Impact of noise and other factors on speech recognition in anaesthesia

Int J Med Inform. 2008 Jan;77(1):68-77. doi: 10.1016/j.ijmedinf.2006.11.007. Epub 2006 Dec 27.

Abstract

Introduction: Speech recognition is currently being deployed in medical and anaesthesia applications. This article is part of a project to investigate and further develop a prototype of a speech-input interface in Danish for an electronic anaesthesia patient record, to be used in real time during operations.

Objective: The aim of the experiment is to evaluate the relative impact of several factors affecting speech recognition when used in operating rooms, such as the type or loudness of background noises, type of microphone, type of recognition mode (free speech versus command mode), and type of training.

Methods: Eight volunteers read aloud a total of about 3600 typical short anaesthesia comments to be transcribed by a continuous speech recognition system. Background noises were collected in an operating room and reproduced. A regression analysis and descriptive statistics were done to evaluate the relative effect of various factors.

Results: Some factors have a major impact, such as the words to be recognised, the type of recognition and participants. The type of microphone is especially significant when combined with the type of noise. While loud noises in the operating room can have a predominant effect, recognition rates for common noises (e.g. ventilation, alarms) are only slightly below rates obtained in a quiet environment. Finally, a redundant architecture succeeds in improving the reliability of the recognitions.

Conclusion: This study removes some uncertainties regarding the feasibility of introducing speech recognition for anaesthesia records during operations, and provides an overview of the interaction of several parameters that are traditionally studied separately.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Anesthesia Department, Hospital*
  • Denmark
  • Equipment Failure Analysis
  • Female
  • Humans
  • Male
  • Medical Records Systems, Computerized
  • Middle Aged
  • Noise, Occupational*
  • Operating Rooms
  • Speech Recognition Software / standards*
  • User-Computer Interface