• Title/Summary/Keyword: Shimmer

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Effects of vocal aerobic treatment on voice improvement in patients with voice disorders (성대에어로빅치료법이 음성장애환자의 음성개선에 미치는 효과)

  • Park, Jun-Hee;Yoo, Jae-Yeon;Lee, Ha-Na
    • Phonetics and Speech Sciences
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    • v.11 no.3
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    • pp.69-76
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    • 2019
  • This study aimed to investigate the effects of vocal aerobic treatment (VAT) on the improvement of voice in patients with voice disorders. Twenty patients (13 males, 7 females) were diagnosed with voice disorders on the basis of videostroboscopy and voice evaluations. Acoustic evaluation was performed with the Multidimensional voice program (MDVP) and Voice Range Profile (VRP) of Computerized Speech Lab (CSL), and aerodynamic evaluation with PAS (Phonatory Aerodynamic System). The changes in F0, Jitter, Shimmer, and NHR before and after treatment were measured by MDVP. F0 range and Energy range were measured with VRP before and after treatment, and the changes in Expiratory Volume (FVC), Phonation Time (PHOT), Mean Expiratory Airflow (MEAF), Mean Peak Air Pressure (MPAP), and Aerodynamic Efficiency (AEFF) with PAS. Videostroboscopy was performed to evaluate the regularity, symmetry, mucosal wave, and amplitude changes of both vocal cords before and after treatment. Voice therapy was performed once a week for each patient using the VAT program in a holistic voice therapy approach. The average number of treatments per patient was 6.5. In the MDVP, Jitter, Shimmer, and NHR showed statistically significant decreases (p < .001, p < .01, p < .05). VRP results showed that Hz and semitones in the frequency range improved significantly after treatment (p < .01, p < .05), as did PAS, FVC, and PHOT (p < .01, p < .001). The results for videostroboscopy, functional voice disorder, laryngopharyngeal reflux, and benign vocal fold lesions were normal. Thus, the VAT program was found to be effective in improving the acoustic and aerodynamic aspects of the voice of patients with voice disorders. In future studies, the effect of VAT on the same group of voice disorders should be studied. It is also necessary to investigate subjective voice improvement and objective voice improvement. Furthermore, it is necessary to examine the effects of VAT in professional voice users.

Acoustic characteristics of speech-language pathologists related to their subjective vocal fatigue (언어재활사의 주관적 음성피로도와 관련된 음향적 특성)

  • Jeon, Hyewon;Kim, Jiyoun;Seong, Cheoljae
    • Phonetics and Speech Sciences
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    • v.14 no.3
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    • pp.87-101
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    • 2022
  • In addition to administering a questionnaire (J-survey), which questions individuals on subjective vocal fatigue, voice samples were collected before and after speech-language pathology sessions from 50 female speech-language pathologists in their 20s and 30s in the Daejeon and Chungnam areas. We identified significant differences in Korean Vocal Fatigue Index scores between the fatigue and non-fatigue groups, with the most prominent differences in sections one and two. Regarding acoustic phonetic characteristics, both groups showed a pattern in which low-frequency band energy was relatively low, and high-frequency band energy was increased after the treatment sessions. This trend was well reflected in the low-to-high ratio of vowels, slope LTAS, energy in the third formant, and energy in the 4,000-8,000 Hz range. A difference between the groups was observed only in the vowel energy of the low-frequency band (0-4,000 Hz) before treatment, with the non-fatigue group having a higher value than the fatigue group. This characteristic could be interpreted as a result of voice abuse and higher muscle tonus caused by long-term voice work. The perturbation parameter and shimmer local was lowered in the non-fatigue group after treatment, and the noise-to-harmonics ratio (NHR) was lowered in both groups following treatment. The decrease in NHR and the fall of shimmer local could be attributed to vocal cord hypertension, but it could be concluded that the effective voice use of speech-language pathologists also contributed to this effect, especially in the non-fatigue group. In the case of the non-fatigue group, the rhamonics-to-noise ratio increased significantly after treatment, indicating that the harmonic structure was more stable after treatment.

