• Dementia and Neurocognitive Disorders
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• v.23 no.1
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• pp.1-10
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• 2024

Background and Purpose: Voice, reflecting cerebral functions, holds potential for analyzing and understanding brain function, especially in the context of cognitive impairment (CI) and Alzheimer's disease (AD). This study used voice data to distinguish between normal cognition and CI or Alzheimer's disease dementia (ADD). Methods: This study enrolled 3 groups of subjects: 1) 52 subjects with subjective cognitive decline; 2) 110 subjects with mild CI; and 3) 59 subjects with ADD. Voice features were extracted using Mel-frequency cepstral coefficients and Chroma. Results: A deep neural network (DNN) model showed promising performance, with an accuracy of roughly 81% in 10 trials in predicting ADD, which increased to an average value of about 82.0%±1.6% when evaluated against unseen test dataset. Conclusions: Although results did not demonstrate the level of accuracy necessary for a definitive clinical tool, they provided a compelling proof-of-concept for the potential use of voice data in cognitive status assessment. DNN algorithms using voice offer a promising approach to early detection of AD. They could improve the accuracy and accessibility of diagnosis, ultimately leading to better outcomes for patients.

• MALSORI
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• no.67
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• pp.33-60
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• 2008

The aim of this study is to show the differences in acoustic parameters between a pathological voice /a/ caused by vocal polyp and a normal voice /a/ produced after LMS (Laryngeal Microscopic Surgery). It was expected that voices of two kinds could be analyzed effectively in terms of HNR in specific frequency bands than in all frequency bands. For this study, 10 patients' voice were recorded before and after LMS and then were manipulated in terms of four acoustic parameter. It was found out that (a) frequency bands of 500Hz in the range of 1,000Hz to 4,000Hz were very useful to obtain HNR values; (b) frequency bands in the range of 1,248Hz to 5,500Hz on a log scale were very useful to obtain HNR values; (c) F0 dropped after LMS but not significantly; (d) the bandwidth of the second formant (B2) decreased significantly after LMS, while that of the first formant (B1) decreased after LMS but not significantly.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.16 no.1
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• pp.5-9
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• 2005

Background and Objectives : Glottal area waveform(GAW) shows the plot of glottal area versus time through the 1 cycle. This study is designed to see how it can be applied to laryngeal patients. Material and Methods : A GAW analysis was peformed on 11 patients before and after surgery and 22 persons without laryngeal problems were recruited for control. Acoustic and aerodynamic analysis with VHI(voice handicap index) evaluation were performed. Results. Significant changes in baseline offset, gross closing rate and VHI were observed postoperatively. Other parameters were changed but insignificant. Conclusion : GAW maybe used to evaluate patient with voice problems.

• Speech Sciences
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• v.15 no.2
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• pp.101-110
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• 2008

The purpose of this study was to investigate the speech intelligibility of voice disordered patients when we consider the severity and utterance level as variables. Based on the severity level, 12 patients were divided into three groups, G1, G2, and G3 group, respectively. Words, phrases and sentences produced by the speakers were judged by four listeners with normal hearing, and we compared the intelligibility scores of the three groups. As a result, the speech intelligibility was decreased as the severity level was increased, and the difference was statistically significant. However, the mean difference among words, phrases and sentences was not significant, and the variation of intelligibility according to the utterance level was not under the regular rules.

• Speech Sciences
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• v.10 no.3
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• pp.29-36
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• 2003

The purposes of this study was to conduct a correlational analysis among $F_^{0}$, Jitter, Shimmer, and NHR (HNR), and NNE estimated by three speech analysis softwares, MDVP, Praat and Dr. Speech. Thirty females and 15 males with normal voice participated in the study. We used Sound Forge 6.0 to record their voice. MDVP, Praat and Dr. Speech were used to measure the acoustic parameters. The Pearson correlation coefficient was determined through a statistical analysis. The results came out as follows: Firstly, there was a strong correlation between $F_^{0}$ and Shimmer of both instruments. However, there was no correlation between Jitter of both instruments. Secondly, Shimmer showed a stronger correlation with HNR, NHR, and NNE than Jitter. Therefore, Shimmer was considered to be more useful and sensitive parameter to identify dysphonic voice compared to jitter.

