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An examination of the language construct in NIMH's research domain criteria: Time for reconceptualization!
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Can older people remember medication reminders presented using synthetic speech?
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Evaluating speech synthesis intelligibility using Amazon Mechanical Turk
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The User Model-Based Summarize and Re_ne Approach Improves Information Presentation in Spoken Dialog Systems
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In: ISSN: 0885-2308 ; EISSN: 1095-8363 ; Computer Speech and Language ; https://hal.archives-ouvertes.fr/hal-00692184 ; Computer Speech and Language, Elsevier, 2010, 25 (2), pp.175. ⟨10.1016/j.csl.2010.04.003⟩ (2010)
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Abstract:
International audience ; A common task for Spoken Dialogue Systems (SDS) is to help users select a suitable option (e.g., fight, hotel, restaurant) from the set of options available. As the number of options increases, the system must have strategies for generating summaries that enable the user to browse the option space e_ciently and successfully. In the user-model based summarize and refine approach (UMSR, Demberg and Moore, 2006), options are clustered to maximize utility with respect to a user model, and linguistic devices such as discourse cues and adverbials are used to highlight the trade-o_s among the presented items. In a Wizard-of-Oz experiment, we show that the UMSR approach leads to improvements in task success, e_ciency, and user satisfaction compared to an approach that clusters the available options to maximise coverage of the domain (Polifroni et al., 2003). In both a laboratory experiment and a web-based experimental paradigm employing the Amazon Mechanical Turk platform, we show that the discourse cues in UMSR summaries help users compare diffirent options and choose between options, even though they do not improve verbatim recall. This effect was observed for both written and spoken stimuli.
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Keyword:
[SCCO.LING]Cognitive science/Linguistics; discourse; Information presentation; markers; spoken dialog systems; user modeling
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URL: https://hal.archives-ouvertes.fr/hal-00692184/document
https://hal.archives-ouvertes.fr/hal-00692184/file/PEER_stage2_10.1016%252Fj.csl.2010.04.003.pdf
https://doi.org/10.1016/j.csl.2010.04.003
https://hal.archives-ouvertes.fr/hal-00692184
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The MATCH Corpus: A Corpus of Older and Younger Users' Interactions With Spoken Dialogue Systems.
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