Talking"‚ PC Week‚ December 7‚ 1998. Mayor‚ Tracy‚ "Look Ma‚ No Hands" PC Week‚ July 1‚ 1996. Coskun‚ Samli A.‚ "Information-Driven Marketing Decisions: Development of Strategic Information Systems" Quorum Books‚ 1996. Schindler‚ Esther‚ "The Computer Speech Book" Academic Press‚ Inc.‚ 1996. Sichel‚ Daniel E.‚ "The Computer Revolution - An Economic Perspective" The Brookings Institution‚ 1997. Vossen‚ Gottfried‚ "Data Models‚ Database languages and Database Management Systems" Wokingham‚ 1991. Watterson
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The dawn of personal computing in the early 1980s was the beginning of a rapidly evolving technology stranglehold on everyday life. The mechanical world of typewriters‚ dedicated word processors and adding machines with cranks were quickly left in a wake of microchips. The good news: you could do more. The bad news: you can be caught in a mire of complex and often-confusing computer-based equipment. The study of Human-Computer Interaction (HCI) finally took center stage in the mid-1990s as the World
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movement towards an electronic environment for health information management (Office of the National Coordinator for Health Information Technology‚ n.d.). This has been the driving force behind increased adoption of Electronic Health Records and Speech Recognition Technology; two tools that threaten to replace medical transcription. While this fundamental transformation is reshaping the industry’s future‚ it has also created an opportunity for the growth of the field of healthcare documentation. It will
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medical transcriptionists. With advancement in technology‚ voice recognition system has taken the place of medical transcriptionists. Voice recognition has decreased the turn-around-time of dictated reports and proven to be cost-effective. Although this may be true‚ the software has problems distinguishing between words that sounds-alike‚ has a high number of transcribed mistakes‚ and has difficulty interpreting normal pace of speech. For these reasons‚ medical transcriptionists are better suited
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ARTIFICIAL PASSENGER-An interactive Artificial Intelligence Anushree N.S.‚ L.Kavyashree 5th semester‚ department of ISE ‚BITM ‚ Bellary. Abstract-Usually‚ an automobilist interacts with the other passengers to stay alert during a journey. This methodology may not actually help him to the mark. But‚ an application of the artificial intelligence can fix the issue. It is called as “Artificial
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Venica Acosta for Finance‚ our academic and administrative deans‚ the faculty and staff‚ fellow scholars and students‚ friends‚ ladies and gentlemen‚ good afternoon. I am not a special person because I am standing here at the stage giving my speech after being chosen by the committee on scholarship and awards. I am not an idol to be praised all the time. I am just like everyone else in this university who study the designed curriculum for me. I am also a student who walks in the corridors‚ who
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Related Literature Related literatures refer to the list of reference related to the study being conducted. This will serve as a guide. According to: Anil K. Jain‚ Brendan Klare‚ and Unsang Park of Michigan State University. Face Recognition Face recognition is the task of recognizing a person using digital face images. A FRS is typically designed to output a measure of similarity between two face images. Automated FRSs typically involve finding key facial landmarks (such as the center of
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messaging‚ email‚ e-paging‚ and fax and e-mail are also used in telecommunications by people who are deaf or hard of hearing. -TRS Telecommunications relay services (TRS) provide voice telephone users and people who are deaf‚ hard of hearing‚ or speech-disabled to communicate over a regular telephone line. TRS is mandated by the Americans with Disabilities Act and is regulated by the Federal Communications Commission. There have been many new improvements in TRS in the last several years. These
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AUTOMATIC SENTENCE GENERATOR SYSTEM FOR SPEECH RECOGNITION APPLICATIONS. José Luciano Maldonado. Universidad de Los Andes‚ FACES‚ Núcleo La Liria‚ edificio G‚ piso 1‚ Instituto de Estadística Aplicada y Computación‚ IEAC‚ Mérida‚ Venezuela. luzmalvy@telcel.net.ve maldonaj@faces.ula.ve Abstract. We describe an experimental computer program which can generate sentences automatically. To do so‚ models are first created based on contexts of interest. These models incorporate word histories that are
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functional requirements that proves thisobjective was developed the way it was proposed. Part of the study is to implement Google Speech API for speech recognition and accelerometer for gesture-based input utilizing Hidden Markov Models and which is the second objective of the study. The study was able to develop a voice gestural method which implements Google Speech API. This will let the users input words or even sequence of words just by saying
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