INF5820, Obligatory Assignment 3: Development of a Spoken Dialogue System
|
|
- Anna Bates
- 8 years ago
- Views:
Transcription
1 INF5820, Obligatory Assignment 3: Development of a Spoken Dialogue System Pierre Lison October 29, 2014 In this project, you will develop a full, end-to-end spoken dialogue system for an application domain of your choice. To this end, you will use the OpenDial toolkit that allows you to design a dialogue system using probabilistic rules specified in XML. An external cloud-based API will be used for speech recognition and synthesis. To complete this assignment, follow the step-by-step explanations in the next pages. Note that you will need a microphone for this assignment (internal microphones in laptops are sufficient). The submission deadline is set to November 19 at 23:59. I advise you to start working on this assignment as early as possible! Step 1: Chose an application domain The first step is to chose any type of application domain for your spoken dialogue system. Here are some examples of possible domains: A dialogue system for ordering pizzas (or sushis, books, etc.). An information kiosk for a public transport network (to answer queries such as when is the next bus arriving at Carl Berners Plass? ). A (simulated) robot able to execute some simple tasks, such as finding and fetching (simulated) objects. A Rogerian psychotherapist similar to the doctor.el script in Emacs. A (very simplified) navigation assistant that can provide driving instructions from place A to place B. A tutoring system that can help you practice a particular skill (e.g. a grammatical construction in a foreign language). A health coach that helps elderly persons with their medication and exercises. 1
2 A virtual receptionist for a company. A (simulated) home automation system that allows you to control particular devices in your house. You are of course not limited to this list of examples! The only constraint for your system is that it must be using speech as communication medium with the human user. You can use Norwegian or English as language for the dialogue system. Please make sure that the application domain you are selecting is constrained enough such that you can develop the application in a reasonable time (remember that you only have 3 weeks to complete this assignment).the goal of the assignment is to give you a better grasp of how spoken dialogue systems work in practice and explore some the concepts seen in the lecture in other words, the goal is not to build a professional-grade application! I would therefore advice you to adopt an iterative approach: start with a basic, toy dialogue domain, and gradually extend its coverage. Step 2: Formalise the task Once you have chosen the task, the next step is to formalise it. More precisely, try to answer the following questions: 1. What are the possible user inputs for the system? Which user utterances should be covered? For instance, a pizza delivery system might need to cover sentences such as what types of pizzas do you have, I would like a pizza X (with X being a pizza type), etc. 2. What are the (communicative and non-communicative) actions available to the dialogue system? In other words, what will the dialogue system be able to say or do? For the pizza delivery example, the action might be to ask the customer for its type of pizza, ask the customer to repeat, confirm the delivery, etc. 3. Which variables need to be recorded in the dialogue state? In other words, are there contextual variables that the system needs to keep track of in your application domain (beyond the last user dialogue act and the last system action)? For instance, a navigation assistant may require the current location of the user as contextual variable. 4. Do you need to implement external modules in addition to the core dialogue system components? If you decide to work on a simulated robot, you need for instance to develop a dummy simulator to represent the robot environment. 2
3 Once you have answered these questions, try to sketch a few interaction scenarios for your domain, and see if these interactions can be fully covered with the user inputs and system actions you have listed. To get a more precise idea of how human users are actually going to interact in your domain, it is also useful to conduct some Wizard-of-Oz experiments: ask a friend to act as a human user, while you are acting as the dialogue system (preferably remotely, e.g. via Skype). You can then adapt your domain design in light of these interactions. Step 3: Install OpenDial The OpenDial toolkit will be used a the main platform to develop your dialogue system. The OpenDial toolkit is a Java-based, domain-independent toolkit that allows system developers to build practical dialogue systems based on probabilistic rules specified in XML. You can find the toolkit and its documentation at the following address: Please checkout the version on the development trunk (as I will sometimes update the code to correct bugs or add new functionalities): svn checkout opendial Once the code is downloaded, you can simply compile it using ant compile and start the toolkit with ant run. You should then go through the step-by-step example in the online documentation to get a better grasp of the toolkit. Note: if you encounter bugs or strange behaviours in OpenDial, please use the issue tracker on the website to record them. Step 4: Set up speech recogniser The first component to set up is the speech recogniser. We are going to use a cloud-based solution. Two cloud-based speech plugins for OpenDial are available: Nuance Speech and AT&T Speech. The Nuance speech recogniser generally has a better recognition performance than AT&T, but AT&T allows you to specify a recognition grammar (while Nuance is limited to a custom vocabulary). I personally recommend you to try the Nuance plugin first, and switch to AT& if you experience problems with the recognition. The installation instructions are detailed in the README.txt file for each plugin. Once you have followed all installation steps, test the setup and check that you can get recognition results in the chat window of OpenDial. If you don t get any result, make sure the microphone is working properly, and that the right audio input source is selected in the OpenDial menu bar. 3