Prevalence of Voice Disorders and Characteristics of Korean Voice Handicap Index in the Elderly (노인 음성장애 출현율 및 음성장애지수 특성)

  • Song, Yun-Kyung
    • Phonetics and Speech Sciences
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    • v.4 no.3
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    • pp.151-159
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    • 2012
  • The purpose of this study is to evaluate the prevalence of voice disorders and the Korean voice handicap index in the elderly. For this study, 169 elderly performed two types of questionnaires and vowel /a/ prolongation. Self-reported voice symptoms and the Korean voice handicap index were analyzed and acoustic voice evaluation was performed by MDVP. The results showed that the prevalence of voice disorders in the elderly are significantly higher than that of adults in self-reports. In acoustic evaluation, 32.2% of the male elderly and 40.9% of the female elderly exceeded the thresholds of Jitter (%), Shimmer (%) and NHR. In addition, Korean voice handicap index scores of the female elderly are significantly higher than those of female adults. These findings indicate the high frequency of voice disorders in the elderly and the need to focus on this group. Additional studies on the voice related quality of life for the elderly are needed.

Performance of GMM and ANN as a Classifier for Pathological Voice

  • Wang, Jianglin;Jo, Cheol-Woo
    • Speech Sciences
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    • v.14 no.1
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    • pp.151-162
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    • 2007
  • This study focuses on the classification of pathological voice using GMM (Gaussian Mixture Model) and compares the results to the previous work which was done by ANN (Artificial Neural Network). Speech data from normal people and patients were collected, then diagnosed and classified into two different categories. Six characteristic parameters (Jitter, Shimmer, NHR, SPI, APQ and RAP) were chosen. Then the classification method based on the artificial neural network and Gaussian mixture method was employed to discriminate the data into normal and pathological speech. The GMM method attained 98.4% average correct classification rate with training data and 95.2% average correct classification rate with test data. The different mixture number (3 to 15) of GMM was used in order to obtain an optimal condition for classification. We also compared the average classification rate based on GMM, ANN and HMM. The proper number of mixtures on Gaussian model needs to be investigated in our future work.

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The Efficacy of the Bel canto Singing Technique as a Method of Improving Voice Quality of Vocal Bowing Sulcus Vocalis

  • Yoo, Jae-Yeon;Seo, Dong-Il
    • Phonetics and Speech Sciences
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    • v.3 no.4
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    • pp.103-108
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    • 2011
  • The purpose of this study was to investigate the effects of the Bel canto singing technique on voice quality in patients with vocal bowing and sulcus vocalis. Five patients with vocal bowing, and five patients with sulcus vocalis participated in the study. Each subject was assessed acoustically (Jitter, Shimmer, NNE) in the first and last session. Dr. Speech (version 4.0, Tiger-DRS) was used to compare acoustic parameters of pre- and post-treatment. The Bel canto singing technique consisted of breathing exercises, relaxation exercises, and phonation exercises. The results showed that the Bel canto singing technique tended to be effective on improving voice quality in patients with organic voice disorders.

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A Validity Study on Measurement of Mental Fatigue Using Speech Technology (음성기술을 이용한 정신피로 측정에 관한 타당성 연구)

  • Song, Seungkyu;Kim, Jongyeol;Jang, Junsu;Kwon, Chulhong
    • Phonetics and Speech Sciences
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    • v.5 no.1
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    • pp.3-10
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    • 2013
  • This study proposes a method to measure mental fatigue using speech technology, which has not been used in previous research and is easier than existing complex and difficult methods. It aims at establishing a relationship between the human voice and mental fatigue based on experiments to measure the influence of mental fatigue on the human voice. Two monotonous tasks of simple calculation such as finding the sum of three one digit numbers were used to measure the feeling of monotony and two sets of subjective questionnaires were used to measure mental fatigue. While thirty subjects perform the experiment, responses to the questionnaire and speech data were collected. Speech features related to speech source and the vocal tract filter were extracted from the speech data. According to the results, speech parameters deeply related to mental fatigue are a mean and standard deviation of fundamental frequency, jitter, and shimmer. This study shows that speech technology is a useful method for measuring mental fatigue.

