Purpose: Laser cordectomy (LC) or radiotherapy (RT) is often recommended in the early stage of laryngeal cancer. We conducted perceptual and acoustic analysis to compare sustained vowel and stop consonants since there is no article evaluating both the sustained vowel and stop consonants. Eventually, we might determine which management is superior in terms of speech production.
Subjects And Methods: A total of 28 patients who underwent LC and RT for early T1 glottic cancer were selected. The sustained vowel /a/ and bilabial stop consonants were used to assess the perceptual scores. The fundamental frequency (F), jitter, shimmer and noise-to-harmonic ratio (NHR) levels for sustained vowels were evaluated. Voice onset time (VOT), vowel duration (VD) and closure duration of the bilabial plosives were analyzed. A receiver operating characteristic curve analysis was used to evaluate significant results statistically.
Results: The GRBAS and discrimination scores were not significantly different between two groups. F and jitter were significantly higher in the LC than RT. The cut-off value was statistically higher in the LC group and statistically lower in the RT group. The VOT was significantly longer in the LC than RT. The cut-off value of the /pipida/ VOT was statistically longer in the LC group and statistically shorter in the RT group.
Conclusions: The differences may have been due to muscular fibrosis after RT. Movements of vocal cords with fibrosis were sluggish, when impulsion developed to pronounce the initial /p/ sound, so the VOT was shortened and the VD was longer after RT.
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http://dx.doi.org/10.1080/14015439.2017.1381148 | DOI Listing |
Healthcare (Basel)
January 2025
Department of Computer Science, Institute of Mathematics and Statistics, University of São Paulo (USP), São Paulo 05508-220, SP, Brazil.
Background/objectives: The aim of this paper was to compare voice and speech characteristics between post-COVID-19 and control subjects. The hypothesis was that acoustic parameters of voice and speech may differentiate subjects infected by COVID-19 from control subjects. Additionally, we expected to observe the persistence of symptoms in women.
View Article and Find Full Text PDFJ Clin Med
December 2024
Center of Hearing and Speech, 7 Mokra Street, 05-830 Kajetany, Poland.
Acoustic analysis of voice enables objective assessment of voice to diagnose changes in voice characteristics, and track the progress of therapy. In contrast to subjective assessment, objective measurements provide mathematical results referring to specific parameters and can be analyzed statistically. Changes in the voice of patients with partial deafness (PD) were not widely described in the literature, and recent studies referred to the voice parameters measured in this group of patients only using the multi-dimensional voice program (MDVP) by Kay Pentax.
View Article and Find Full Text PDFBioengineering (Basel)
December 2024
Department of Communication Sciences and Disorders, University of Iowa, Iowa City, IA 52242, USA.
Room reverberation can affect oral/aural communication and is especially critical in computer analysis of voice. High levels of reverberation can distort voice recordings, impacting the accuracy of quantifying voice production quality and vocal health evaluations. This study quantifies the impact of additive simulated reverberation on otherwise clean voice recordings as reflected in voice metrics commonly used for voice quality evaluation.
View Article and Find Full Text PDFMachine learning approaches including deep learning models have shown promising performance in the automatic detection of Parkinson's disease. These approaches rely on different types of data with voice recordings being the most used due to the convenient and non-invasive nature of data acquisition. Our group has successfully developed a novel approach that uses convolutional neural network with transfer learning to analyze spectrogram images of the sustained vowel /a/ to identify people with Parkinson's disease.
View Article and Find Full Text PDFJ Voice
January 2025
Division of Phoniatrics and Pediatric Audiology at the Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054 Erlangen, Germany.
Objectives: This study investigates the use of sustained phonations recorded during high-speed videoendoscopy (HSV) for machine learning-based assessment of hoarseness severity (H). The performance of this approach is compared with conventional recordings obtained during voice therapy to evaluate key differences and limitations of HSV-derived acoustic recordings.
Methods: A database of 617 voice recordings with a duration of 250 ms was gathered during HSV examination (HS).
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