4 You will probably notice that the quality of the recognition results is not always very good. To improve the recognition performance, you should modify the language model used by the speech recogniser. For the Nuance recogniser, this is done by specifying a custom vocabulary a collection of phrases that are especially likely for the domain (please see the documentation on the Nuance website for details). For the AT&T recogniser, this is done by specifying a context-free recognition grammar that covers the set of possible user utterances. Modify the custom vocabulary or recognition grammar until you get recognition results of reasonable accuracy for your domain. Step 5: Construct dialogue act recognition model The next step is to build a natural language understanding model that will map user utterances to high-level, logical representations of the user dialogue act. For instance, one should map an utterance such I would like a peperoni pizza, please! to a predicate such as Request(PeperoniPizza,1). Such mappings can be easily specified using XML rules in OpenDial. To reuse the above example, one can write a rule such as: <condition operator="or"> <if var="u_u" value="a peperoni pizza" relation="in" /> <if var="u_u" value="one peperoni pizza" relation="in" /> <if var="u_u" value="one pizza with peperoni" relation="in" /> </condition> <effect> <set var="a_u" value="request(peperonipizza,1)" /> The above rule specifies that the user dialogue act a u will be set to Request(PeperoniPizza,1) if the user utterance contains a substring such as a peperoni pizza, one peperoni pizza or one pizza with peperoni. Of course, this is a very basic example, and you can write more complex types of rules with nested logical operators, underspecified variables, etc. See the OpenDial documentation for details. The collection of rules should be specified within a model <model trigger="u u">... </model> to get OpenDial to trigger these rules upon changes to the user utterance variable u u. If required for your application domain, you can design more complex NLU models (using e.g. a sequence of several models) to include e.g. reference resolution or other processing tasks. It is up to you to decide how the NLU model should be structured depending on your particular needs. 4
5 Start by specifying a collection of probability rules that maps the possible input utterances to dialogue acts expressed as logical predicates (as in the example above). Once this are done, make sure you properly test your model to ensure that all types of utterances are covered. You can check the results of the mapping process via the Dialogue State Monitor tab in OpenDial. Note: The model will automatically erase the previous values for the user dialogue act a u. In some application domains, it might be useful to keep track of a longer history of dialogue acts. To record the previous dialogue act, you can simply add the following rule to the NLU model, which will record the previous dialogue act in a new variable a u prev. <effect> <set var="a_u-prev" value="{a_u}" /> Step 6: Construct dialogue management model Once the NLU model is in place, you are now ready to construct a simple dialogue manager that will select the most likely system action given the last user dialogue act (and possibly other contextual variables). The dialogue management model will be encoded via utility rules that specify the utility of various system actions depending on state variables. Here is an example of utility rule, which specifies that, if the user orders an item X and quantity Y, the utility of asking the user to confirm X and Y will be set to 2: <condition> <if var="a_u" value="request({x},{y})"/> </condition> <effect util="2> <set var="a_m" value="confirm({x},{y})"/> The system actions may comprise both communicative actions (statements, clarification requests, etc.) and non-communicative actions (for instance, fetching an object). Again, you are free to decide on how you would like to design the dialogue strategies for your application domain. Once you have constructed the model, test it to ensure that the system selects the most appropriate action in each situation. I recommend you to test the system using the speech recogniser, to verify that the dialogue management model also works in the presence of errors and uncertainty. 5
6 Step 7: Construct generation model Communicative actions must be mapped to actual system utterances. This is the purpose of the generation model. The generation model is another utility model that specifies the utility of various linguistic realisations of the selected system action. A typical example of generation rule is the following: <condition> <if var="a_m" value="confirm({x},{y})"/> </condition> <effect util="1> <set var="u_m" value="you ordered {Y} {X}. Is that correct?"/> If you would like to use several alternative realisations for a given system action (in order to introduce some variety in the system behaviour), you can do so by specifying several effects with identical utility. Step 8: Implement external modules Depending on your application domain, you may need to implement additional system modules and connect them to the OpenDial toolkit. Such modules may be used to periodically update the dialogue state with new content (for instance, a simulator may be responsible for updating specific contextual variables related to the user location, perceived objects, etc.). They can also be used as a backend to a database or information repository (for instance, timetables for a transportation system). Or they can be used on the output side to execute non-verbal actions. See the online documentation for more information on how to integrate modules into OpenDial. I would like to stress once more that the purpose of this assignment is not to build a professional-grade application. It is perfectly ok to fake things up or introduce dummy behaviours in the external modules, as they are not the focus of this assignment. Step 9: Construct user act prediction model The current understanding model is quite basic: it directly maps raw user utterances to dialogue acts, without taking into account the likelihood of various dialogue acts given the context. For instance, it is much more likely that the user will utter a sentence such as Put down the object on the floor if the robot actually carries an object. 6