• Speech Sciences
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• v.11 no.4
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• pp.185-195
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• 2004

Spastic dysarthria is a motor speech disorder produced by a damage to the direct (pyramidal) and indirect (extrapyramidal) pathways of the central nervous system. This study attempted to determine the influences of the severity of spastic dysarthria on the stability of voice. A sustained /a/, /a/ produced at the beginning of a sentence and at the end of the sentence were analyzed. The Praat 4.0.51 was used for analysis. The results showed a significant difference between the severe spastic dysarthric group and normal group matched by age and sex at the beginning and the end of the sentence. In addition, the severe group showed a significant difference between the first /a/ and the second /a/ at the end of sentence.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5541-5554
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• 2018

A voice is one of the most significant non-verbal elements for communication. Disorders in vocal organs, or habitual muscular setting for articulatory cause vocal disorders. Therefore, by analyzing the vocal disorders, it is possible to predicate vocal diseases. In this paper, a method of predicting vocal disorders using the jitter, shimmer, and harmonics-to-noise ratio (HNR) extracted from vocal records is proposed. In order to extract jitter, shimmer, and HNR, one-second's voice signals are recorded in 44.1khz. In an experiment, 151 voice records are collected. The collected data set is clustered using cobweb clustering method. 21 classes with 12 leaves are resulted from the data set. According to the semantics of jitter, shimmer, and HNR, the class whose centroid has lowest jitter and shimmer, and highest HNR becomes the normal vocal group. The risk of vocal disorders can be predicted by measuring the distance and direction between the centroids.

• Advances in nano research
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• v.15 no.3
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• pp.239-251
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• 2023

In the present study, we aim to use nanotechnology sensors/actuators to capture pressure and frequency of voice singers and to send signals for improving breathing pressure. In this regard, a circular composite structure having 3 different layers are used. The core layer is nano-composite material reinforced with graphene nanoplatelets. The face sheets are piezo electric materials connected to electrical circuit capable of measuring and applying voltage to the piezoelectric layers. This sensors have extremely smaller size than conventional sensors attached to the neck of singer and, hence, minimizes the influences on the output voice of the singer. A brief theoretical framework are presented for nonlocal strain gradient theory and geometry of the sensor is described in detail. The controlling procedure along with experimental results on 20 amateur and professional singer participants are also presented. The results of the study indicate that the participants could gain benefit from the device for improving their ability in phonation and keeping their frequency at a constant level although they have difficulty in the beginning of the experiment getting used to the device.

• Phonetics and Speech Sciences
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• v.6 no.3
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• pp.49-56
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• 2014

This research compared the features of respiration and phonation between practical musicology students and general male students, according to their smoking status. Participants of this research are 15 practical musicology male students attending ${\bigcirc}{\bigcirc}$ university and 16 general ${\bigcirc}{\bigcirc}{\bigcirc}$ university students. The participants, both non-smokers and smokers with 5-years of smoking history have no history of voice disease in any case and have normal cognitive functions. The results indicated that, first, there is not a notable difference in the respiratory activity status(FVC, FEV1, FEV1/FVC), regardless of major and smoking status. In MPT, even though there is no significant difference in accordance with their majors, considering smoking status, the smoker group was shorter than non-smoker group significant difference statistically (p<.01). Second, the divisions of participants' major did not show significant difference in Fo, jitter, shimmer, and NHR in the vowel prolongation task. However, the smoker group showed a significantly higher degree of jitter and shimmer than the non-smoker group (p<.05) as Fo and NHR shows no difference. In the case of VRP, maximum frequency and frequency range of the practical group are significantly higher than normal group statistically (p<.001). Moreover, although the difference of the minimum frequency shown at the statistic is not significant, practical group showed a higher tendency of frequency than normal group (p=.051). In conclusion, even though there is no difference in respiratory activity between the smoker group and non-smoker group, the MPT of the smoker group is shorter than that of non-smoker group. In addition, the smoker group showed a higher degree of jitter and shimmer than the non-smoker group. MPT is related to the valve action of vocal fold that passes through the glottis. Thus, it is interpreted that the smoker group has a lower quality of voice and valve action of the vocal fold. Also, the practical group has a higher degree of maximum frequency and frequency range than the normal group. This research can function as basic data for vocal characteristics for the majors in relation to the voice-specializing.

• Speech Sciences
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• v.9 no.3
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• pp.133-140
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• 2002

The purpose of this study was to investigate any changes in acoustic qualities of voice as ,a function of nasalance, in order to determine the relationship between vocal quality and nasalance. Twenty normal subjects (10 males and 10 females) vocalized /a/, /$\tilde{a}$/, and /a $\eta$/. The changes in nasalance and acoustic characteristics of the voice were analyzed by Nasometer (Model 6200-3, Kay Elemetrics, co) and Dr, Speech 4.0 (Tiger Electronics, Co), respectively. One-way ANOVA was used to examine any changes in jitter, shimmer, harmonics-to-noise ratio, and normalized noise energy relative to the nasalance in 3 types of vocalization. The Person r correlation coefficient was used to identify the relationship between the nasalance and the vocal quality. There was no statistically significant changes in jitter, shimmer, HNR and NNE. The jitter, however, tended to increase as the nasalance socre increased, compared to the other vocal parameters. In addition, the NNE showed an increase on / $\tilde{a}$/, and /a $\eta$/, more on the /a $\eta$/. Thus, it was speculated that NNE could be used to identify or screen resonant disorders with hypernasality