. notwithstanding, the complexity inherent in normal language dialogs signifies that cautious checking out of the method has to be performed from the very starting of the layout method. This e-book examines how consumer types can be utilized to aid such early reviews in methods: by means of operating simulations of dialogs, and by way of estimating the standard judgments of clients. First, a layout setting aiding the construction of conversation flows, the simulation of dialogs, and the research of the simulated information is proposed. How the standard of consumer simulations will be quantified with recognize to their suitability for either formative and summative evaluate is then mentioned. the rest of the ebook is devoted to the matter of predicting caliber judgments of clients according to interplay information. New modeling techniques are awarded, which technique the dialogs as sequences, and which enable wisdom concerning the judgment habit of clients to be integrated into predictions. All proposed tools are established with instance overview studies.

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Furthermore analyze Recall and Precision of actions generated by the simulator. This is done on a turn-by-turn basis, feeding each system turn into the simulator, together with the dialog history, and collecting the response of the simulated user. Actions are modeled as a dialog act and the information conveyed. 3 Analysis of Simulated Corpora Using Standard Metrics R ¼ 100 Ã 27 Correctly predicted actions All actions in real response Again, the simulations run by Schatzmann et al. could be distinguished by these measures.

Therefore, in this section two examples of entire dialogs are presented which were generated with our user model. From this, we derive further requirements for a more realistic simulation. 12), the user starts the dialog by naming a number, which makes sense as the number describes a specific TV program. However, in the next two steps the user remains in the start state because of a no-match, but changes her intention twice. A real user would rather try to reformulate the sentence than changing her intention, and would be even more unlikely to change her intention twice.

Please select a title from the list by saying the number I understood number 1. What do you want to do with the program? Example wording Description {reminder} Set a reminder {program_info} Electronic program guide, please {today} Today {evening} After 6 pm {movie} Movies {number} Number 1 please {channel_id} {TV} {reminder} Set a reminder Stating channel name and TV for the TV, not necessary after channel one program has been selected constraints for this subtask should not be produced. However, it is difficult even to just describe this behavior formally for a range of systems or tasks, and even more difficult to formulate general rules which generate such behavior automatically.

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