A Speech-Enabled Interface Agent for Static Html Web Pages
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General Subtitling FAQ's
General Subtitling FAQ’s What's the difference between open and closed captions? Open captions are sometimes referred to as ‘burnt-in’ or ‘in-vision’ subtitles. They are generally encoded as a permanent part of the video image. Closed captions is a generic term for subtitles that are viewer-selectable and is generally used for subtitles that are transmitted as a discrete data stream in the VBI then decoded and displayed as text by the TV receiver e.g. Line 21 Closed Captioning system in the USA, and Teletext subtitles, using line 335, in Europe. What's the difference between "live" and "offline" subtitling? Live subtitling is the real-time captioning of live programmes, typically news and sports. This is achieved by using either Speech Recognition systems or Stenographic (Steno) keyboards. Offline subtitling is created by viewing previously recorded material. Typically this produces better results because the subtitle author can ensure they produce An accurate translation/transcription with no spelling mistakes Subtitles are timed to coincide precisely with the dialogue Subtitles are positioned to avoid obscuring other important onscreen features Which Speech Recognition packages do Starfish support? Starfish supports Speech Recognition packages from IBM and Dragon and other suppliers who confirm to the Microsoft Speech API. The choice of the software is usually dictated by the availability of a specific language. Starfish Technologies Ltd FAQ General FAQ’s What's the difference between subtitling and captioning? The use of these terms varies in different parts of the world. Subtitling often refers to the technique of using open captions for language translation of foreign programmes. -
Speech Recognition Technology for Disabilities Education
J. EDUCATIONAL TECHNOLOGY SYSTEMS, Vol. 33(2) 173-184, 2004-2005 SPEECH RECOGNITION TECHNOLOGY FOR DISABILITIES EDUCATION K. WENDY TANG GILBERT ENG RIDHA KAMOUA WEI CHERN CHU VICTOR SUTAN GUOFENG HOU OMER FAROOQ Stony Brook University, New York ABSTRACT Speech recognition is an alternative to traditional methods of interacting with a computer, such as textual input through a keyboard. An effective system can replace or reduce the reliability on standard keyboard and mouse input. This can especially assist dyslexic students who have problems with character or word use and manipulation in a textual form; and students with physical disabilities that affect their data entry or ability to read, and therefore to check, what they have entered. In this article, we summarize the current state of available speech recognition technologies and describe a student project that integrates speech recognition technologies with Personal Digital Assistants to provide a cost-effective and portable health monitoring system for people with disabilities. We are hopeful that this project may inspire more student-led projects for disabilities education. 1. INTRODUCTION Speech recognition allows “hands-free” control of various electronic devices. It is particularly advantageous to physically disabled persons. Speech recognition can be used in computers to control the system, launch applications, and create “print-ready” dictation and thus provide easy access to persons with hearing or 173 Ó 2004, Baywood Publishing Co., Inc. 174 / TANG ET AL. vision impairments. For example, a hearing impaired person can use a microphone to capture another’s speech and then use speech recognition technologies to convert the speech to text. -
Microsoft Patches Were Evaluated up to and Including CVE-2020-1587
Honeywell Commercial Security 2700 Blankenbaker Pkwy, Suite 150 Louisville, KY 40299 Phone: 1-502-297-5700 Phone: 1-800-323-4576 Fax: 1-502-666-7021 https://www.security.honeywell.com The purpose of this document is to identify the patches that have been delivered by Microsoft® which have been tested against Pro-Watch. All the below listed patches have been tested against the current shipping version of Pro-Watch with no adverse effects being observed. Microsoft Patches were evaluated up to and including CVE-2020-1587. Patches not listed below are not applicable to a Pro-Watch system. 