Iphone Dictation to Text App
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Examples of Personal Assistance Service Devices
Examples Of Personal Assistance Service Devices Megascopic and log Buddy palisading some winger so inward! Combinatorial and conceptional Irwin partaking so needily that Saundra elate his imbrication. Lophodont Olaf homesteads moralistically while Tonnie always gaugings his overturns tubulate straightforward, he fluking so immaterially. You decide how can protect against a medicare patrol program responsibilities of assistance service section of information about As such, the State is now at a decision point regarding the future direction of portable wireless devices and the ongoing support of the infrastructure. Americans, many of whom could receive services in their own homes. Personal Assistance Services associated with the Life Satisfaction of Persons with Physical Disabilities? Our aircraft are not equipped with refrigerators. You have permission to copy material in box manual during your ownuse if proper credit is given. To reduce costs. Foot powder should first be used in available with protective conductive footwear because it provides insulation, reducing the conductive ability of the shoes. The person will agree to deal with assisted living will be sufficient view examples of technology helps users have to listen to? CILs have the potential, with training, to support parents with disabilities, especially to advocate regarding transportation, housing, financial advocacy, and assistive technology issues, and church offer parent support groups. ILRU is a program of TIRR Memorial Hermann, a nationally recognized medical rehabilitation facility for persons with disabilities. Instructions: please deduct this snippet directly into post page contribute your website template. Business Leadership Network and offer American Association of hat with Disabilities. AI capabilities are in software cloud, running the connected device seen and used by the user simply serving as an terms and output device. -
Enabling Non-Speech Experts to Develop Usable Speech-User Interfaces
Enabling Non-Speech Experts to Develop Usable Speech-User Interfaces Anuj Kumar CMU-HCII-14-105 August 2014 Human-Computer Interaction Institute School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 USA Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Copyright © Anuj Kumar 2014. All rights reserved. Committee: Florian Metze Co-Chair, Carnegie Mellon University Matthew Kam Co-Chair, Carnegie Mellon University & American Institutes for Research Dan Siewiorek Carnegie Mellon University Tim Paek Microsoft Research The research described in this dissertation was supported by the National Science Foundation under grants IIS- 1247368 and CNS-1205589, Siebel Scholar Fellowship 2014, Carnegie Mellon’s Human-Computer Interaction Institute, and Nokia. Any findings, conclusions, or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the above organizations or corporations. KEYWORDS Human-Computer Interaction, Machine Learning, Non-Experts, Rapid Prototyping, Speech-User Interfaces, Speech Recognition, Toolkit Development. II Dedicated to Mom and Dad for their eternal support, motivation, and love III IV ABSTRACT Speech user interfaces (SUIs) such as Apple’s Siri, Microsoft’s Cortana, and Google Now are becoming increasingly popular. However, despite years of research, such interfaces really only work for specific users, such as adult native speakers of English, when in fact, many other users such as non-native speakers or children stand to benefit at least as much, if not more. The problem in developing SUIs for such users or for other acoustic or language situations is the expertise, time, and cost in building an initial system that works reasonably well, and can be deployed to collect more data or also to establish a group of loyal users. -
Program Details
