Reproducibility of Voice Parameters: The Effect of Room Acoustics and Microphones
| Autor: | Eric Hunter, Juliana Codino, Jean Skeffington, Pasquale Bottalico, Maria Cristina Jackson-Menaldi, Katherine L. Marks, Rahul Shrivastav, Lady Catherine Cantor-Cutiva, Charles Nudelman, Adam D. Rubin |
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| Rok vydání: | 2020 |
| Předmět: |
Adult
Male Sound Spectrography Voice Quality Microphone Computer science Acoustics Transducers Speech Acoustics Article Background noise Motion Young Adult 030507 speech-language pathology & audiology 03 medical and health sciences Speech and Hearing 0302 clinical medicine Quality (physics) Speech Production Measurement Cepstrum medicine Humans 030223 otorhinolaryngology Jitter Torso LPN and LVN Room acoustics Sound Tilt (optics) medicine.anatomical_structure Otorhinolaryngology Facility Design and Construction Female Noise 0305 other medical science |
| Zdroj: | J Voice |
| ISSN: | 0892-1997 |
| DOI: | 10.1016/j.jvoice.2018.10.016 |
| Popis: | Summary Introduction Computer analysis of voice recordings is an integral part of the evaluation and management of voice disorders. In many practices, voice samples are taken in rooms that are not sound attenuated and/or sound-proofed; further, the technology used is rarely consistent. This will likely affect the recordings, and therefore, their analyses. Objectives The objective of this study is to compare various acoustic outcome measures taken from samples recorded in a sound-proofed booth to those recorded in more common clinic environments. Further, the effects from six different commonly used microphones will be compared. Methods Thirty-six speakers were recorded while reading a text and producing sustained vowels in a controlled acoustic environment. The collected samples were reproduced by a Head and Torso Simulator and recorded in three clinical rooms and in a sound booth using six different microphones. Newer measures (eg, Pitch Strength, cepstral peak prominence, Acoustic Voice Quality Index), as well as more traditional measures (eg Jitter, Shimmer, harmonics-to-noise ratio and Spectrum Tilt), were calculated from the samples collected with each microphone and within each room. Results The measures which are more robust to room acoustic differences, background noise, and microphone quality include Jitter and smooth cepstral peak prominence, followed by Shimmer, Acoustic Voice Quality Index, harmonics-to-noise ratio, Pitch Strength, and Spectrum Tilt. Conclusions The effect of room acoustics and background noise on voice parameters appears to be stronger than the type of microphone used for the recording. Consequently, an appropriate acoustical clinical space may be more important than the quality of the microphone. |
| Databáze: | OpenAIRE |
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