Literature DB >> 16147224

Influence of sampling rate on accuracy and reliability of acoustic voice analysis.

Dimitar D Deliyski1, Heather S Shaw, Maegan K Evans.   

Abstract

It is universally recognized that sampling rate (F(S)) influences the reliability and validity of acoustic voice measurements; however, an exact relationship has not been determined. The purpose of this experiment was to investigate the influence of F(S) on acoustic voice quality measurements, while considering the influences of gender, intra-subject variability, microphone, environmental noise, data acquisition hardware, and analysis software as balancing factors. The impact of F(S), from 44.1 kHz to 10 kHz, was explored by analyzing 864,000 measures of fundamental frequency, jitter, and shimmer, using three software analysis systems: MDVP, TF32, and PRAAT. Results suggest that the recommended, acceptable, and critical F(S) for acoustic voice analysis are above 26 kHz, above 19 kHz, and 12 kHz, respectively. Thus, voice samples captured above 26 kHz can be used for data analysis and compared without introducing error due to F(S).

Mesh:

Year:  2005        PMID: 16147224     DOI: 10.1080/1401543051006721

Source DB:  PubMed          Journal:  Logoped Phoniatr Vocol        ISSN: 1401-5439            Impact factor:   1.487


  7 in total

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Authors:  Yu-An S Lien; Elizabeth S Heller Murray; Carolyn R Calabrese; Carolyn M Michener; Jarrad H Van Stan; Daryush D Mehta; Robert E Hillman; J Pieter Noordzij; Cara E Stepp
Journal:  Ann Otol Rhinol Laryngol       Date:  2017-08-29       Impact factor: 1.547

2.  Clinical value of acoustic voice measures: a retrospective study.

Authors:  Katrin Werth; Daniel Voigt; Michael Döllinger; Ulrich Eysholdt; Jörg Lohscheller
Journal:  Eur Arch Otorhinolaryngol       Date:  2010-02-21       Impact factor: 2.503

3.  Adaptations in humans for assessing physical strength from the voice.

Authors:  Aaron Sell; Gregory A Bryant; Leda Cosmides; John Tooby; Daniel Sznycer; Christopher von Rueden; Andre Krauss; Michael Gurven
Journal:  Proc Biol Sci       Date:  2010-06-16       Impact factor: 5.349

4.  Standardization of pitch-range settings in voice acoustic analysis.

Authors:  Adam P Vogel; Paul Maruff; Peter J Snyder; James C Mundt
Journal:  Behav Res Methods       Date:  2009-05

5.  Development of the Arabic Voice Pathology Database and Its Evaluation by Using Speech Features and Machine Learning Algorithms.

Authors:  Tamer A Mesallam; Mohamed Farahat; Khalid H Malki; Mansour Alsulaiman; Zulfiqar Ali; Ahmed Al-Nasheri; Ghulam Muhammad
Journal:  J Healthc Eng       Date:  2017-10-19       Impact factor: 2.682

6.  Influence of spatial camera resolution in high-speed videoendoscopy on laryngeal parameters.

Authors:  Patrick Schlegel; Melda Kunduk; Michael Stingl; Marion Semmler; Michael Döllinger; Christopher Bohr; Anne Schützenberger
Journal:  PLoS One       Date:  2019-04-22       Impact factor: 3.240

7.  Validating Biobehavioral Technologies for Use in Clinical Psychiatry.

Authors:  Alex S Cohen; Christopher R Cox; Raymond P Tucker; Kyle R Mitchell; Elana K Schwartz; Thanh P Le; Peter W Foltz; Terje B Holmlund; Brita Elvevåg
Journal:  Front Psychiatry       Date:  2021-06-11       Impact factor: 4.157

  7 in total

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