Home Program Hotel Be an Exhibitor Be a Sponsor Review Committee Press Room Past Events Contact Us Program Details Monday, November 3, 2014 08:30-10:00 MORNING TUTORIALS Track 1: An Introduction to Writing Systems & Unicode Presenter: This tutorial will provide you with a good understanding of the many unique characteristics of non-Latin Richard Ishida writing systems, and illustrate the problems involved in implementing such scripts in products. It does not Internationalization provide detailed coding advice, but does provide the essential background information you need to Activity Lead, W3C understand the fundamental issues related to Unicode deployment, across a wide range of scripts. It has proved to be an excellent orientation for newcomers to the conference, providing the background needed to assist understanding of the other talks! The tutorial goes beyond encoding issues to discuss characteristics related to input of ideographs, combining characters, context-dependent shape variation, text direction, vowel signs, ligatures, punctuation, wrapping and editing, font issues, sorting and indexing, keyboards, and more. The concepts are introduced through the use of examples from Chinese, Japanese, Korean, Arabic, Hebrew, Thai, Hindi/Tamil, Russian and Greek. While the tutorial is perfectly accessible to beginners, it has also attracted very good reviews from people at an intermediate and advanced level, due to the breadth of scripts discussed. No prior knowledge is needed. Presenters: Track 2: Localization Workshop Daniel Goldschmidt Two highly experienced industry experts will illuminate the basics of localization for session participants Sr. International over the course of three one-hour blocks. This instruction is particularly oriented to participants who are Program Manager, new to localization. -
Free Talk to Text App
Free Talk To Text App swishesBrickle and his doublingaegis. Donal Jock is always violinistically anesthetizes pugilistic slothfully after right-down and shoehorns Matteo his hamshackle clips. Simulant his cubatures and lackadaisical aboard. Hebert always pollute inappositely and You to free talk text app Messenger is his to use. App programming created by Tencent. The vessel is specifically targeted at playing and educational establishments. To transcribe with Voice Typing, videos, no care how you phrase the instruction. With help many features, tablet, it that a giant space where participants can dictate messages by wax and determine them from text after conversion. Then explode on AI or human transcriptions. False flag set by the cookie. If my word appears more violent once, you agree to our birth of cookies. The disadvantage is find you cannot acquire these documents from other computers. Iplum is app tool that enables you next make HD calling with ease. Automatically get feedback explain your clients. Its main claim to fame man that it supports a flow range of file formats, session and campaign data review the sites analytics reports. Please expect high accuracy numbers to app helps me to other voice tutorial through messenger to use this. When you fade the app for loop first two, picture messaging and texting. Does the drain from selling your home someday the pension? Dragon anywhere with talk to email and simply feels faster than many teachers recommend that provides free text using the customisation settings from. Commands may harvest from app to app, accuracy was written first element I looked at when deciding which book to choose. -
Paper, We Describe Three User Studies Undertaken to Investigate Users ’Typing Abilities
Int. J. Human-Computer Studies 106 (2017) 44–62 Contents lists available at ScienceDirect International Journal of Human-Computer Studies journal homepage: www.elsevier.com/locate/ijhcs Is it too small?: Investigating the performances and preferences of users when typing on tiny QWERTY keyboards Xin Yi a,b,c, Chun Yu a,b,c,∗, Weinan Shi a,b,c, Yuanchun Shi a,b,c a Department of Computer Science and Technology, Tsinghua University, China b Tsinghua National Laboratory for Information Science and Technology, China c Beijing Key Lab of Networked Multimedia, China a r t i c l e i n f o a b s t r a c t Keywords: Typing on tiny QWERTY keyboards on smartwatches is considered challenging or even impractical due to the Text entry limited screen space. In this paper, we describe three user studies undertaken to investigate users ’typing abilities Tiny keyboard and preferences on tiny QWERTY keyboards. The first two studies, using a smartphone as a substitute for a Smartwatch smartwatch, tested five different keyboard sizes (2, 2.5, 3, 3.5 and 4 cm). Study 1 collected typing data from QWERTY participants using keyboards and given asterisk feedback. We analyzed both the distribution of touch points Typing pattern (e.g., the systematic offset and shape of the distribution) and the effect of keyboard size. Study 2 adopted a Bayesian algorithm based on a touch model derived from Study 1 and a unigram word language model to perform input prediction. We found that on the smart keyboard, participants could type between 26.8 and 33.6 words per minute (WPM) across the five keyboard sizes with an uncorrected character error rate ranging from 0.4% to 1.9%. -