2020 – Microsoft® Patches Tested with Pro-Watch CVE-2020-1587 Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability CVE-2020-1584 Windows dnsrslvr.dll Elevation of Privilege Vulnerability CVE-2020-1579 Windows Function Discovery SSDP Provider Elevation of Privilege Vulnerability CVE-2020-1578 Windows Kernel Information Disclosure Vulnerability CVE-2020-1577 DirectWrite Information Disclosure Vulnerability CVE-2020-1570 Scripting Engine Memory Corruption Vulnerability CVE-2020-1569 Microsoft Edge Memory Corruption Vulnerability CVE-2020-1568 Microsoft Edge PDF Remote Code Execution Vulnerability CVE-2020-1567 MSHTML Engine Remote Code Execution Vulnerability CVE-2020-1566 Windows Kernel Elevation of Privilege Vulnerability CVE-2020-1565 Windows Elevation of Privilege Vulnerability CVE-2020-1564 Jet Database Engine Remote Code Execution Vulnerability CVE-2020-1562 Microsoft Graphics Components Remote Code Execution Vulnerability -
Automated Regression Testing Approach to Expansion and Refinement of Speech Recognition Grammars
University of Central Florida STARS Electronic Theses and Dissertations, 2004-2019 2008 Automated Regression Testing Approach To Expansion And Refinement Of Speech Recognition Grammars Raul Dookhoo University of Central Florida Part of the Computer Sciences Commons, and the Engineering Commons Find similar works at: https://stars.library.ucf.edu/etd University of Central Florida Libraries http://library.ucf.edu This Masters Thesis (Open Access) is brought to you for free and open access by STARS. It has been accepted for inclusion in Electronic Theses and Dissertations, 2004-2019 by an authorized administrator of STARS. For more information, please contact [email protected]. STARS Citation Dookhoo, Raul, "Automated Regression Testing Approach To Expansion And Refinement Of Speech Recognition Grammars" (2008). Electronic Theses and Dissertations, 2004-2019. 3503. https://stars.library.ucf.edu/etd/3503 AUTOMATED REGRESSION TESTING APPROACH TO EXPANSION AND REFINEMENT OF SPEECH RECOGNITION GRAMMARS by RAUL AVINASH DOOKHOO B.S. University of Guyana, 2004 A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the School of Electrical Engineering and Computer Science in the College of Engineering and Computer Science at the University of Central Florida Orlando, Florida Fall Term 2008 © 2008 Raul Avinash Dookhoo ii ABSTRACT This thesis describes an approach to automated regression testing for speech recognition grammars. A prototype Audio Regression Tester called ART has been developed using Microsoft’s Speech API and C#. ART allows a user to perform any of three tasks: automatically generate a new XML-based grammar file from standardized SQL database entries, record and cross-reference audio files for use by an underlying speech recognition engine, and perform regression tests with the aid of an oracle grammar. -
Speech@Home: an Exploratory Study
Speech@Home: An Exploratory Study A.J. Brush Paul Johns Abstract Microsoft Research Microsoft Research To understand how people might use a speech dialog 1 Microsoft Way 1 Microsoft Way system in the public areas of their homes, we Redmond, WA 98052 USA Redmond, WA 98052 USA conducted an exploratory field study in six households. [email protected] [email protected] For two weeks each household used a system that logged motion and usage data, recorded speech diary Kori Inkpen Brian Meyers entries and used Experience Sampling Methodology Microsoft Research Microsoft Research (ESM) to prompt participants for additional examples of 1 Microsoft Way 1 Microsoft Way speech commands. The results demonstrated our Redmond, WA 98052 USA Redmond, WA 98052 USA participants’ interest in speech interaction at home, in [email protected] [email protected] particular for web browsing, calendaring and email tasks, although there are still many technical challenges that need to be overcome. More generally, our study suggests the value of using speech to enable a wide range of interactions. Keywords Speech, home technology, diary study, domestic ACM Classification Keywords H.5.2 User Interfaces: Voice I/O. General Terms Human Factors, Experimentation Copyright is held by the author/owner(s). Introduction CHI 2011, May 7–12, 2011, Vancouver, BC, Canada. The potential for using speech in home environments ACM 978-1-4503-0268-5/11/05. has long been recognized. Smart home research has suggested using speech dialog systems for controlling . home infrastructure (e.g. [5, 8, 10, 12]), and a variety We conducted a two week exploratory speech diary of novel home applications use speech interfaces, such study in six households to understand whether or not as cooking support systems [2] and the Nursebot speech interaction was desirable, and, if so, what types personal robotic assistant for the elderly [14]. -
