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Dialog participants in a non-mixed initiative dialogs, in which one participant asks questions exclusively and the other participant responds to those questions exclusively, can select actions that minimize the expected length of the dialog. The choice of question that minimizes the expected number of questions to be asked can be computed in polynomial time in some cases. The polynomial-time solutions to special cases of the problem suggest a number of strategies for selecting dialog actions in the intractable general case. ...
Previous studies evaluate simulated dialog corpora using evaluation measures which can be automatically extracted from the dialog systems’ logs. However, the validity of these automatic measures has not been fully proven. In this study, we ﬁrst recruit human judges to assess the quality of three simulated dialog corpora and then use human judgments as the gold standard to validate the conclusions drawn from the automatic measures. We observe that it is hard for the human judges to reach good agreement when asked to rate the quality of the dialogs from given perspectives.
This work presents an agenda-based approach to improve the robustness of the dialog manager by using dialog examples and n-best recognition hypotheses. This approach supports n-best hypotheses in the dialog manager and keeps track of the dialog state using a discourse interpretation algorithm with the agenda graph and focus stack. Given the agenda graph and n-best hypotheses, the system can predict the next system actions to maximize multi-level score functions. To evaluate the proposed method, a spoken dialog system for a building guidance robot was developed.
Current statistical speech translation approaches predominantly rely on just text transcripts and do not adequately utilize the rich contextual information such as conveyed through prosody and discourse function. In this paper, we explore the role of context characterized through dialog acts (DAs) in statistical translation. We demonstrate the integration of the dialog acts in a phrase-based statistical translation framework, employing 3 limited domain parallel corpora (Farsi-English, Japanese-English and Chinese-English).
A considerable amount of work in current AI research is concerned with inferring intentions from utterances (e.g., [Allen 83], [Carberry 83], [Grosz, Sidner 86]) or planning speech acts serving certain goals (e.g., [Appelt 85]), but only a few uniform approaches to both aspects have been presented. Most approaches to dialog control described in the literature offer either rigid action schemata that enable the simulation of the desired behavior on the surface (but lack the necessary degree of flexibility, e. g.
[ Team LiB ] The Reading Pane Microsoft replaced the Preview pane with what it calls the Reading Pane. By default, the Reading Pane is on the right side of the window, although you can move it to the bottom of the window or turn it off completely. When the Reading Pane is on the right, more of the message is visible, which means less scrolling is required and your efficiency is improved when reading large volumes of email. You can change the position of the Reading Pane using the Other Settings dialog, or by right-clicking in the gray border...
[ Team LiB ] Creating Custom Views The power of views comes not from the predefined views, but from the ability to create your own custom views. You can customize the current view used on any folder, create new views, or customize any of the default views included with Outlook. All custom view options are on the Custom View dialog. Open the dialog by rightclicking on the field names at the top of the list pane and selecting Custom. The options you can choose from when customizing or creating views include...
17.4. Rewriting the Words Mac OS X stores the text and settings of its menus, dialog boxes, and other elements in special text files called plist (for Property List) files. They sit in one of the three Library folders (in your Home folder, the System folder, or the hard drive window)
Sử dụng thường Dialog Controls The Bell Ringers ứng dụng bây giờ cho phép bạn lưu thông tin, nhưng nó luôn luôn lưu dữ liệu vào cùng một tập tin, ghi đè lên bất cứ điều gì đã có. Ngoài ra, các chức năng in ấn vẫn còn mất tích. Bây giờ là thời gian để giải quyết những vấn đề này.
[ Team LiB ] Recipe 1.13 Using the Data Link Properties Dialog Box Problem You want to display the Data Link Properties dialog box from an application so that users can create their own database connections just as they can from the Server Explorer window in the Visual Studio .NET IDE.
An open-domain spoken dialog system has to deal with the challenge of lacking lexical as well as conceptual knowledge. As the real world is constantly changing, it is not possible to store all necessary knowledge beforehand. Therefore, this knowledge has to be acquired during the run time of the system, with the help of the out-of-vocabulary information of a speech recognizer. As every word can have various meanings depending on the context in which it is uttered, additional context information is taken into account, when searching for the meaning of such a word.
We report on an investigation of the pragmatic category of topic in Danish dialog and its correlation to surface features of NPs. Using a corpus of 444 utterances, we trained a decision tree system on 16 features. The system achieved nearhuman performance with success rates of 84–89% and F 1 -scores of 0.63–0.72 in 10fold cross validation tests (human performance: 89% and 0.78). The most important features turned out to be preverbal position, deﬁniteness, pronominalisation, and non-subordination. We discovered that NPs in epistemic matrix clauses (e.g. “I think . . .
To understand a speaker's turn of a conversation, one needs to segment it into intonational phrases, clean up any speech repairs that might have occurred, and identify discourse markers. In this paper, we argue that these problems must be resolved together, and that they must be resolved early in the processing stream. We put forward a statistical language model that resolves these problems, does POS tagging, and can be used as the language model of a speech recognizer.
This tutorial is about the evolution of speech technology from research to a mature industry. Today, spoken language communication with computers is becoming part of everyday life. Thousands of interactive applications using spoken language technology— known also as “conversational machines”—are only phone calls away, allowing millions of users each day to access information, perform transactions, and get help. Speech recognition, language understanding, text-to-speech synthesis, machine learning, and dialog management enabled this revolution after more than 50 years of research.
Data-driven techniques have been used for many computational linguistics tasks. Models derived from data are generally more robust than hand-crafted systems since they better reﬂect the distribution of the phenomena being modeled. With the availability of large corpora of spoken dialog, dialog management is now reaping the beneﬁts of data-driven techniques. In this paper, we compare two approaches to modeling subtask structure in dialog: a chunk-based model of subdialog sequences, and a parse-based, or hierarchical, model. ...