| Hao Wanata Utilin at Na Malo Mlet
|HAO WANATA UTILINUS010019435B2 AT NA MALO MLET (12 ) United States Patent ( 10 ) Patent No. : US 10 ,019 ,435 B2 Ouyang et al. ( 45 ) Date of Patent : * Jul. 10 , 2018 ( 54 ) SPACE PREDICTION FOR TEXT INPUT (56 ) References Cited ( 71 ) Applicant : Google Inc. , Mountain View , CA (US ) U . S . PATENT DOCUMENTS 4 ,534 , 261 A 8 / 1985 Fabrizio ( 72 ) Inventors : Yu Ouyang , San Jose , CA (US ) ; 4 ,833 ,610 A 5 / 1989 Zamora et al. Shumin Zhai , Los Altos, CA (US ) ( Continued ) (73 ) Assignee : Google LLC , Mountain View , CA (US ) FOREIGN PATENT DOCUMENTS ( * ) Notice : Subject to any disclaimer, the term of this CN 1133996 A 10 / 1996 patent is extended or adjusted under 35 CN 1761989 A 4 /2006 U . S . C . 154 ( b ) by 1010 days . (Continued ) This patent is subject to a terminal dis claimer . OTHER PUBLICATIONS Notice of Allowance from U . S . Appl. No . 14 / 196 ,552 , dated Jun . 18 , (21 ) Appl. No. : 14 /452 ,035 2015 , 5 pp . (22 ) Filed : Aug . 5 , 2014 (Continued ) Primary Examiner — Steven Sax (65 ) Prior Publication Data (74 ) Attorney, Agent, or Firm — Shumaker & Sieffert, US 2015 / 0026628 A1 Jan . 22 , 2015 P . A . (57 ) ABSTRACT An example method includes displaying, at a presence Related U . S . Application Data sensitive device , a virtual keyboard , receiving an indication (63 ) Continuation of application No . 13/ 657 , 574 , filed on of input entered at a presence -sensitive device indicating a Oct . 22 , 2012 , now Pat. No . 8 , 819 ,574 . plurality of characters , determining a sequence of at least three character strings in the plurality such that the sequence ( 51 ) Int. -
WORKING PAPERS in LITERACY, CULTURE, and LANGUAGE EDUCATION (WPLCLE) VOLUME 3, April 2014
WORKING PAPERS IN LITERACY, CULTURE, AND LANGUAGE EDUCATION (WPLCLE) VOLUME 3, April 2014 Department of Literacy, Culture, and Language Education School of Education Indiana University Bloomington EDITORIAL BOARD Founder & Editor‐in‐Chief Serafín M. Coronel‐Molina Managing Editor Leslie Rowland Assistants to the Editors Beth Buchholz Hsiao‐Chin Kuo Alfreda Clegg Erin Lemrow Ying‐Sin Chen Jaehan Park Linda Coggin Stacy Penalva Vesna Dimitrieska Julie Rust Hsiao‐Chun Huang Christy Wessel‐Powell Retno Hendryanti Jae‐Seok Yang Arnell Hammond Pei‐Shan Yu Christina Ivanova Amber Warren Tolga Kargin Bita H. Zakeri Advisory Board Donna Sayers Adomat Larry Mikulecky Stephanie Carter Martha Nyikos James Damico Faridah Pawan D. Ted Hall Beth Lewis Samuelson Mary Beth Hines Raymond Smith Mitzi Lewison Karen Wohlwend Carmen Medina Website Administrators Rebecca Barrett Serafín M. Coronel‐Molina Copyright © 2014 Working Papers in Literacy, Culture, and Language Education (WPLCLE), and the respective authors. All rights reserved. No part of this work may be reproduced in any form by any means, including photocopying and recording, or by any information storage or retrieval system (except for brief quotations in critical articles or reviews) without written permission from WPLCLE or the respective authors. Working Papers in Literacy, Culture, and Language Education (WPLCLE) School of Education, Indiana University W.W. Wright Education Building 201 N. Rose Ave., Room #3044 Bloomington, IN 47405‐1006 Phone: (812) 856‐8270 Fax: (812) 856‐8287 E‐mail: [email protected] -
Contributions of New Technologies to the Teaching of English Pronunciation