Personalized Speech Translation Using Google Speech API and Microsoft Translation API
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 07 Issue: 05 | May 2020 www.irjet.net p-ISSN: 2395-0072 Personalized Speech Translation using Google Speech API and Microsoft Translation API Sagar Nimbalkar1, Tekendra Baghele2, Shaifullah Quraishi3, Sayali Mahalle4, Monali Junghare5 1Student, Dept. of Computer Science and Engineering, Guru Nanak Institute of Technology, Maharashtra, India 2Student, Dept. of Computer Science and Engineering, Guru Nanak Institute of Technology, Maharashtra, India 3Student, Dept. of Computer Science and Engineering, Guru Nanak Institute of Technology, Maharashtra, India 4Student, Dept. of Computer Science and Engineering, Guru Nanak Institute of Technology, Maharashtra, India 5Student, Dept. of Computer Science and Engineering, Guru Nanak Institute of Technology, Maharashtra, India ---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Speech translation innovation empowers inherent in globalization.[6] Speech to speech translation speakers of various language to impart. It subsequently is of systems are often used for applications in a specific situation, enormous estimation of mankind as far as science, cross- such as supporting conversations in non-native languages. cultural exchange and worldwide trade. Henceforth we The demand for trans-lingual conversations, triggered by IT proposed a that can connect this language hindrance. In this technologies has boosted research activities on Speech to paper we propose a personalized speech translation system speech technology. Most of them were consist of three using Google Speech API and Microsoft Translation API. modules namely speech 7recognition, machine translation Personalized in the sense that user have the choice to select and text to speech translation. Speech recognition is an the languages which will be used by the system as a input and interdisciplinary sub-field of computational linguistics that a output. -
Automated Scanning Vulnerability Report
Automated Scanning Vulnerability Report − Classified − Automated Scanning Vulnerability Report Performed by Beyond Security's Automated Scanning Host/s Tested: 192.168.4.122 Report Generated: 05 Jun 2007 13:31 Table of Contents Introduction Host Information Executive Summary Possible Vulnerabilities What Next? Introduction We have scanned your host/s 192.168.4.122 for 4345 known security holes. This scan took place on 5 Jun 2007 13:31 and took 0 hours and 5 minutes to complete. The 'Possible Vulnerabilities' section of this report lists security holes found during the scan, sorted by risk level. Note that some of these reported vulnerabilities could be 'false alarms' since the hole is never actually exploited during the scan. Some of what we found is purely informational; It will not help an attacker to gain access, but it will give him information about the local network or hosts. These results appear in the 'Low Risk / Intelligence Gathering' section. The last section of this report ('Security Tests') lists the security tests that were performed in this scan by category of vulnerability. 1/44 Automated Scanning Vulnerability Report Executive Summary Learn more about how vulnerabilities are classified Vulnerabilities by Host and Risk Level Total IP Address High Medium Low Vulnerabilities 192.168.4.122 113 33 60 20 Vulnerabilities By Risk Level Top Vulnerabilities By Host 2/44 Automated Scanning Vulnerability Report Vulnerabilities by Service and Risk Level Service Total High Risk Medium Risk Low Risk Vulnerabilities netbios−ns (137/udp) 1 0 0 1 microsoft−ds 101 33 58 10 (445/tcp) general/tcp 8 0 1 7 ntp (123/udp) 1 0 0 1 netbios−ssn 1 0 1 0 (139/tcp) general/icmp 1 0 0 1 Top Vulnerabilities By Service Top Vulnerable Services 3/44 Automated Scanning Vulnerability Report Possible Vulnerabilities High Medium Low Risk Factor: High A Total of 33 High Risk Vulnerability/ies was/were discovered. -
License Clerks
