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Více informací o knize Increasing Robustness of Spoken Dialogue Systems

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Anotace knihy

In conversational dialogue applications it is§critical to understand the requests accurately.§However, the performance of current speech§recognition systems are far from perfect. In order to§function effectively with imperfect speech§recognition, an accurate confidence scoring mechanism§should be employed. To determine a confidence score§for a hypothesis, certain confidence features are§combined. In this work, the performance of§filler-model based confidence features are§investigated. Five types of filler model are defined:§triphone-network, phone-network, phone-class network,§5-state catch-all model and 3-state catch-all model.§First all models are evaluated in terms of their§ability to correctly tag (miss or hit) recognition§hypotheses. Then the performance of reliable§combinations of these models are evaluated to show§how certain reliable combinations of filler models§could significantly improve the accuracy of the§confidence annotation. Moreover to show the practical§side of the work, an implementation of a real§dialogue management system is described.

Parametry knihy

Zařazení knihy Knihy v angličtině Technology, engineering, agriculture Electronics & communications engineering Electronics engineering

• Plný název: Increasing Robustness of Spoken Dialogue Systems
• Podnázev: Employing Filler Model Based Word Level Confidence Measures
• Autor: Aydin Akyol
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 104
• EAN: 9783836476782
• ISBN: 3836476789
• ID: 06857350
• Nakladatelství: VDM Verlag
• Hmotnost: 163 g
• Rozměry: 229 × 152 × 6 mm
• Datum vydání: 09. June 2009

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