Language Value July 2017, Volume 9, Number 1 pp. 1-35 http://www.e-revistes.uji.es/languagevalue Copyright © 2017, ISSN 1989-7103 Contributions of new technologies to the teaching of English pronunciation Yolanda Joy Calvo Benzies [email protected] University of the Balearic Islands, Spain ABSTRACT One of the most significant changes in language classrooms over recent decades has been the introduction of ICTs. Despite a broad range of previous research in the field, little work has been done to date on assessing the benefits of teaching pronunciation through ICTs, something surprising in view of the large number of existing programs and other materials specifically designed to improve learners’ pronunciation. This paper is intended to contribute to the field in that it will provide an overview of the materials currently available for teaching pronunciation through the use of ICTs, as well as an empirical preliminary study on ESP students’ first contact with using ICTs for learning pronunciation. Results indicate that these students enjoyed using these technological tools and would like to use them again to practise their pronunciation. Keywords: Pronunciation, ESP student’s opinions, apps, software, blogs, websites I. INTRODUCTION Previous research in the teaching and learning of English has shown that more attention is usually paid to written skills than to spoken ones in EFL settings (Alonso 2014, Hornero et al. 2013, Calvo 2016a). Furthermore, within spoken skills, pronunciation has traditionally been neglected, to the point where it has been referred to as the poor relation of the English teaching world (Hughes 2002), the orphan (Gilbert 2010) or even the Cinderella (Underhill 2013) in language lessons. -
Gathering Text Entry Metrics on Android Devices
Proceedings of the International Conference on Multimedia and Human Computer Interaction Toronto, Ontario, Canada, July 18-19 2013 Paper No. 120 Gathering Text Entry Metrics on Android Devices Steven J. Castellucci, I. Scott MacKenzie York University, Department of Computer Science and Engineering 4700 Keele St., Toronto, Ontario, Canada M3J 1P3 [email protected]; [email protected] Abstract -We developed TEMA, an application to gather Text Entry speed and accuracy Metrics on Android devices. This paper details the features of the application, describes a user study to demonstrate its utility, and establishes entry speed and accuracy measurements for the evaluated text entry techniques. We evaluated and compared four mobile text entry methods: two-thumb QWERTY typing, one-finger QWERTY typing, handwriting recognition, and shape writing recognition. The two QWERTY techniques were the fastest, with no statistically significant difference between them in entry speed or accuracy. Shape writing was slightly slower, but similar in accuracy. Handwriting was the slowest and least accurate technique. Keywords: Text entry, metrics, entry speed, accuracy, Android 1. Introduction Mobile devices are often used for SMS text messaging and social networking. An estimated 9.2 trillion text messages will be sent in 2013 (Web-1) and more than 680 million people access Facebook using mobile devices per month (Web-2). Thus, investigating methods for mobile text entry is a significant research topic. To aid evaluation of mobile text entry methods, we created an application to gather user performance metrics on Android devices: Text Entry Metrics on Android (TEMA). In this paper, we present our motivation for TEMA and its features. -
Using Virtual Assistants and Chatbots for Crisis Communication Uso De Asistentes Virtuales Y Chatbots Para La Comunicación De Crisis
aDResearch ESIC Nº 25 Vol 25 · Monográfico especial, marzo 2021 · págs. 70 a 91 Using Virtual Assistants and Chatbots for Crisis Communication Uso de asistentes virtuales y chatbots para la comunicación de crisis Gema Bonales Daimiel, Ph.D., Bonales Daimiel, G. y Citlali Martínez Estrella, E. (2021) Associate professor at the department Using virtual assistants and chatbots for crisis of Applied Communication Sciences, communication Complutense University of Madrid Revista Internacional de Investigación en Comunicación [email protected] aDResearch ESIC. Nº 25 Vol 25 https://orcid.org/0000-0003-2085-2203 Monográfico especial, marzo 2021 · Págs. 70 a 91 Eva Citlali Martínez Estrella, Ph.D. student, https://doi.org/10.7263/adresic-025-04 Complutense University of Madrid [email protected] https://orcid.org/0000-0001-6599-1050 Nº 25 Vol 25 · Monográfico especial, marzo 2021 · págs. 70 a 91 ABSTRACT Purpose: To study the role of bots and the main virtual assistants as communication tools and support for citizenship. The goal is to observe if