Title
Calibration of clinical audio recording and analysis systems for sound intensity measurementCalibration of clinical audio recording and analysis systems for sound intensity measurement
Author
Faculty/Department
Faculty of Medicine and Health Sciences
Research group
Faculteit Geneeskunde
Publication type
article
Publication
,
Subject
Human medicine
Linguistics
Source (journal)
American journal of speech-language pathology. -
Volume/pages
24(2015):4, p. 608-618
ISSN
1058-0360
ISI
000368430100020
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Purpose: Sound intensity is an important acoustic feature of voice/speech signals. Yet recordings are performed with different microphone, amplifier, and computer configurations, and it is therefore crucial to calibrate sound intensity measures of clinical audio recording and analysis systems on the basis of output of a sound-level meter. This study was designed to evaluate feasibility, validity, and accuracy of calibration methods, including audiometric speech noise signals and human voice signals under typical speech conditions. Method: Calibration consisted of 3 comparisons between data from 29 measurement microphone-and-computer systems and data from the sound-level meter: signal-specific comparison with audiometric speech noise at 5 levels, signal-specific comparison with natural voice at 3 levels, and cross-signal comparison with natural voice at 3 levels. Intensity measures from recording systems were then linearly converted into calibrated data on the basis of these comparisons, and validity and accuracy of calibrated sound intensity were investigated. Results: Very strong correlations and quasisimilarity were found between calibrated data and sound-level meter data across calibration methods and recording systems. Conclusions: Calibration of clinical sound intensity measures according to this method is feasible, valid, accurate, and representative for a heterogeneous set of microphones and data acquisition systems in real-life circumstances with distinct noise contexts.
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