Misscommunication
On the use of expectations for detecting and repairing human-machine miscommunication
CSELT Centro Studi E Laboratori Telecomunicazioni S.p.A. Via G. Reiss Romoli 274 I-10148 Torino, Italy E-Mail: Morena.Danieli@cselt.stet.it
In this paper I describe how miscommunication problems are dealt with in the spoken language system DIALOGOS. The dialogue module of the system exploits dialogic expectations in a twofold way: to model what future user utterance might be about (predictions), and to account how the user 's next utterance may be related to previous ones in the ongoing interaction (pragmatic-based expectations). The analysis starts from the hypothesis that the occurrence of miscommunication is concomitant with two pragmatic phenomena: the deviation of the user from the expected behaviour and the generation of a conversational implicature. A preliminary evaluation of a large amount of interactions between subjects and DIALOGOS shows that the system performance is enhanced by the uses of both predictions and pragmatic-based expectations.
Morena Danieli
Abstract
During the last few years it has been emerging that the success of spoken language systems is greatly improved by the contextual reasoning of dialogue modules. This tenet has spread through both the speech and the dialogue communities. Dialogue systems devoted to spoken language applications are able to detect partial communication breakdowns by other system modules, and that increases the robustness of human-machine interactions by speech. During oral interactions with computers, communication problems often arise after the occurrence of errors during the recognition phase. Sometimes these errors cannot be solved by the semantic module: the utterances containing them are interpreted by the semantic analyser, but with an information content different from the speaker 's intended meaning. Detecting such miscommunications and repairing them through initialization of appropriate repair subdialogues
CSELT Centro Studi E Laboratori Telecomunicazioni S.p.A. Via G. Reiss Romoli 274 I-10148 Torino, Italy E-Mail: Morena.Danieli@cselt.stet.it
In this paper I describe how miscommunication problems are dealt with in the spoken language system DIALOGOS. The dialogue module of the system exploits dialogic expectations in a twofold way: to model what future user utterance might be about (predictions), and to account how the user 's next utterance may be related to previous ones in the ongoing interaction (pragmatic-based expectations). The analysis starts from the hypothesis that the occurrence of miscommunication is concomitant with two pragmatic phenomena: the deviation of the user from the expected behaviour and the generation of a conversational implicature. A preliminary evaluation of a large amount of interactions between subjects and DIALOGOS shows that the system performance is enhanced by the uses of both predictions and pragmatic-based expectations.
Morena Danieli
Abstract
During the last few years it has been emerging that the success of spoken language systems is greatly improved by the contextual reasoning of dialogue modules. This tenet has spread through both the speech and the dialogue communities. Dialogue systems devoted to spoken language applications are able to detect partial communication breakdowns by other system modules, and that increases the robustness of human-machine interactions by speech. During oral interactions with computers, communication problems often arise after the occurrence of errors during the recognition phase. Sometimes these errors cannot be solved by the semantic module: the utterances containing them are interpreted by the semantic analyser, but with an information content different from the speaker 's intended meaning. Detecting such miscommunications and repairing them through initialization of appropriate repair subdialogues
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