Speech Recognition Technology: Improving Speed and Accuracy of Emergency Medical Services Documentation to Protect Patients

Because hospital errors, such as mistakes in documentation, cause one in six deaths each year in the United States, the accuracy of health records in the emergency medical services (EMS) must be improved. One possible solution is to incorporate speech recognition (SR) software into current tools used by EMS first responders. The purpose of this research was to determine if SR software could increase the efficiency and accuracy of EMS documentation to improve the safety of patients of EMS. An initial review of the literature on the performance of current SR software demonstrated that this software was not 99% accurate, and therefore, errors in the medical documentation produced by the software could harm patients. The literature review also identified weaknesses of SR software that could be overcome so that the software would be accurate enough for use in EMS settings. These weaknesses included the inability to differentiate between similar phrases and the inability to filter out background noise. To find a solution, an analysis of natural language processing algorithms showed that the bag-of-words post processing algorithm has the ability to differentiate between similar phrases. This algorithm is best suited for SR applications because it is simple yet effective compared to machine learning algorithms that required a large amount of training data. The findings suggested that if these weaknesses of current SR software are solved, then the software would potentially increase the efficiency and accuracy of EMS documentation. Further studies should integrate the bag-of-words post processing method into SR software and field test its accuracy in EMS settings

Speech Recognition Technology: Improving Speed and Accuracy of Emergency Medical Services Documentation to Protect Patients

Because hospital errors, such as mistakes in documentation, cause one sixth of the deaths each year in the United States, the accuracy of health records in the emergency medical services (EMS) must be improved. One possible solution is to incorporate speech recognition (SR) software into current tools used by EMS first responders. The purpose of this research was to determine if SR software could increase the efficiency and accuracy of EMS documentation to improve the safety for patients of EMS. An initial review of the literature on the performance of current SR software demonstrated that this software was not 99% accurate and therefore, errors in the medical documentation produced by the software could harm patients. The literature review also identified weaknesses of SR software that could be overcome so that the software would be accurate enough for use in EMS settings. These weaknesses included the inability to differentiate between similar phrases and the inability to filter out background noise. To find a solution, an analysis of natural language processing algorithms showed that the bag-of-words post processing algorithm has the ability to differentiate between similar phrases. This algorithm is the best suited for SR applications because it is simple yet effective compared to machine learning algorithms that required a large amount of training data. The findings suggested that if these weaknesses of current SR software are solved, then the software would potentially increase the efficiency and accuracy of EMS documentation. Further studies should integrate the bag-of-words post processing method into SR software and field test its accuracy in EMS settings.https://scholarscompass.vcu.edu/uresposters/1273/thumbnail.jp

Quality Analysis of Software Applications using Software Reliability Growth Models and Deep Learning Models

Finding the faults in the software is a very tedious task. Many software companies are trying to develop high-quality software which is having no faults. It is very important to analyze the errors, faults, and bugs in software development. Software reliability growth models (SRGM's) are used to help the software industries to create quality software products. Quality is the software metric that is used to analyze the performance of the software product. The software product which is having no errors or faults is considered the best software product. SRGM is also utilized to analyze the software quality based on the programming language. Deep Learning (DL) is a sub-domain in machine learning to solve several complex issues in software development. Finding accurate patterns from software faults is a very tedious task. DL algorithm performs better in integrating the SRGM with the DL approaches giving better results based on software fault detection. Many software faults real-time datasets are available to analyze the DL approaches. The performances of the various integrated models are analyzed by showing the quality metrics

Designing Tools to Facilitate Students Learning American Sign Language

Students learning American Sign Language (ASL) lack interactive tools to give them feedback on their signing accuracy, when a human ASL instructor is not available. In this multi-university NSF-funded project, we are creating software, utilizing a Kinect camera, to aid students who are learning ASL. In the final system, computer vision software will identify aspects of signing that contain nonfluent movements and give feedback to students practicing ASL independently. This tool won’t replace feedback from ASL instructors; it would only catch certain errors

Constructive Use of Errors in Teaching the UML Class Diagram in an IS Engineering Course

A class diagram is one of the most important diagrams of Unified Modeling Language (UML) and can be used for modeling the static structure of a software system. Learning from errors is a teaching approach based on the assumption that errors can promote learning. We applied a constructive approach of using errors in designing a UML class diagram in order to (a) categorize the students’ errors when they design a class diagram from a text scenario that describes a specific organization and (b) determine whether the learning-from-errors approach enables students to produce more accurate and correct diagrams. The research was conducted with college students (N = 45) studying for their bachelor’s degree in engineering. The approach is presented, and the learning-from-errors activity is illustrated. We present the students’ errors in designing the class diagram before and after the activity, together with the students’ opinions about applying the new approach in their course. Twenty errors in fundamental components of the class diagram design were observed. The students erred less after the activity of learning from errors. The displayed results show the relevance and potential of embedding our approach in teaching. Furthermore, the students viewed the learning-from-errors activity favorably. Thus, one of the benefits of our developed activity is increased student motivation. In light of the improved performance of the task, and the students’ responses to the learning-from-errors approach, we recommend that information systems teachers use similar activities in different fields and on various topics

