Smartphone speech-to-text applications for communication with profoundly deaf patients

2015 ◽  
Vol 130 (1) ◽  
pp. 104-106 ◽  
Author(s):  
F C Lyall ◽  
P J Clamp ◽  
D Hajioff
Keyword(s):  
Speech Recognition ◽  
Confidence Interval ◽  
Communication Aids ◽  
Speech Recognition Software ◽  
Feasible Alternative ◽  
Standard Set ◽  
The Mean ◽  
Recognition Software ◽  
Slow Speech ◽  
Mean Time

AbstractObjective:Visual communication aids, such as handwriting or typing, are often used to communicate with deaf patients in the clinic. This study aimed to establish the feasibility of communicating through smartphone speech recognition software compared with writing or typing.Method:Thirty doctors and medical students were timed writing, typing and dictating a standard set of six sentences appropriate for a post-operative consultation, and the results were assessed for accuracy and legibility.Results:The mean time for smartphone dictation (17.8 seconds, 95 per cent confidence interval = 17.0–18.7) was significantly faster than writing (59.2 seconds, 95 per cent confidence interval = 56.6–61.7) or typing (44 seconds, 95 per cent confidence interval = 41.0–47.1) (p< 0.001). Speech recognition was slightly less accurate, but accuracy increased with time spent dictating.Conclusion:Smartphone dictation is a feasible alternative to typing and handwriting. Slow speech may improve accuracy. Early clinical experience has been promising.

Implementation of a Voice-ControlSystem for Issuing Commands in a Virtual Manufacturing Simulation Process

2014 ◽  
Vol 980 ◽  
pp. 165-171
Author(s):  
Yun Suen Pai ◽  
Hwa Jen Yap ◽  
Ramesh Singh
Keyword(s):  
Speech Recognition ◽  
Application Programming Interface ◽  
Virtual Manufacturing ◽  
Numerical Control ◽  
Robot Arm ◽  
Cnc Machine ◽  
Simulation Process ◽  
Speech Recognition Software ◽  
Programming Knowledge ◽  
Recognition Software

Speech recognition is a technology that attempts to involve audio cues during interaction with machines, instead of being limited to just visual and touch interfaces. However, a keyboard and mouse input is an archaic method of interaction, adding on to the fact that voice control is seemingly more natural. This study aims to implement speech recognition as a form of machine control to perform simple commands in a virtual simulation process. The simulation system is an in-house developed augmented reality robotic work cell which includes a robot arm, a conveyer belt, a computer numerical control (CNC) machine, and a pellet. Issuing commands are performed via the Windows Speech Recognition software built from the Microsoft Speech Application Programming Interface (SAPI). This software is advantageous because it can be fairly accurate once trained properly, is easily modifiable by anyone regardless of the operator’s programming knowledge, and is free. A macros tool is used to support the additional features of the recognition software which includes directly programmable Extensible Markup Language (XML) codes.

Support Technique for Real-Time Captionist to Use Speech Recognition Software

2008 ◽  
pp. 647-650 ◽  
Author(s):  
Shigeki Miyoshi ◽  
Hayato Kuroki ◽  
Sumihiro Kawano ◽  
Mayumi Shirasawa ◽  
Yasushi Ishihara ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Real Time ◽  
Speech Recognition Software ◽  
Recognition Software

Voice/Speech Recognition Software

2013 ◽  
pp. 1005-1011
Author(s):  
Andrew Kitchenham ◽  
Doug Bowes
Keyword(s):  
Speech Recognition ◽  
Assistive Technology ◽  
Special Needs ◽  
Learning Process ◽  
Voice Recognition ◽  
Special Needs Students ◽  
Speech Recognition Software ◽  
The Disabled ◽  
Recognition Software

In this chapter, the authors discuss the promise of speech or voice recognition software and provide practical suggestions for the teacher or any stakeholder working with a disabled child. The authors begin the chapter with a brief overview of the legislation mandating the accommodation of special needs students in the classroom and discuss the implications of assistive technology. The authors then move on to an examination of the promise of the software. The authors end the chapter with practical ideas for implementation should the caregiver believe that voice recognition software will assist the disabled child in the learning process.

The experience of speech recognition software abandonment by adolescents with physical disabilities

2014 ◽  
Vol 9 (6) ◽  
pp. 513-520 ◽  
Author(s):  
Rebecca Van Schyndel ◽  
Amita Bhargava Furgoch ◽  
Tara Previl ◽  
Rose Martini
Keyword(s):  
Speech Recognition ◽  
Physical Disabilities ◽  
Speech Recognition Software ◽  
Recognition Software

scholarly journals Incidence and Risk Factors for Vancomycin Nephrotoxicity in Acutely Ill Pediatric Patients

2017 ◽  
Vol 34 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Henock Woldu ◽  
B. Joseph Guglielmo
Keyword(s):  
Risk Factors ◽  
Confidence Interval ◽  
Serum Creatinine ◽  
Odds Ratio ◽  
Kidney Injury ◽  
Severe Toxicity ◽  
Vancomycin Trough ◽  
Trough Concentrations ◽  
The Mean ◽  
Mean Time

Background: Particularly with the current increased vancomycin dosing trends, the true risk of the agent’s nephrotoxicity is not well characterized and remains of concern. Objective: To determine the incidence of vancomycin nephrotoxicity in acutely ill hospitalized children and to secondarily characterize the risk factors for this complication. Methods: A single-center retrospective cohort study conducted at UCSF Benioff Children’s Hospital from June 2012 to June 2015. Inpatients 3 months to <19 years who received intravenous vancomycin for ≥48 hours were included. The primary outcome was incidence of nephrotoxicity, defined as an increase in serum creatinine by ≥50% from baseline. Univariate and multivariate analyses were conducted to identify risk factors for vancomycin nephrotoxicity. Results: A total of 291 patients (272 nonnephrotoxic and 19 nephrotoxic) were included in the analysis. Of the 19 patients, 12 (4.1%) were found to have moderate to severe toxicity. The median duration of therapy was 3 (3-5) and 4 (3-6) days for the group with “no nephrotoxicity” and “nephrotoxicity,” respectively. The mean time for the serum creatinine to return to normal in patients with nephrotoxicity was 5.1 days. In the multivariate analysis, only final trough concentration ≥15mg/dL (odds ratio = 3.49, 95% confidence interval = 1.2-10.1; P = .021) and receipt of piperacillin/tazobactam (odds ratio = 3.14, 95% confidence interval = 1.02-9.6; P = .046) were significantly associated with nephrotoxicity. Conclusion: The rate of moderate to severe vancomycin-associated nephrotoxicity in acutely ill children is relatively uncommon and reversible. Kidney injury is associated with increased vancomycin trough concentrations and concomitant receipt of nephrotoxins, particularly piperacillin/tazobactam.

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