7 We can create such predictive model using probability rules. Here is an example of predictive rules stating that the probability of asking the robot to put down an object will be 0.3 if an object is actually carried, and 0.01 otherwise: <condition> <if var="carriesobject" value="true"/> </condition> <effect prob="0.3> <set var="a_u^p" value="request(putdownobject)"/> <effect prob="0.01> <set var="a_u^p" value="request(putdownobject)"/> Notice the ^p suffix on the output variable, which signals to OpenDial that this rule specifies a prior probability for a future (currently unobserved) user dialogue act a u. Create a set of probability rules that specifies the predicted probability of user dialogue acts depending on the current context (which may correspond to the last user dialogue act, the last system action, or other variables). To help you determine the probability values, you can exploit the Wizard-of-Oz data from Step 2. 1 Step 10: Evaluate dialogue system If you have correctly followed all the steps so far, you should have a working dialogue system. The final step is to evaluate its performance. As we will discuss during the lectures, there are many ways to evaluate spoken dialogue systems. One simple approach is simply to ask external persons to try the system and ask them about their user experience in a survey conducted after the interaction. For this assignment, we will adopt a very simple evaluation scheme: find (at least) two external persons and ask them to interact with your system a few times. Once they are done, ask them to rank their experience on a scale from 1 (worst) to 5 (best). Also ask them whether they have suggestions for future improvements. 1 In an actual system, one would of course derive these probabilities rigorously using statistical methods based on collected dialogue data. 7
8 Step 11: Write and submit small report To complete this assignment, please submit the following in Devilry: The specification of your dialogue domain in the OpenDial XML format. The source code for the additional modules you have developed for your domain (if any). Additional data that you may have used for this project (for instance, Wizard-of-Oz data). A short 3-pages report on the dialogue system you developed. The report should describe the application domain, your design choices, the system components, and the results of the final evaluation. In other words, the report should document what your system does, how you designed it, and what are its current functionalities and limitations. You may write the report in Norwegian or English. Step 12: Present you work! One week after the submission deadline (during the last gruppetime for INF5820), you will be asked to present your dialogue system to your fellow students, and do a short demonstration. 8
Robustness of a Spoken Dialogue Interface for a Personal Assistant
Robustness of a Spoken Dialogue Interface for a Personal Assistant Anna Wong, Anh Nguyen and Wayne Wobcke School of Computer Science and Engineering University of New South Wales Sydney NSW 22, Australia
More informationSpecialty Answering Service. All rights reserved.
0 Contents 1 Introduction... 2 1.1 Types of Dialog Systems... 2 2 Dialog Systems in Contact Centers... 4 2.1 Automated Call Centers... 4 3 History... 3 4 Designing Interactive Dialogs with Structured Data...
More information1. Introduction to Spoken Dialogue Systems
SoSe 2006 Projekt Sprachdialogsysteme 1. Introduction to Spoken Dialogue Systems Walther v. Hahn, Cristina Vertan {vhahn,vertan}@informatik.uni-hamburg.de Content What are Spoken dialogue systems? Types
More informationOpen-Source, Cross-Platform Java Tools Working Together on a Dialogue System
Open-Source, Cross-Platform Java Tools Working Together on a Dialogue System Oana NICOLAE Faculty of Mathematics and Computer Science, Department of Computer Science, University of Craiova, Romania oananicolae1981@yahoo.com
More informationMobile Voice Productivity & Automation. For Field Service Applications
AccuSpeechMobile: Technical Overview Mobile Voice Productivity & Automation For Field Service Applications Mobile Inspections, Repair, Delivery & Asset Management Table of Contents Mobile Workforce Productivity
More informationD2.4: Two trained semantic decoders for the Appointment Scheduling task
D2.4: Two trained semantic decoders for the Appointment Scheduling task James Henderson, François Mairesse, Lonneke van der Plas, Paola Merlo Distribution: Public CLASSiC Computational Learning in Adaptive
More informationThe Workflow Management Coalition Specification Workflow Management Coalition Terminology & Glossary
The Workflow Management Coalition Specification Workflow Management Coalition Terminology & Glossary Workflow The automation of a business process, in whole or part, during which documents, information
More informationIBM. Implementing SMTP and POP3 Scenarios with WebSphere Business Integration Connect. Author: Ronan Dalton
IBM Implementing SMTP and POP3 Scenarios with WebSphere Business Integration Connect Author: Ronan Dalton Table of Contents Section 1. Introduction... 2 Section 2. Download, Install and Configure ArGoSoft
More informationSupport and Compatibility
Version 1.0 Frequently Asked Questions General What is Voiyager? Voiyager is a productivity platform for VoiceXML applications with Version 1.0 of Voiyager focusing on the complete development and testing
More informationSTAT REVIEW/EXECUTIVE DASHBOARD TASK ORDER EXECUTIVE DASHBOARD SYNTHESIS OF BEST PRACTICES
STAT REVIEW/EXECUTIVE DASHBOARD TASK ORDER EXECUTIVE DASHBOARD SYNTHESIS OF BEST PRACTICES October 26, 2011 This publication was produced for review by the United States Agency for International Development.
