Quantifying the Cepstral Peak Prominence, a Measure of Dysphonia

Heman‐Ackah, Yolanda D.; Sataloff, Robert T.; Laureyns, Griet; Lurie, Deborah; Michael, Deirdre D.; Heuer, Reinhardt J.; Rubin, Adam D.; Eller, Robert; Somasundram, Chandran; Abaza, Mona; Lyons, Karen M.; Divi, Venu; Lott, Joanna; Johnson, Jennifer; Hillenbrand, James

doi:10.1016/j.jvoice.2014.05.005

Cited by 115 publications

(48 citation statements)

References 16 publications

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“…[8][9][10]17 Cepstral peak prominence is an objective measure that has recently shown strong correlations with other objective voice measures but also perceptual measures of voice changes. 18 It has not been studied specifically in the irradiated larynx and is an area that will require focus for future research.…”

Section: Villari and Coureymentioning

confidence: 99%

Management of Dysphonia After Radiation Therapy

Villari

Courey

2015

Otolaryngologic Clinics of North America

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Section: Villari and Coureymentioning

confidence: 99%

Management of Dysphonia After Radiation Therapy

Villari

Courey

2015

Otolaryngologic Clinics of North America

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“…The change in CPP in nasality was also expected, as it has been shown to vary in nasal phrases and in VPI . However, a decrease of 3 dB (equivalent to 25.9%) as phonation changes from vowel to nasal may be clinically significant, particularly if the CPPS is used, given that the mean cutoff threshold of CPPS for connected speech obtained from a similar analyzing program (i.e., ADSV) has been found to be 4.15 dB (SD = 1.73, range = 0.4–7.12) or below 4 dB for pathological voices.…”

Section: Discussionmentioning

confidence: 86%

The Impact of Nasalance on Cepstral Peak Prominence and Harmonics‐to‐Noise Ratio

et al. 2018

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Objectives/Hypothesis Cepstral peak prominence (CPP) has been reported as a reliable measure of dysphonia and a preferred alternative to harmonics‐to‐noise ratio (HNR). However, CPP has been observed to be sensitive to articulatory variation and vocal intensity. The aim of this study was to examine the impact of nasalance on CPP and HNR of voice signals. It was hypothesized that increased nasalance would be associated with decreased CPP. Study Design Within‐subject correlation design. Methods Thirty vocally healthy female participants were recorded reading and producing a vowel in alternation with a nasal consonant while wearing a nasometer for calculation of nasalance. Recorded vowel, nasalized, and nasal segments of speech were used to calculate CPP using Analysis of Dysphonia in Speech and Voice software, and HNR and vocal intensity using Praat software. Results Significant main effects of conditions were observed for CPP. CPP values decreased significantly when phonation changed from vowel to nasalized vowel and to nasal. There was correlation between CPP and nasalance and between CPP and intensity. HNR was slightly higher in the nasal condition than in vowel. There was a weak correlation between HNR and nasalance. No correlation was found between HNR and intensity. Conclusions CPP is sensitive to changes in vocal tract configuration caused by nasalization as well as intensity, whereas HNR is not. Therefore, CPP may reflect the periodicity in source signal or the filtering effects of vocal tract. Further research is needed to clarify the application and interpretation of CPP in clinical practice. Level of Evidence 4 Laryngoscope, 129:E299–E304, 2019

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“…Cepstral peak prominence (CPP) was the only measure extracted directly from the speech signal and has been historically widely used to classify and rate levels of dysphonia [25]. While there is no clear understanding of what the parameter measures, the general findings among the speech pathologists show that the parameter is tied to vocal attributes of breathiness, roughness and hoarseness.…”

Section: Voice Source Featuresmentioning

confidence: 99%

Monitoring Cognitive Workload Using Vocal Tract and Voice Source Features

Magnúsdóttir

Borský

Meier

et al. 2017

Period. Polytech. Elec. Eng. Comp. Sci.

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IntroductionMonitoring cognitive workload in individuals that are performing safety-critical jobs has huge potential, for example in aviation [1]. The relationship between cognitive workload and performance has been well studied [2] and the connection between cognitive workload and physical health has also been highlighted [3]. Clearly, it is crucial to manage cognitive workload in the modern day work environment, both in terms of performance and health. Speech processing offers the ability to monitor cognitive workload in a non-intrusive way, compared to measures such as blood pressure, heart rate, electroencephalogram or electrocardiogram. Measuring voice is easy and recent work has shown very promising results in classifying cognitive workload levels using the speech signal [4][5][6]. Successful design and implementation of such a method would provide a powerful tool to developers of cognitive infocommunications systems [7].The main objective of this work is to provide an independent verification of whether there is a link between increased cognitive workload and changes in the speech signal and, if this link exists, to characterize what part of voice is mostly affected. To do this we conducted a cognitive workload experiment where the set tasks were primarily solved using speech from 98 participants. Each participant read a standard passage of text on a computer screen and solved Stroop tasks with three difficulty levels [8]. A separate classifier of the three difficulty levels was trained for each speaker based on two sets of voice parameters comprising of the vocal tract (VT) and voice source (VS) features respectively. The conclusion is that task load does affect the speech signal and that vocal tract parameters are a better indicator of task level than voice source parameters. The context of the work is presented in Section 2 and the speech processing approach is described in Section 3. The experimental methodology and detailed results are given in Section 4 and 5. The results are summarized in Section 6 and the discussion is continued in Section 7.

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Quantifying the Cepstral Peak Prominence, a Measure of Dysphonia

Cited by 115 publications

References 16 publications

Management of Dysphonia After Radiation Therapy

Management of Dysphonia After Radiation Therapy

The Impact of Nasalance on Cepstral Peak Prominence and Harmonics‐to‐Noise Ratio

Monitoring Cognitive Workload Using Vocal Tract and Voice Source Features

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