Literature DB >> 3351130

Measuring the rate of change of voice fundamental frequency in fluent speech during mental depression.

A Nilsonne1, J Sundberg, S Ternström, A Askenfelt.   

Abstract

A method of measuring the rate of change of fundamental frequency has been developed in an effort to find acoustic voice parameters that could be useful in psychiatric research. A minicomputer program was used to extract seven parameters from the fundamental frequency contour of tape-recorded speech samples: (1) the average rate of change of the fundamental frequency and (2) its standard deviation, (3) the absolute rate of fundamental frequency change, (4) the total reading time, (5) the percent pause time of the total reading time, (6) the mean, and (7) the standard deviation of the fundamental frequency distribution. The method is demonstrated on (a) a material consisting of synthetic speech and (b) voice recordings of depressed patients who were examined during depression and after improvement.

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Year:  1988        PMID: 3351130     DOI: 10.1121/1.396114

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  5 in total

1.  Detection of clinical depression in adolescents' speech during family interactions.

Authors:  Lu-Shih Alex Low; Namunu C Maddage; Margaret Lech; Lisa B Sheeber; Nicholas B Allen
Journal:  IEEE Trans Biomed Eng       Date:  2010-11-11       Impact factor: 4.538

2.  Remote capture of human voice acoustical data by telephone: a methods study.

Authors:  Michael S Cannizzaro; Nicole Reilly; James C Mundt; Peter J Snyder
Journal:  Clin Linguist Phon       Date:  2005-12       Impact factor: 1.346

3.  Identification of Mild Cognitive Impairment From Speech in Swedish Using Deep Sequential Neural Networks.

Authors:  Charalambos Themistocleous; Marie Eckerström; Dimitrios Kokkinakis
Journal:  Front Neurol       Date:  2018-11-15       Impact factor: 4.003

Review 4.  Voice Stress Analysis: A New Framework for Voice and Effort in Human Performance.

Authors:  Martine Van Puyvelde; Xavier Neyt; Francis McGlone; Nathalie Pattyn
Journal:  Front Psychol       Date:  2018-11-20

5.  A study of using cough sounds and deep neural networks for the early detection of Covid-19.

Authors:  Rumana Islam; Esam Abdel-Raheem; Mohammed Tarique
Journal:  Biomed Eng Adv       Date:  2022-01-06
  5 in total

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