More informationCopyrighted www.eh1infotech.com +919780265007, 0172-5098107 Address :- EH1-Infotech, SCF 69, Top Floor, Phase 3B-2, Sector 60, Mohali (Chandigarh),
Content of 6 Months Software Testing Training at EH1-Infotech Module 1: Introduction to Software Testing Basics of S/W testing Module 2: SQA Basics Testing introduction and terminology Verification and
More informationSPeach: Automatic Classroom Captioning System for Hearing Impaired
SPeach: Automatic Classroom Captioning System for Hearing Impaired Andres Cedeño, Riya Fukui, Zihe Huang, Aaron Roe, Chase Stewart, Peter Washington Problem Definition Over one in seven Americans have
More informationWebSphere Business Monitor
WebSphere Business Monitor Debugger 2010 IBM Corporation This presentation provides an overview of the monitor model debugger in WebSphere Business Monitor. WBPM_Monitor_Debugger.ppt Page 1 of 23 Goals
More informationHydroDesktop Overview
HydroDesktop Overview 1. Initial Objectives HydroDesktop (formerly referred to as HIS Desktop) is a new component of the HIS project intended to address the problem of how to obtain, organize and manage
More informationApp Development with Talkamatic Dialogue Manager
App Development with Talkamatic Dialogue Manager Dialogue Systems II September 7, 2015 Alex Berman alex@talkamatic.se Staffan Larsson Outline! Introduction to TDM! Technical architecture! App development
More informationAn Automated Development Process for Interlocking Software that. Cuts Costs and Provides Improved Methods for Checking Quality.
An Automated Development Process for Interlocking Software that Cuts Costs and Provides Improved Methods for Checking Quality and Safety Authors: Claes Malmnäs Prover Technology Rosenlundsgatan 54 118
More informationcustomer care solutions
customer care solutions from Nuance white paper :: Understanding Natural Language Learning to speak customer-ese In recent years speech recognition systems have made impressive advances in their ability
More informationVoiceXML-Based Dialogue Systems
VoiceXML-Based Dialogue Systems Pavel Cenek Laboratory of Speech and Dialogue Faculty of Informatics Masaryk University Brno Agenda Dialogue system (DS) VoiceXML Frame-based DS in general 2 Computer based
More informationHudson configuration manual
Hudson configuration manual 1 Chapter 1 What is Hudson? Hudson is a powerful and widely used open source continuous integration server providing development teams with a reliable way to monitor changes
More informationecollege September 2011 quick guide for students
ecollege September 2011 quick guide for students Table of Contents Table of Contents...2 ecollege Quick Guide for Students...3 Gradebook...5 To access the Gradebook:...5 Email...5 To send an email to the
More informationDesign Grammars for High-performance Speech Recognition
Design Grammars for High-performance Speech Recognition Copyright 2011 Chant Inc. All rights reserved. Chant, SpeechKit, Getting the World Talking with Technology, talking man, and headset are trademarks
More informationConsumers want conversational virtual assistants.
Consumers want conversational virtual assistants. Research Now study reveals insights into virtual assistants usage and preferences. 1 Table of contents 1 Survey says... / p2 2 Speak easy: how conversational
More informationModern foreign languages
Modern foreign languages Programme of study for key stage 3 and attainment targets (This is an extract from The National Curriculum 2007) Crown copyright 2007 Qualifications and Curriculum Authority 2007
More informationDevelop Software that Speaks and Listens
Develop Software that Speaks and Listens Copyright 2011 Chant Inc. All rights reserved. Chant, SpeechKit, Getting the World Talking with Technology, talking man, and headset are trademarks or registered
More informationGCE APPLIED ICT A2 COURSEWORK TIPS
GCE APPLIED ICT A2 COURSEWORK TIPS COURSEWORK TIPS A2 GCE APPLIED ICT If you are studying for the six-unit GCE Single Award or the twelve-unit Double Award, then you may study some of the following coursework
More informationGetting started with 2c8 plugin for Microsoft Sharepoint Server 2010
Getting started with 2c8 plugin for Microsoft Sharepoint Server 2010... 1 Introduction... 1 Adding the Content Management Interoperability Services (CMIS) connector... 1 Installing the SharePoint 2010
More informationUser Guide & Implementation Guidelines for using the Transaction Delivery Agent (TDA) 3.0
Using SWIFTNet to communicate with the Deriv/SERV system at DTCC User Guide & Implementation Guidelines for using the Transaction Delivery Agent (TDA) 3.0 Version 2.0 August 2009 Deriv/SERV through SWIFTNet
More information14.1. bs^ir^qfkd=obcib`qflk= Ñçê=emI=rkfuI=~åÇ=léÉåsjp=eçëíë
14.1 bs^ir^qfkd=obcib`qflk= Ñçê=emI=rkfuI=~åÇ=léÉåsjp=eçëíë bî~äì~íáåö=oéñäéåíáçå=ñçê=emi=rkfui=~åç=lééåsjp=eçëíë This guide walks you quickly through key Reflection features. It covers: Getting Connected
More informationRequirements Definition of Communication Platform
Requirements Definition of Communication Platform Workpackage WP5 Task T5.2 Document type Deliverable D5.2 Title Requirements Definition of Communication Platform Subtitle CommRob Project Authors TUW with
More informationXTM Drupal Connector. A Translation Management Tool Plugin
XTM Drupal Connector A Translation Management Tool Plugin Published by XTM International Ltd. Copyright XTM International Ltd. All rights reserved. No part of this publication may be reproduced or transmitted
More informationUsing the VEX Cortex with ROBOTC
Using the VEX Cortex with ROBOTC This document is a guide for downloading and running programs on the VEX Cortex using ROBOTC for Cortex 2.3 BETA. It is broken into four sections: Prerequisites, Downloading
More informationDragon speech recognition Nuance Dragon NaturallySpeaking 13 comparison by product. Feature matrix. Professional Premium Home.