Paralegals and Legal Assistants License Clerks TORQ Analysis of Paralegals and Legal Assistants to License Clerks ANALYSIS INPUT Transfer Title O*NET Filters Paralegals and Legal Importance LeveL: Weight: From Title: 23-2011.00 Abilities: Assistants 50 1 Importance LeveL: Weight: To Title: License Clerks 43-4031.03 Skills: 69 1 Labor Market Importance Level: Weight: Maine Statewide Knowledge: Area: 69 1 TORQ RESULTS Grand TORQ: 93 Ability TORQ Skills TORQ Knowledge TORQ Level Level Level 96 91 91 Gaps To Narrow if Possible Upgrade These Skills Knowledge to Add Ability Level Gap Impt Skill Level Gap Impt Knowledge Level Gap Impt No Critical Gaps Recorded! Speaking 76 13 83 Customer and Personal 88 32 73 Service Transportation 12 2 76 LEVEL and IMPT (IMPORTANCE) refer to the Target License Clerks. GAP refers to level difference between Paralegals and Legal Assistants and License Clerks. ASK ANALYSIS Ability Level Comparison - Abilities with importance scores over 50 Paralegals and Legal Description Assistants License Clerks Importance Oral Comprehension 67 51 75 Oral Expression 66 53 75 Written Comprehension 69 50 72 Written Expression 64 48 65 Speech Recognition 59 41 62 Speech Clarity 53 44 62 Near Vision 71 51 59 Problem Sensitivity 51 42 53 Deductive Reasoning 59 44 50 Inductive Reasoning 64 42 50 Information Ordering 55 44 50 Jul-07-2009 - TORQ Analysis Page 1 of 53. Copyright 2009. Workforce Associates, Inc. Paralegals and Legal Assistants License Clerks Selective Attention 42 39 50 Skill Level Comparison - Abilities with importance -
Automatic Speech Recognition Using Limited Vocabulary: a Survey
Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000. Digital Object Identifier 10.1109/ACCESS.xxxx.DOI Automatic Speech Recognition using limited vocabulary: A survey JEAN LOUIS K. E. FENDJI1, (Member, IEEE), DIANE M. TALA2, BLAISE O. YENKE1, (Member, IEEE), and MARCELLIN ATEMKENG3 1Department of Computer Engineering, University Institute of Technology, University of Ngaoundere, 455 Ngaoundere, Cameroon (e-mail: [email protected], [email protected]) 2Department Mathematics and Computer Science, Faculty of Science, University of Ngaoundere, 454 Ngaoundere, Cameroon (e-mail: [email protected]) 3Department of Mathematics, Rhodes University, Grahamstown 6140, South Africa (e-mail: [email protected]) Corresponding author: Jean Louis K.E. Fendji (e-mail: lfendji@ gmail.com), Marcellin Atemkeng (e-mail: [email protected]). ABSTRACT Automatic Speech Recognition (ASR) is an active field of research due to its huge number of applications and the proliferation of interfaces or computing devices that can support speech processing. But the bulk of applications is based on well-resourced languages that overshadow under-resourced ones. Yet ASR represents an undeniable mean to promote such languages, especially when design human-to-human or human-to-machine systems involving illiterate people. An approach to design an ASR system targeting under-resourced languages is to start with a limited vocabulary. ASR using a limited vocabulary is a subset of the speech recognition problem that focuses on the recognition of a small number of words or sentences. This paper aims to provide a comprehensive view of mechanisms behind ASR systems as well as techniques, tools, projects, recent contributions, and possibly future directions in ASR using a limited vocabulary. -
Merlin Programmer for Kids Is a Simple Program to Help Kids, Ages 5
Merlin Programmer for Kids is a simple program to help kids, ages 5 - 8 (ages prior to their moving on to more advanced languages such as Scratch), learn about the concept of sequential programming by allowing them to make Merlin or any of the other Microsoft Agent characters perform actions, move, speak, listen for and make sounds in a predetermined manner. They will learn about do loops, conditional program continuation based on time, key strokes, spoken words, and more! I wrote it in 2003 for my twins, Tommy and Betsy, ages 7 then (now 16!), and although they enjoyed it most for making the characters speak naughty words and make silly sounds, they learned more. I am sure your kids will have fun with it! It is a totally FREE program. This help file is intended for you, the parents. You must explain how this program works to your child, in a manner appropriate for his/her age. Obviously, the