• Speech Sciences
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• v.15 no.3
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• pp.183-201
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• 2008

This study attempted to reveal the physiologic etiology or related factors associated with speech processing by comparing the compensation ability in speech motor control in children with and without articulation disorders. Subjects were 35 children with articulation disorder and 35 children without articulation disorder whose age ranged from 5 to 6 years. They were asked to rapidly repeat /$p^ha$/, /$t^ha$/, /$k^ha$/, /$p^hat^hak^ha$/ diadochokinetic movement while mandible was free and mandible was stabilized with bite block. The results showed that children with articulation disorder revealed significantly greater difference in elapsed time for diadochokinetic movement between mandible free and stabilized state compared to the without articulation disorder group. But the correlation between the percentage of consonants correct and the compensation ability in speech motor control in the articulation disorder group was irrelevant. These results point out to the fact that children with articulation disorder have poor compensation ability in speech motor control compared to the children without articulation disorder. On the other hand, the poor ability does not have any relation with the severity of articulation disorder. These results suggest either general or individual characteristics of children with articulation disorder.

• Journal of Broadcast Engineering
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• v.22 no.2
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• pp.253-256
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• 2017

This paper deals with the implementation of speech disorder detection system based on machine learning classification. Problems with speech are a common early symptom of a stroke or other brain injuries. Therefore, detection of speech disorder may lead to correction and fast medical treatment of strokes or cerebrovascular accidents. The speech disorder system can be implemented by extracting features from the input speech and classifying the features using machine learning algorithms. Ten machine learning algorithms with various scaling methods were used to discriminate speech disorder from normal speech. The detection system was evaluated by the TORGO database which contains dysarthric speech collected from speakers with either cerebral palsy or amyotrophic lateral sclerosis.

• The Journal of Internal Korean Medicine
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• v.25 no.3
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• pp.662-668
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• 2004

Cerebrovascular accident(CVA) is a leading cause of death, and severe sequelae, like motor disturbance, mental disorder, dysphagia, recognition disorder, speech disorder(aphasia) often occur. Most of medical cure about CVA sequelae lay emphasis on motor disturbance, so speech disorder(aphasia) has been neglected. But speech disorder therapy is essential for social rehabiltation. Recently, inside and outside South Korea, various clinical approaches and potential medical cures for speech disorder (aphasia) have been researched. In Korean Medicine, papers pertaining to speech disorders have been but a few. In this study two cases of aphasic stroke patients who were treated for speech and language disorders through Korean medical therapy are reported.

• Phonetics and Speech Sciences
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• v.15 no.2
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• pp.53-59
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• 2023

Detection of children with autism spectrum disorder (ASD) based on speech has relied on predefined feature sets due to their ease of use and the capabilities of speech analysis. However, clinical impressions may not be adequately captured due to the broad range and the large number of features included. This paper demonstrates that the knowledge-driven speech features (KDSFs) specifically tailored to the speech traits of ASD are more effective and efficient for detecting speech of ASD children from that of children with typical development (TD) than a predefined feature set, extended Geneva Minimalistic Acoustic Standard Parameter Set (eGeMAPS). The KDSFs encompass various speech characteristics related to frequency, voice quality, speech rate, and spectral features, that have been identified as corresponding to certain of their distinctive attributes of them. The speech dataset used for the experiments consists of 63 ASD children and 9 TD children. To alleviate the imbalance in the number of training utterances, a data augmentation technique was applied to TD children's utterances. The support vector machine (SVM) classifier trained with the KDSFs achieved an accuracy of 91.25%, surpassing the 88.08% obtained using the predefined set. This result underscores the importance of incorporating domain knowledge in the development of speech technologies for individuals with disorders.

• Korean Journal of Cleft Lip And Palate
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• v.11 no.1
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• pp.1-12
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• 2008

In cleft palate patient, characteristic of speech disorder is the resonance disorder result from velopharyngeal incompetence. Clinically VPI caused by congenital factor as congenital palatal incompetence, submucosal cleft palate, and caused by acquired factor as CNS damage, tumor, palatal palsy. The clinicians more concerned about the speech disorders after cleft palate surgery rather than language pathologist. The resonance disorder devided for hypernasality, hyponasality and nasal emission, but as a rule, hypernasality is typical phenomenon of the resonance disorder. Traditionally clinicians and language pathologists evaluated four-stage or five-stage of hypernasality by subjective assessment. Although language pathologist is well-trained, results of the language level should be different. In late 1980s, Kay Elemetrics Corp. developed nasometer that objective nasalance identified with well-trained language pathologist and originate from nasometer Tonar I and II were developed by Fletcher. Therefore objective nasalance test was possible, the nasometer used in hospital, collage and speech clinic both and home and abroad. Standardization of the cleft palate speech assessment must be settled without delay because of different character result in different language and different assessment results by dialect in same language. In our study, we provide the data base for the standardization of cleft palate speech assessment which through report of objective assessment method, speech therapy effects and problems result in interdisciplinary teamwork by nasometer use in treatment of cleft palate patient.