matrix Recognition accuracy Recognition speed System configuration Turns your voice into text with up to 99% accuracy New - Up to a 15% improvement to out-of-the-box accuracy compared to Dragon version
More informationVoice Driven Animation System
Voice Driven Animation System Zhijin Wang Department of Computer Science University of British Columbia Abstract The goal of this term project is to develop a voice driven animation system that could take
More informationCall Recorder Oygo Manual. Version 1.001.11
Call Recorder Oygo Manual Version 1.001.11 Contents 1 Introduction...4 2 Getting started...5 2.1 Hardware installation...5 2.2 Software installation...6 2.2.1 Software configuration... 7 3 Options menu...8
More informationMore power for your processes
>> ELO business solution for ERP applications More power for your processes - the integration module for ERP-oriented process solutions The (BLP) enables the efficient linking of different ERP systems
More informationIn depth study - Dev teams tooling
In depth study - Dev teams tooling Max Åberg mat09mab@ Jacob Burenstam Linder ada09jbu@ Desired feedback Structure of paper Problem description Inconsistencies git story explanation 1 Introduction Hypotheses
More informationNick Ashley TOOLS. The following table lists some additional and possibly more unusual tools used in this paper.
TAKING CONTROL OF YOUR DATABASE DEVELOPMENT Nick Ashley While language-oriented toolsets become more advanced the range of development and deployment tools for databases remains primitive. How often is
More informationAbstract. Avaya Solution & Interoperability Test Lab
Avaya Solution & Interoperability Test Lab Application Notes for LumenVox Automated Speech Recognizer, LumenVox Text-to-Speech Server and Call Progress Analysis with Avaya Aura Experience Portal Issue
More informationContinuous Integration and Automatic Testing for the FLUKA release using Jenkins (and Docker)
Continuous Integration and Automatic Testing for the FLUKA release using Jenkins (and Docker) Vittorio BOCCONE DECTRIS Ltd. 5405 Baden-Daettwil Switzerland www.dectris.com Definitions Continuous Integration
More informationIBM Endpoint Manager Version 9.1. Patch Management for Red Hat Enterprise Linux User's Guide
IBM Endpoint Manager Version 9.1 Patch Management for Red Hat Enterprise Linux User's Guide IBM Endpoint Manager Version 9.1 Patch Management for Red Hat Enterprise Linux User's Guide Note Before using
More informationStandard Languages for Developing Multimodal Applications
Standard Languages for Developing Multimodal Applications James A. Larson Intel Corporation 16055 SW Walker Rd, #402, Beaverton, OR 97006 USA jim@larson-tech.com Abstract The World Wide Web Consortium
More informationIndustry Guidelines on Captioning Television Programs 1 Introduction
Industry Guidelines on Captioning Television Programs 1 Introduction These guidelines address the quality of closed captions on television programs by setting a benchmark for best practice. The guideline
More informationCDC UNIFIED PROCESS PRACTICES GUIDE
Document Purpose The purpose of this document is to provide guidance on the practice of Requirements Management and to describe the practice overview, requirements, best practices, activities, and key
More informationAPPLICATION CASE OF THE END-TO-END RELAY TESTING USING GPS-SYNCHRONIZED SECONDARY INJECTION IN COMMUNICATION BASED PROTECTION SCHEMES
APPLICATION CASE OF THE END-TO-END RELAY TESTING USING GPS-SYNCHRONIZED SECONDARY INJECTION IN COMMUNICATION BASED PROTECTION SCHEMES J. Ariza G. Ibarra Megger, USA CFE, Mexico Abstract This paper reviews
More informationRobotics and Automation Blueprint
Robotics and Automation Blueprint This Blueprint contains the subject matter content of this Skill Connect Assessment. This Blueprint does NOT contain the information one would need to fully prepare for
More informationConstruct User Guide
Construct User Guide Contents Contents 1 1 Introduction 2 1.1 Construct Features..................................... 2 1.2 Speech Licenses....................................... 3 2 Scenario Management
More informationVOICE RECOGNITION KIT USING HM2007. Speech Recognition System. Features. Specification. Applications
VOICE RECOGNITION KIT USING HM2007 Introduction Speech Recognition System The speech recognition system is a completely assembled and easy to use programmable speech recognition circuit. Programmable,
More informationHow Silk Central brings flexibility to agile development
How Silk Central brings flexibility to agile development The name agile development is perhaps slightly misleading as it is by its very nature, a carefully structured environment of rigorous procedures.