Rancang Bangun Aplikasi Mobile Learning Tenses Bahasa Inggris

All that requires a media to understand each other and understand one another. The media is language. Language is a medium for communication so cooperation will be created in various aspects. English is the connecting language used as a medium of communication between countries in the world. But some people find it difficult when learning English. The difficulty experienced is due to a lack of understanding of grammar, one of which includes tenses. Learning media as a means of improving the quality of education is very important in the learning process. The research methodology used is waterfall method as an application development methodology. The first step to do is to analyze the needs of the system made, including library research, data collection, consultation, and design. From this analysis a system design using usecase diagrams, activity diagrams and class diagrams is made as a system design to be made. After the system is designed, the next step is to write the program code. At writing the programming language program code used is java, android studio and genymotion as an emulator. Blacbox test results show the software can find out the functions that are not correct, interface errors, performance errors and functionally produce the expected results

Improving Language Pedagogy through Exploration of Learners’ Errors: An Examination of Undergraduates’ Written Communication

One major part of language learning pedagogy includes identifying and rectifying discrepancies while communicating through the target language. In such educational settings, the importance of understanding learners’ errors becomes undeniable for both the pupil and pedagogue. Keeping this in forefront, the current investigation sampled two-hundred and ten emails jotted down by ESL (‘English as a Second Language’) students to their teachers. This comparative investigation divided the learners’ emails into two groups; First Semester and Fourth Semester, enrolled in MA English at COMSATS Institute of Information Technology, Virtual Campus, Islamabad. Utilizing Corder’s Model (1967) and Sawalmeh’s Categorization (2013), the emails were scrutinized and the results established that selected Pakistani learners commit nine different errors regularly in their electronic mail communiqué. Moreover, these outputs were comparatively studied utilizing the statistical software of SPSS (Version 16.0). These results highlighted a significant difference between the two semesters, which revealed a considerable reduction of errors in the learners’ language use as they move from first to fourth semester of the prescribed degree program. Additionally, Richards’ framework (1974) for deciphering source of learners’ errors was employed, which depicted that the first semester students’ first language (Urdu) frequently interferes when they use the second language (English) in writing emails. Meanwhile, the fourth semester students’ language errors majorly contained deviant structures or ignorance of target language’s (English) rules. Considering these findings, the study proposes similar studies to be conducted on other institutes’ pupils and also recommends practical methodologies like corrective feedback for teachers, in aiding learners to fortify their command on English language

Does the MS Spell Checker Effectively Correct Non-Native English Writers’ Errors? A Case Study of Saudi University Students

Those learning English as a second or foreign language use spell checkers to correct the mistakes and errors they may have made while typing texts on a computer However scholars have debated the effectiveness of such checkers which were originally designed to fix the spelling mistakes of native speakers An example of these checkers is the Microsoft MS Word program which constitutes the focus of the current study This study examined how MS Word treats misspellings made by Saudi learners of English as a foreign language It specifically addressed three research questions 1 which L2 spelling errors were successfully fixed by MS Word 2 which L2 spelling errors were unsuccessfully fixed by MS Word and 3 how did intermediate L2 learners respond to alternative corrections provided by MS Word A screentracking software Screencast-O-Matic was used to monitor the MS Word spell checker s treatment of misspelled words It was also used to track learners reactions to alternative corrections provided by MS Word in real time The study analysed 401 errors made by25 female intermediate-level English learners at a Saudi universit

Identifying the Grammatical Errors Committed by EFL Learners: A study of Public Sector Universities Sindh, Pakistan

Grammar is considered very important for learning a foreign language as it is an important pedagogical skill and a significant part of target language proficiency. Teachers are, thus, supposed to identify L2 learners’ common grammar mistakes for addressing them in their teaching.   This study is intended to investigate the most common errors made by Pakistani students at university level. Data was collected through Google Survey by dispatching questionnaire to the participants (n=80) also distributed manually. The data was analyzed using SPSS software version 21. The results show that Pakistani university EFL students make a large number of both intra-lingual and inter-lingual errors.  The results also revealed that there was consensus found about the effectiveness of error correction. Teachers supported the use of different methods and stated that it has a positive impact on EFL learners' correct use of grammar. It is recommended that grammatical errors need more attention and the teachers need to provide essential feedback to minimize the error occurrence. Keywords: Error Analysis, GTM, Perceived Common Errors, Interlanguage, L1 Interferenc

Improving Speech-to-Text Transcription of Chinese Podcasts

The internship was spent contributing to the Tech Center’s ongoing podcast project; an ap- plication that will collect language podcasts and extract information from those podcasts that can help language learners and instructors better find relevant language learning materi- als. The podcast audio files are transcribed by software, and most of the work of the intern- ship was creating a markup tool that can im- prove the quality of the podcast transcriptions. The transcriptions were corrected by hand and then a rule-based approach was developed to correct errors the transcription software consis- tently made. This adds a layer of polish to the project, yielding cleaner and more accurate En- glish translations later on. The internship was largely exploratory, and the rest of the time was spent experimenting with other aspects of the project, such as researching lexical sophis- tication and how a metric for the sophistication of a text could be useful information to teach- ers or learners trying to gather useful study ma- terials