• Speech Sciences
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• v.13 no.3
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• pp.7-18
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• 2006

Diagnosis of pathological voice is one of the important issues in biomedical applications of speech technology. This study focuses on the discrimination of voice disorder using HMM (Hidden Markov Model) for automatic detection between normal voice and vocal fold disorder voice. This is a non-intrusive, non-expensive and fully automated method using only a speech sample of the subject. Speech data from normal people and patients were collected. Mel-frequency filter cepstral coefficients (MFCCs) were modeled by HMM classifier. Different states (3 states, 5 states and 7 states), 3 mixtures and left to right HMMs were formed. This method gives an accuracy of 93.8% for train data and 91.7% for test data in the discrimination of normal and vocal fold disorder voice for sustained /a/.

• Journal of Biomedical Engineering Research
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• v.29 no.4
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• pp.307-315
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• 2008

In this paper, we developed a visual-auditory cue software for reading training of motor speech disorder patients. Motor speech disorder patients can use the visual and/or auditory cues for reading training and improving their symptom. The software provides some sentences with visual-auditory cues. Our sentences used for reading training are adequately comprised on modulation training according to a professional advice in speech therapy field. To ameliorate reading skills we developed two algorithms, first one is automatically searching the starting time of speech spoken by patients and the other one is removing auditory-cue from the recorded speech that recorded at the same time. The searching of speech starting time was experimented by 10 sentences per 6 subjects in four kinds of noisy environments thus the results is that $7.042{\pm}8.99[ms]$ error was detected. The experiment of the cancellation algorithm of auditory-cue was executed from 6 subjects with 1 syllable speech. The result takes improved the speech recognition rate $25{\pm}9.547[%]$ between before and after cancellation of auditory-cue in speech. User satisfaction index of the developed program was estimated as good.

• Journal of The Korean Society of Integrative Medicine
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• v.6 no.4
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• pp.191-206
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• 2018

Purpose : This study investigated the correlation between speech intelligibility and acoustic measurements of speech sounds produced by the children with speech sound disorders and children without any diagnosed speech sound disorder. Methods : A total of 60 children with and without speech sound disorders were the subjects of this study. Speech samples were obtained by having the subjects? speak meaningful words. Acoustic measurements were analyzed on a spectrogram using the Multi-speech 3700 program. Speech intelligibility was determined according to a listener's perceptual judgment. Results : Children with speech sound disorders had significantly lower speech intelligibility than those without speech sound disorders. The intensity of the vowel /u/, the duration of the vowel /${\omega}$/, and the second formant of the vowel /${\omega}$/ were significantly different between both groups. There was no difference in voice onset time between the groups. There was a correlation between acoustic measurements and speech intelligibility. Conclusion : The results of this study showed that the speech intelligibility of children with speech sound disorders was affected by intensity, word duration, and formant frequency. It is necessary to complement clinical setting results using acoustic measurements in addition to evaluation of speech intelligibility.

• Journal of Korea Entertainment Industry Association
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• v.13 no.3
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• pp.249-258
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• 2019

The health care services are the most basic social institutions that are provided to citizen including disabled persons for improvement of health. However, the study of the difference of health care services according to the speech therapy use in the people with speech-language disorders was insufficient. The aim of this investigation was to compare the awareness of health care services and characteristics of people with speech-language disorders according to speech therapy use. The researchers selected 229 people with language disorder using raw data of National Survey of the Disabled Person (2017). We compared the characteristics and health care services of people with speech-language disorders by distinguishing between speech therapy non-users and speech therapy users. Among the 229 people with language disorder, speech therapy users were 37 persons (16.2%). In comparison with non-users, users were younger, more preschoolers, more family incomes, and intellectual disabilities and autistic disorder were the most common types of disability enrollment. Users had a lower proportion of unmet medical needs than non-users. For the reasons of unmet medical need, there were 6.8% and 6.3% of the "economic reasons" and "communication difficulties" Both users and non-users responded that "disability management services" need to be strengthened by the government. In conclusion, we suggest that access to health care services needs to be increased to lower the barriers of speech therapy use.

• Phonetics and Speech Sciences
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• v.3 no.3
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• pp.173-179
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• 2011

The present study was performed to investigate the intelligibility of voice disorder patients by providing the various background noise levels. Four sets of 12-sentence-stimuli produced by 11 voice disorder patients were prepared, and 5 minute-news from radio broadcasting studio were used as a background noise. 30 listeners assigned intelligibility score of each sentence with visual analog scale. Each set of sentences was provided with 20dB, 10dB, 0dB noise (same intensity with stimuli), and, finally, with no noise. As results, as background noise level increased, intelligibility scores were lowered with statistical significance. Even though in the same severity, more loud background noise showed much lower scores than less loud noise. When 10dB noise was provided, intelligibility scores showed the biggest difference among the degree of severity.