More informationhttp://www.softwaretestinghelp.com/ Test Plan Template: (Name of the Product) Prepared by: (Names of Preparers) (Date) TABLE OF CONTENTS
http://www.softwaretestinghelp.com/ Test Plan Template: (Name of the Product) Prepared by: (Names of Preparers) (Date) TABLE OF CONTENTS 1.0 INTRODUCTION 2.0 OBJECTIVES AND TASKS 2.1 Objectives 2.2 Tasks
More informationDEALMAKER: An Agent for Selecting Sources of Supply To Fill Orders
DEALMAKER: An Agent for Selecting Sources of Supply To Fill Orders Pedro Szekely, Bob Neches, David Benjamin, Jinbo Chen and Craig Milo Rogers USC/Information Sciences Institute Marina del Rey, CA 90292
More informationInformation extraction from online XML-encoded documents
Information extraction from online XML-encoded documents From: AAAI Technical Report WS-98-14. Compilation copyright 1998, AAAI (www.aaai.org). All rights reserved. Patricia Lutsky ArborText, Inc. 1000
More informationBatch Scanning. 70 Royal Little Drive. Providence, RI 02904. Copyright 2002-2011 Ingenix. All rights reserved.
70 Royal Little Drive Providence, RI 02904 Copyright 2002-2011 Ingenix. All rights reserved. Updated: December 13, 2011 Table of Contents 1 Batch Scanning... 1 1.1 Installing the CareTracker Client...
More informationUsing Microsoft Visual Studio 2010. API Reference
2010 API Reference Published: 2014-02-19 SWD-20140219103929387 Contents 1... 4 Key features of the Visual Studio plug-in... 4 Get started...5 Request a vendor account... 5 Get code signing and debug token
More informationDownload Check My Words from: http://mywords.ust.hk/cmw/
Grammar Checking Press the button on the Check My Words toolbar to see what common errors learners make with a word and to see all members of the word family. Press the Check button to check for common
More informationThe Welcome screen displays each time you log on to PaymentNet; it serves as your starting point or home screen.
PaymentNet Cardholder Quick Reference Card Corporate Card ffwelcome to PaymentNet The Welcome screen displays each time you log on to PaymentNet; it serves as your starting point or home screen. PaymentNet
More informationHow to Extend a Fiori Application: Purchase Order Approval
SAP Web IDE How-To Guide Provided by Customer Experience Group How to Extend a Fiori Application: Purchase Order Approval Applicable Releases: SAP Web IDE 1.4 Version 2.0 - October 2014 Document History
More information2011 Springer-Verlag Berlin Heidelberg
This document is published in: Novais, P. et al. (eds.) (2011). Ambient Intelligence - Software and Applications: 2nd International Symposium on Ambient Intelligence (ISAmI 2011). (Advances in Intelligent
More informationIBM Campaign Version-independent Integration with IBM Engage Version 1 Release 3 April 8, 2016. Integration Guide IBM
IBM Campaign Version-independent Integration with IBM Engage Version 1 Release 3 April 8, 2016 Integration Guide IBM Note Before using this information and the product it supports, read the information
More informationWeb page creation using VoiceXML as Slot filling task. Ravi M H
Web page creation using VoiceXML as Slot filling task Ravi M H Agenda > Voice XML > Slot filling task > Web page creation for user profile > Applications > Results and statistics > Language model > Future
More informationOptimization: Continuous Portfolio Allocation
Optimization: Continuous Portfolio Allocation Short Examples Series using Risk Simulator For more information please visit: www.realoptionsvaluation.com or contact us at: admin@realoptionsvaluation.com
More informationWEBSITE DESIGN. RWebsite Design OVERVIEW CHALLENGE ELIGIBILITY TIME LIMITS
WEBSITE DESIGN OVERVIEW Participants are required to design, build and launch a World Wide Web site that features the team s ability to research topics pertaining to technology. Pre-conference semifinalists
More informationRedpaper Axel Buecker Kenny Chow Jenny Wong
Redpaper Axel Buecker Kenny Chow Jenny Wong A Guide to Authentication Services in IBM Security Access Manager for Enterprise Single Sign-On Introduction IBM Security Access Manager for Enterprise Single
More informationCS4025: Pragmatics. Resolving referring Expressions Interpreting intention in dialogue Conversational Implicature
CS4025: Pragmatics Resolving referring Expressions Interpreting intention in dialogue Conversational Implicature For more info: J&M, chap 18,19 in 1 st ed; 21,24 in 2 nd Computing Science, University of