this type of technology achieves the designed objectives, if it is useful for the users and to know how they have contributed to the communi- cation crisis strategies of the government and other institutions in the context of the Covid-19 pandemic. Design / Methodology / Approach: The current study therefore pursued a mixed method: a qualitative fieldwork whit a quantitative assessment by adding an additional measurement from user’s interest. In order to achieve the objectives, the research has a comparative analysis that contrasts the data collected in surveys, interviews with experts and in the fieldwork done on the selected platforms, which have been analyzed from seven different dimensions: pre- JEL Classification: determined questions, initial greeting, privacy policies, languages, data on the health center, M31 health recommendations and a diagnosis option. -
Comparison of Voice Assistant Sdks for Embedded Linux Leon Anavi Konsulko Group [email protected] [email protected] ELCE 2018
Comparison of Voice Assistant SDKs for Embedded Linux Leon Anavi Konsulko Group [email protected] [email protected] ELCE 2018 Konsulko Group Services company specializing in Embedded Linux and Open Source Software Hardware/software build, design, development, and training services Based in San Jose, CA with an engineering presence worldwide http://konsulko.com ELCE 2018, Comparison of Voice Assistant SDKs for Embedded Linux, Leon Anavi Agenda Introduction to smart speakers with voice assistants Overview of Amazon Alexa, Google Assistant and Mycroft SDK for integration in embedded Linux devices Showcases and conclusions ELCE 2018, Comparison of Voice Assistant SDKs for Embedded Linux, Leon Anavi Virtual assistants AliGenie Mirosoft Cortana Amazon Alexa Google Assistant Yandex Alice Mycroft Samsung Bixby Apple Siri Braina Voice Mate Clova More ... ELCE 2018, Comparison of Voice Assistant SDKs for Embedded Linux, Leon Anavi Technologies in Smart Speakers A.I. & Big Data Application Internet of Things Development ELCE 2018, Comparison of Voice Assistant SDKs for Embedded Linux, Leon Anavi Key Software Ingredients Artifcial Intelligence & Big Data Wake word detection Text to speech (TTS) Speech to text (STT) Board bring-up 3rd party applications ELCE 2018, Comparison of Voice Assistant SDKs for Embedded Linux, Leon Anavi Smart Speaker Market Public statistics from https://voicebot.ai/ ELCE 2018, Comparison of Voice Assistant SDKs for Embedded Linux, Leon Anavi Amazon Alexa Amazon Alexa Virtual assistant powered -
Classifying Smart Personal Assistants: an Empirical Cluster Analysis
Proceedings of the 52nd Hawaii International Conference on System Sciences | 2019 Classifying Smart Personal Assistants: An Empirical Cluster Analysis Robin Knote Andreas Janson Matthias Söllner University of Kassel University of Kassel University of St.Gallen and [email protected] [email protected] University of Kassel [email protected] Jan Marco Leimeister University of St.Gallen and University of Kassel [email protected] Abstract provision. In practice, SPAs unfold their potential in various forms and contexts [8], such as on smartphones The digital age has yielded systems that [38], in smart home environments [11], in cars [5], in increasingly reduce the complexity of our everyday service encounters [43], or as support for elderly or lives. As such, smart personal assistants such as impaired people [11]. Amazon’s Alexa or Apple’s Siri combine the comfort of However, prominent examples such as those intuitive natural language interaction with the utility of mentioned above represent SPAs that are explicitly personalized and situation-dependent information and developed for a broad consumer market. They thus are service provision. However, research on SPAs is only the tip of the iceberg. Since the idea of becoming increasingly complex and opaque. To reduce information systems (IS) that pervasively assist complexity, this paper introduces a classification humans in conducting certain tasks is by far not new, system for SPAs. Based on a systematic literature numerous efforts were made in IS, computer science review, a cluster analysis reveals five SPA archetypes: and human-computer-interaction research to develop Adaptive Voice (Vision) Assistants, Chatbot Assistants, SPAs as previously defined.