The Effect of Frequency and Intensity of /a/ Phonation on the Result of Acoustic Analysis (발성시 음도 및 강도의 변화가 음성분석검사 결과에 미치는 영향)

  • 손영익;윤영선;권중근;추광철
    • Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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    • v.8 no.1
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    • pp.12-17
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    • 1997
  • Measuring phonatory stability using MDVP(Multi-dimensional voice program, Kay Elemetrics Corp., NJ, USA) are becoming popular in many Korean clinics and laboratories, yet questions about standardization and reference values have remained. The purpose of present study was to examine the effects of frequency and intensity variation on the results of acoustic analysis related to phonatory stability. Twenty young adults(ten females and ten males) were asked to sustain vowel /a/ for more than 3 seconds under 9 different pitch and loudness conditions. Using MDVP, nine voice samples were analyzed, and jitter percent, fundamental frequency variation, shimmer percent, peak amplitude variation, noise to harmonic ratio, amplitude tremor intensity index, and degree of subharmonics were compared. The results showed that intensity changes can significantly affect various phonatory stability measures, and the lowest perturbation values can be obtained from slightly louder(10dB) phonatory condition than comfortable level phonation.

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Speech Emotion Recognition on a Simulated Intelligent Robot (모의 지능로봇에서의 음성 감정인식)

  • Jang Kwang-Dong;Kim Nam;Kwon Oh-Wook
    • MALSORI
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    • no.56
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    • pp.173-183
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    • 2005
  • We propose a speech emotion recognition method for affective human-robot interface. In the Proposed method, emotion is classified into 6 classes: Angry, bored, happy, neutral, sad and surprised. Features for an input utterance are extracted from statistics of phonetic and prosodic information. Phonetic information includes log energy, shimmer, formant frequencies, and Teager energy; Prosodic information includes Pitch, jitter, duration, and rate of speech. Finally a pattern classifier based on Gaussian support vector machines decides the emotion class of the utterance. We record speech commands and dialogs uttered at 2m away from microphones in 5 different directions. Experimental results show that the proposed method yields $48\%$ classification accuracy while human classifiers give $71\%$ accuracy.

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On the Classification of Normal, Benign, Malignant Speech Using Neural Network and Cepstral Method (Cepstrum 방법과 신경회로망을 이용한 정상, 양성종양, 악성종양 상태의 식별에 관한 연구)

  • 조철우
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1998.06e
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    • pp.399-402
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    • 1998
  • 본 논문에서는 환자의 음성을 정상, 양성종양, 악성종양으로 분류하는 실험을 켑스트럼 파라미터를 통한 음원분리와 신경회로망을 이용하여 수행하고 그 결과를 보고한다. 기존의 장애음성 데이터베이스에는 정상음성과 양성종양의 경우만 수록되어 있었고 외국의 환자들을 대상으로 한 경우만 있었기 때문에 국내의 환자들에게 직접 적용할 경우 어떠한 결과가 나올지 예측하기가 어려웠다. 최근 부산대학교 이비인후과팀에서 수집한 국내의 정상, 양성, 악성종양의 경우에 대한 데이터베이스를 분석하고 신경회로망에 의해 분류함으로써 사람의 음성신호만에 의한 후두질환이 식별이 가능하였다. 본 실험에서는 식별 파라미터로 음성신호의 선형예측오차신호에 관한 켑스트럼으로부터 음원비인 HNRR을 구하여 Jitter, Shimmer와 함께 사용하였다. 신경회로망은 입, 출력 층과 한 개의 은닉층을 갖는 다층신경망을 이용하였으며, 식별은 두단계로 나누어 정상과 비정상을 분류한 후 다시 비정상을 양성과 악성으로 분류하였다[1].

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A Study on Characteristics of Children's Voice Preference from Different Pitch (음도 차이에 따른 아동의 선호 음성 특성 연구)

  • Ham, Eun-Seon;Lim, Kyung-Suk;Yi, So-Hee;Kim, Ha-Kyung
    • Speech Sciences
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    • v.15 no.3
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    • pp.175-181
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    • 2008
  • The aim of this study was to survey 'voice preference' of children from among three voice pitches, which are high-pitch, mid-pitch and low pitch, and understand acoustic characteristics of the best voice chosen. To record distinctive pitches, Dr. Speech(ver. 4.0 Tiger Electronics) was used and we analyzed their choices. Also, we measured subglottal air pressure in aerodynamic analyze and phonatory aerodynamic system(Model 6600, KAY) was used. As a result children preferred to the low-pitch yet there was not any difference by sex. We fined them to prefer higher HNR voice to lower jitter and shimmer voice rate.

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