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Cepstral and entropy analyses in vowels excerpted from continuous speech of dysphonic and control speakers
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH. (TMH)
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH. (TMH)ORCID iD: 0000-0002-3323-5311
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2017 (English)In: Proceedings of the Annual Conference of the International Speech Communication Association, Interspeech 2017 / [ed] ISCA, International Speech Communication Association, 2017, Vol. 2017, p. 1814-1818Conference paper, Published paper (Refereed)
Abstract [en]

There is a growing interest in Cepstral and Entropy analyses of voice samples for defining a vocal health indicator, due to their reliability in investigating both regular and irregular voice signals. The purpose of this study is to determine whether the Cepstral Peak Prominence Smoothed (CPPS) and Sample Entropy (SampEn) could differentiate dysphonic speakers from normal speakers in vowels excerpted from readings and to compare their discrimination power. Results are reported for 33 patients and 31 controls, who read a standardized phonetically balanced passage while wearing a head mounted microphone. Vowels were excerpted from recordings using Automatic Speech Recognition and, after obtaining a measure for each vowel, individual distributions and their descriptive statistics were considered for CPPS and SampEn. The Receiver Operating Curve analysis revealed that the mean of the distributions was the parameter with the highest discrimination power for both CPPS and SampEn. CPPS showed a higher diagnostic precision than SampEn, exhibiting an Area Under Curve (AUC) of 0.85 compared to 0.72. A negative correlation between the parameters was found (Spearman; p = - 0.61), with higher SampEn corresponding to lower CPPS. The automatic method used in this study could provide support to voice monitorings in clinic and during individual's daily activities.

Place, publisher, year, edition, pages
International Speech Communication Association, 2017. Vol. 2017, p. 1814-1818
Series
Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, ISSN 2308-457X
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-211649DOI: 10.21437/Interspeech.2017-335Scopus ID: 2-s2.0-85039155375OAI: oai:DiVA.org:kth-211649DiVA, id: diva2:1130222
Conference
18th Annual Conference of the International Speech Communication Association, INTERSPEECH 2017, Stockholm, Sweden, 20 August 2017 through 24 August 2017
Note

QC 20170919

Available from: 2017-08-08 Created: 2017-08-08 Last updated: 2018-01-09Bibliographically approved

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Selamtzis, AndreasSalvi, Giampiero
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
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  • vancouver
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More styles
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  • de-DE
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  • Other locale
More languages
Output format
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  • asciidoc
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