ability to understand and work with some features in this program will depend on your child’s age. Soon enough he/she will amaze you! In order to help you, several example scripts are included. Please read the sections on Menu and Programming. They are very short, but informative. Merlin Programmer for Kids home: SciSoft Company My home page: Yale University Ear Lab Installation New! After you download <Merlin Programmer for Kids v.5.5.8.msi> into a folder, double click on it and the Merlin program will be installed. A shortcut will be placed on the desktop , and when you first double click on it additional required components will be installed and then the program will start. -
Jira Evaluation License Key
Jira Evaluation License Key Constantine is uncropped and anastomosing abysmally as epigenetic Eugen hattings ablaze and asseverated winsomely. Keene is neverremonstrant pervading and erenowoccasion when unsensibly Job casserole as dotted his Clemente pastas. metathesizes trenchantly and disorients plum. Clustery and admired Horace Component or infer Label. You realize want some information on compulsory private platform to or kept back from our public one. Xray is connected machine without prejudice to jira evaluation license key? Microsoft Store is one ask their official Partners. Atlassian products and related services to their split and prospective customers. All other trademarks, servicemarks, and copyrights are the property with their respective owners. Gantt charts to solutions allowing to parsley custom reports of dumb kind. Since this communicate a trial license, this office an expected behavior. Thanks for intermediate feedback. Thanks for signing up! This article and free for everyone, thanks to Medium Members. These days, he writes news stories, columns, and reviews for CNET and other technology sites and publications. SOFTWARE PRODUCT identified above. For new installations, the wizard restricts the permissions that privileged accounts have attach the MSOL account after creating the MSOL account. You trust receive the license key once payment had been confirmed, the license key to be available for your license request ticket. No, children every Atlassian system lost one license can be applied. Atlassian software like Jira, Confluence or Bitbucket to your Marketplace Apps. This change helps you let more quickly delete your field domain names if your organization no longer uses the ashtray, or if you need simple use the month name today another Azure AD. -
A Voice Controlled E-Commerce Web Application
A Voice Controlled E-Commerce Web Application Mandeep Singh Kandhari Farhana Zulkernine Haruna Isah School of Computing School of Computing School of Computing Queen’s University Queen’s University, Queen’s University, Kingston, Canada Kingston, Canada Kingston, Canada [email protected] [email protected] [email protected] Abstract— Automatic voice-controlled systems have changed technology has made it possible to develop computer-based the way humans interact with a computer. Voice or speech reading coaches that listen to students, assess the performances, recognition systems allow a user to make a hands-free request to and provide immediate customized feedbacks [1]. the computer, which in turn processes the request and serves the user with appropriate responses. After years of research and The traditional methods of data entry (keyboard and mouse) developments in machine learning and artificial intelligence, today fail the accessibility requirements to support all types of users. voice-controlled technologies have become more efficient and are Therefore, it is necessary to develop systems and applications widely applied in many domains to enable and improve human-to- with enhanced usability for all users. Our research focuses on a human and human-to-computer interactions. The state-of-the-art cloud-based Speech Recognition System (SRS) for e-commerce e-commerce applications with the help of web technologies offer applications as a use case scenario. It is crucial for an interactive and user-friendly interfaces. However, there are some organization or company to design and develop a web instances where people, especially with visual disabilities, are not application that is informative, interactive and easily accessible able to fully experience the serviceability of such applications.