More informationComparative Error Analysis of Dialog State Tracking
Comparative Error Analysis of Dialog State Tracking Ronnie W. Smith Department of Computer Science East Carolina University Greenville, North Carolina, 27834 rws@cs.ecu.edu Abstract A primary motivation
More informationMicrosoft Office Access 2007 which I refer to as Access throughout this book
Chapter 1 Getting Started with Access In This Chapter What is a database? Opening Access Checking out the Access interface Exploring Office Online Finding help on Access topics Microsoft Office Access
More informationEasyC. Programming Tips
EasyC Programming Tips PART 1: EASYC PROGRAMMING ENVIRONMENT The EasyC package is an integrated development environment for creating C Programs and loading them to run on the Vex Control System. Its Opening
More informationPart I. Introduction
Part I. Introduction In the development of modern vehicles, the infotainment system [54] belongs to the innovative area. In comparison to the conventional areas such as the motor, body construction and
More informationFAQs Frequently Asked Questions
FAQs Frequently Asked Questions BURLINGTON ENGLISH Table of Contents Page installation Q1 What are the minimum system requirements for installing BurlingtonEnglish? 4 Q2 What are the installation instructions
More informationSilkTest Workbench. Getting Started with.net Scripts
SilkTest Workbench Getting Started with.net Scripts Borland Software Corporation 4 Hutton Centre Dr., Suite 900 Santa Ana, CA 92707 Copyright 2010 Micro Focus (IP) Limited. All Rights Reserved. SilkTest
More informationBanner Workflow. Creating FOAPAL Requests
Banner Workflow Creating FOAPAL Requests Workflow s automated processes allow business events to trigger user emails, automated activities, and notifications. Workflow s automated approval notifications
More informationOperational Decision Manager Worklight Integration
Copyright IBM Corporation 2013 All rights reserved IBM Operational Decision Manager V8.5 Lab exercise Operational Decision Manager Worklight Integration Integrate dynamic business rules into a Worklight
More informationTEST AUTOMATION FRAMEWORK
TEST AUTOMATION FRAMEWORK Twister Topics Quick introduction Use cases High Level Description Benefits Next steps Twister How to get Twister is an open source test automation framework. The code, user guide
More informationSOFTWARE TESTING TRAINING COURSES CONTENTS
SOFTWARE TESTING TRAINING COURSES CONTENTS 1 Unit I Description Objectves Duration Contents Software Testing Fundamentals and Best Practices This training course will give basic understanding on software
More informationUsing the vcenter Orchestrator Plug-In for vsphere Auto Deploy 1.0
Using the vcenter Orchestrator Plug-In for vsphere Auto Deploy 1.0 vcenter Orchestrator 4.2 This document supports the version of each product listed and supports all subsequent versions until the document
More informationEMC Documentum Content Services for SAP Repository Manager
EMC Documentum Content Services for SAP Repository Manager Version 6.0 Installation Guide P/N 300 005 500 Rev A01 EMC Corporation Corporate Headquarters: Hopkinton, MA 01748 9103 1 508 435 1000 www.emc.com
More informationSoMA. Automated testing system of camera algorithms. Sofica Ltd
SoMA Automated testing system of camera algorithms Sofica Ltd February 2012 2 Table of Contents Automated Testing for Camera Algorithms 3 Camera Algorithms 3 Automated Test 4 Testing 6 API Testing 6 Functional
More informationMore power for your processes ELO Business Logic Provider for Microsoft Dynamics NAV
>> ELO Business Logic Provider for ELO Business Solution for Microsoft Dynamics NAV More power for your processes ELO Business Logic Provider for Microsoft Dynamics NAV The ELO Business Logic Provider
More informationSchool of Computer Science
School of Computer Science Computer Science - Honours Level - 2014/15 October 2014 General degree students wishing to enter 3000- level modules and non- graduating students wishing to enter 3000- level
More informationCreating a Virtual Neighbor
Creating a Virtual Neighbor Carina Corbin, Fabrizio Morbini, and David Traum Abstract We present the first version of our Virtual Neighbor, who can talk with users about people employed in the same institution.
