Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-29T02:08:30.975Z Has data issue: false hasContentIssue false
  • English
  • Français

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

Published online by Cambridge University Press:  27 November 2015

F C Lyall ,
P J Clamp  and
D Hajioff
F C Lyall*
Affiliation:
Peninsula Radiology Academy, Plymouth, UK
P J Clamp
Affiliation:
Department of ENT Surgery, University Hospitals Bristol, UK
D Hajioff
Affiliation:
Department of ENT Surgery, University Hospitals Bristol, UK
*
Address for correspondence: Dr Fiona Lyall, Peninsula Radiology Academy, William Prance Road, Derriford, Plymouth PL6 5WR, UK E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective:

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.

Keywords

Cell PhonesCommunication Aids for DisabledCommunication Methods, TotalCochlear ImplantationPersons With Hearing ImpairmentsPostoperative CareSpeech Recognition SoftwareWriting
Type
Short Communication
Information
The Journal of Laryngology & Otology , Volume 130 , Issue 1 , January 2016 , pp. 104 - 106
Copyright
Copyright © JLO (1984) Limited 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Presented at the Association of Surgeons in Training conference, 5–7 April 2013, Manchester, UK.

References

1Ebert, DA, Heckerling, PS. Communication with deaf patients: knowledge, beliefs and practices of physicians. JAMA 1995;273:227–9CrossRefGoogle ScholarPubMed
2Reeves, D, Kokoruwe, B. Communication and communication support in primary care: a survey of deaf patients. Audiol Med 2005;3:95–107CrossRefGoogle Scholar
3Middleton, A, Turner, GH, Bitner-Glindzicz, M, Lewis, P, Richards, M, Clarke, A et al. Preferences for communication in clinic from deaf people: a cross-sectional study. J Eval Clin Prac 2010;16:811–17CrossRefGoogle ScholarPubMed
4National Institute for Health and Clinical Excellence. NICE Technology Appraisal Guidance 166: Cochlear Implants for Children and Adults with Severe to Profound Deafness. London: NICE, 2009Google Scholar
5Hinman, RT, Lupton, EC, Leeb, SB, Avestruz, A, Gilmore, R, Paul, D et al. Using talking lights illumination-based communication networks to enhance word comprehension by people who are deaf or hard of hearing. Am J Audiol 2003;12:17–22CrossRefGoogle ScholarPubMed
6Zekveld, AA, Kramer, SE, Kessens, JM, Vlaming, MS, Houtgast, T. The benefit obtained from visually displayed text from an automatic speech recognizer during listening to speech presented in noise. Ear Hear 2008;29:838–52CrossRefGoogle ScholarPubMed
7Klann, JG, Szolovits, P. An intelligent listening framework for capturing encounter notes from a doctor-patient dialog. BMC Med Inform Decis Mak 2009;9(suppl 1):S3CrossRefGoogle ScholarPubMed
8Issenmann, RM, Haffer, IH. Use of voice recognition software in an outpatient pediatric specialty practice. Pediatrics 2004;114:290–3CrossRefGoogle Scholar
9Bottrill, ID. The practical application of voice recognition technology in the ENT clinic. Otorhinolaryngologist 2008;2:58–60Google Scholar
10Fellbaum, K, Koroupetroglou, G. Principles of electronic speech processing with applications for people with disabilities. Technology and Disability 2008;20:55–85CrossRefGoogle Scholar