Đây là một lớp tổng quát và gặp rất nhiều lần trong quá trình làm việc trên
dialog nói riêng và trên các ứng dụng MFC nói chung.
Lớp CWnd cung cấp các chức năng cơ bản cho tất cả các lớp cửa sổ1 (các
control, mainframe, view, dialog…) trong thư viện MFC.
Dialogs (giao thoại) được dùng để hiển thị tin tức và nhận mouse hay keyboard input từ users tùy
theo tình huống. Chúng được dùng để tập trung sự chú ý của users vào công tác đương thời của
program nên rất hữu dụng trong các chương trình của Windows.
6.2.1.Tô màu đồng nhất (Fill Color Dialog) Fill Tool là công cụ tô màu với nhiều kiểu tô khác nhau như tô màu đồng nhất (Uniform Fill), tô màu chuyển sắc (Fountain Fill), . . . Khi bạn nhấp chọn vào công cụ Fill Tool trên thanh ToolBox, bảng tùy chọn các công cụ tô màu xuất hiện.
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.
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.
[ 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.
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 . . .
User simulations are shown to be useful in spoken dialog system development. Since most current user simulations deploy probability models to mimic human user behaviors, how to set up user action probabilities in these models is a key problem to solve. One generally used approach is to estimate these probabilities from human user data. However, when building a new dialog system, usually no data or only a small amount of data is available.
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. ...
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. ...
This paper describes a spoken dialog QA system as a substitution for call centers. The system is capable of making dialogs for both ﬁxing speech recognition errors and for clarifying vague questions, based on only large text knowledge base. We introduce two measures to make dialogs for ﬁxing recognition errors. An experimental evaluation shows the advantages of these measures.
The centering framework explains local coherence by relating local focus and the form of referring expressions. It has proven useful in monolog, but its utility for multiparty discourse has not been shown, and a variety of issues must be tackled to adapt the model for dialog. This paper reports our application of three naive models of centering theory for dialog. These results will be used as baselines for evaluating future models.
In this paper we describe a systematic approach for creating a dialog management system based on a Construct Algebra, a collection o f relations and operations on a task representation. These relations and operations are analytical components for building higher level abstractions called dialog motivators.
In this paper, we propose an annotation schema for the discourse analysis of Wikipedia Talk pages aimed at the coordination efforts for article improvement. We apply the annotation schema to a corpus of 100 Talk pages from the Simple English Wikipedia and make the resulting dataset freely available for download1 . Furthermore, we perform automatic dialog act classiﬁcation on Wikipedia discussions and achieve an average F1 -score of 0.82 with our classiﬁcation pipeline.