More informationWriting The Business Case for Automated Software Testing and Test Management Tools
Writing The Business Case for Automated Software Testing and Test Management Tools How to successfully research, plan and present a convincing business case that will justify the budget and resources you
More informationChapter 27 Web Server
Chapter 27 Web Server The HCA Web Server is an application installed when HCA installs that allows HCA to generate HTML pages from browser requests. By using a network and a browser, you can access your
More informationDescription: Objective: Upon completing this course, the learner will be able to meet these overall objectives:
Course: Deploying Cisco Unified Contact Center Express Software v9.0 Duration: 5 Day Hands-On Lab & Lecture Course Price: $ 3,695.00 Learning Credits: 37 Description: Deploying Cisco Unified Contact Center
More informationCommon European Framework of Reference for Languages: learning, teaching, assessment. Table 1. Common Reference Levels: global scale
Common European Framework of Reference for Languages: learning, teaching, assessment Table 1. Common Reference Levels: global scale C2 Can understand with ease virtually everything heard or read. Can summarise
More informationLarge Scale Systems Design G52LSS
G52LSS Refine Requirements Lecture 13 Use Case Analysis Use Case Diagrams and Use Cases Steps of Use Case Analysis Example: University Registration System Learning outcomes: understand the importance of
More informationSpecial Topics in Computer Science
Special Topics in Computer Science NLP in a Nutshell CS492B Spring Semester 2009 Jong C. Park Computer Science Department Korea Advanced Institute of Science and Technology INTRODUCTION Jong C. Park, CS
More informationSofware Requirements Engineeing
Sofware Requirements Engineeing Three main tasks in RE: 1 Elicit find out what the customers really want. Identify stakeholders, their goals and viewpoints. 2 Document write it down (). Understandable
More informationUninstallation Guide Funding Information System (FIS)
(FIS) Document Details Document Type: Uninstallation Guide Creation Date: 05/03/2014 Document Version: 1.0 Change to this document Version Date Changes made V1.0 05/03/2014 Initial version to support the
More informationApplication Notes for Speech Technology Center Voice Navigator 8 with Avaya Aura Experience Portal 7.0.1 - Issue 1.0
Avaya Solution & Interoperability Test Lab Application Notes for Speech Technology Center Voice Navigator 8 with Avaya Aura Experience Portal 7.0.1 - Issue 1.0 Abstract These application notes describe
More informationZabbix 1.8 Network Monitoring
Zabbix 1.8 Network Monitoring Monitor your network's hardware, servers, and web performance effectively and efficiently Rihards Olups - PUBLISHING - 1 BIRMINGHAM - MUMBAI Preface 1 Chapter 1: Getting Started
More informationZoom Plug-ins for Adobe
= Zoom Plug-ins for Adobe User Guide Copyright 2010 Evolphin Software. All rights reserved. Table of Contents Table of Contents Chapter 1 Preface... 4 1.1 Document Revision... 4 1.2 Audience... 4 1.3 Pre-requisite...
More informationIntegrating with BarTender Integration Builder
Integrating with BarTender Integration Builder WHITE PAPER Contents Overview 3 Understanding BarTender's Native Integration Platform 4 Integration Builder 4 Administration Console 5 BarTender Integration
More informationCustom Software Development Portfolio. Innovation Collaboration Evolution Results
Phonecierge SOFTEL Verifier First Responder Innovation Collaboration Evolution Results Bespoke Custom Software Portfolio SOFTEL Communications Complete Customized Software Services Designing software that
More informationBazaarvoice SEO implementation guide
Bazaarvoice SEO implementation guide TOC Contents Bazaarvoice SEO...3 The content you see is not what search engines see...3 SEO best practices for your review pages...3 Implement Bazaarvoice SEO...4 Verify
More informationIVR CRM Integration. Migrating the Call Center from Cost Center to Profit. Definitions. Rod Arends Cheryl Yaeger BenchMark Consulting International
IVR CRM Integration Migrating the Call Center from Cost Center to Profit Rod Arends Cheryl Yaeger BenchMark Consulting International Today, more institutions are seeking ways to change their call center
More informationSubversion Integration
Subversion Integration With the popular Subversion Source Control Management tool, users will find a flexible interface to integrate with their ExtraView bug-tracking system. Copyright 2008 ExtraView Corporation
More informationStep 1: Select the Start Menu, then Control Panel.
Part of the Adobe Connect 9 software includes functionality to support full audio in addition to chat areas, shared spaces, and video. The technology that makes this possible is Voice- Over-IP (VOIP).
More informationLab 0 (Setting up your Development Environment) Week 1
ECE155: Engineering Design with Embedded Systems Winter 2013 Lab 0 (Setting up your Development Environment) Week 1 Prepared by Kirill Morozov version 1.2 1 Objectives In this lab, you ll familiarize yourself
More informationAutomatic promotion and versioning with Oracle Data Integrator 12c
Automatic promotion and versioning with Oracle Data Integrator 12c Jérôme FRANÇOISSE Rittman Mead United Kingdom Keywords: Oracle Data Integrator, ODI, Lifecycle, export, import, smart export, smart import,
More informationNatural Language Updates to Databases through Dialogue
Natural Language Updates to Databases through Dialogue Michael Minock Department of Computing Science Umeå University, Sweden Abstract. This paper reopens the long dormant topic of natural language updates
More information