• Phonetics and Speech Sciences
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• v.9 no.4
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• pp.107-114
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• 2017

The purpose of the current study was to compare selected acoustic and electroglottographic measures (closed quotient, pitch, and loudness) among vowel phonation, traditional voiced lip trill ($VLT_T$), modified voiced lip trill methods ($VLT_M$). A total of 21 participants without voice complaints produced 4-second long samples using each phonation method. Results indicated that mean closed quotient of $VLT_M$ was higher than that of vowel phonation and $VLT_T$, while its range and standard deviation measures were higher than those of vowel phonation. Mean, range, standard deviation, maximum of pitch measures of $VLT_M$ were higher than those of vowel phonation. Lastly, mean and maximum loudness of the $VLT_M$ were higher than $VLT_T$. In conclusion, the current data indicate the possibility to use the $VLT_M$ as a training method for singing or a strategy to facilitate generalization effect of voice therapy. Current results also reflect the necessity for further study pertaining to the long-term effect of the $VLT_M$ training method. Clinical implications are discussed.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.13 no.1
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• pp.28-32
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• 2002

Background and Objective : Classical singing students who have received in systematic voice training appeared distinctive voice characteristics compared to normal people who have not received in systematic voice training. The purpose of this study was to determine the correlation between acoustic parameters and Electroglottography(EGG) parameters in two groups(ordinary college students vs. classical singing students group). Materials and Methods : The 80 ordinary college students and 65 classical singing students participated in this study by utilizing Dr. speech program to obtain acoustic measurements and physiologic measurements simultaneously. The Pearson correlation coefficient was used to find the correlation between acoustic parameters and EGG parameters in two groups(ordinary college students group and classical singing students group). Results : The results of the study were as follows : First, there was no correlation between Jitter and EGG Jitter in ordinary college students group, but there was strong correlation between Jitter and EGG Jitter in classical singing students group. Second, there was no correlation between Shimmer and EGG Shimmer in ordinary college students group, but there was strong correlation between Shimmer and EGG Shimmer in classical singing students group. Third, there was no correlation between Harmonic to Noise Ratio(HNR) and EGG HNR in ordinary college students group, but there was strong correlation between HNR and EGG HNR in classical singing students group. Finally, there was no correlation between Normalized Noise Energy(NNE) and EGG NNE in two groups.

• Journal of The Korean Association of Information Education
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• v.23 no.5
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• pp.491-497
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• 2019

As the world develops into a global society, more and more people want to speak foreign languages fluently. To speak fluently, you must have sufficient training in speaking, which requires a dialogue partner. Recently, it is expected that the development of voice recognition information technology will enable the development of a system for conducting foreign language speaking training without human beings from the other party. In this study, a test bed system for foreign language speaking training was developed and applied to elementary school classes. Elementary school students were asked to present their English conversation situation and conduct speaking training. Then, satisfaction with the system and potential for continuous utilization were surveyed. The system developed in this study has been identified as helpful for the training of learning to speak a foreign language.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.13-20
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• 2005

In this paper, I recognized Korean isolated words using CVEM which is suggested by M. Bilginer et al. CVEM is an algorithm which is easy to extract the common properties from training voice signals and also doesn't need complex calculation. In addition CVEM shows high accuracy in recognition results. But, CVEM has couple of problems which are impossible to use for many training voices and no discriminant information among extracted common vectors. To get the optimal common vectors from certain voice classes, various voices should be used for training. But CVEM is impossible to get continuous high accuracy in recognition because CVEM has a limitation to use many training voices and the absence of discriminant information among common vectors can be the source of critical errors. To solve above problems and improve recognition rate, k-clustering subspace method and DCVEM suggested. And did various experiments using voice signal database made by ETRI to prove the validity of suggested methods. The result of experiments shows improvements in performance. And with proposed methods, all the CVEM problems can be solved with out calculation problem.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.14 no.2
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• pp.88-93
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• 2003

Whether respiratory muscle training is of benefit to the singing students is controversial. The purpose of the study is to investigate pulmonary function and the maximal inspiratory(MIP) and expiratory pressure(MET), and maximum phonation time in five female singing students before and after the specially programmed respiratory muscle training during 2 months. All singing students had average 4.8 years of formal classical voice training. Respiratory muscle training machine (Ultrabreath) was used to train respiratory muscle. Pulmonary function test data on simple pulmonary function, flow volume curve, static lung volumes are obtained from Vmax 6200. The MIP and MEP were measured using Spirovis, and the MPT were measured using hand-held stopwatch. Any pulmonary function test variables are not changed after respiratory muscle training. However, MIP and MEP were significantly increased between before and after respiratory muscle training. MPT increased significantly after training, compared to the pre-trained. MIP, MEP, and MPT after training in female singing students were 26%, 25% and 33% higher than those before training. The result indicated that the specially programmed respiratory muscle training is beneficial to improve respiratory muscle strength and vocal function without an increment in pulmonary function.

• The Journal of the Korea Contents Association
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• v.11 no.9
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• pp.407-413
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• 2011

Distinguishing aphasia in stroke patients and observing the subtle linguistic characteristics associated with it primarily requires the use of instruments that provide reliable assessment results. Additionally, examiners should be fully aware of how to use those instruments. This study examined 46 stroke patients for aphasia and assessed the reliability of their diagnoses according to examiners whose medical fields were different from each other. Furthermore, a comparison was made between the reliability before training and that after training. To this end, 46 stroke patients were tested for aphasia and in terms of their speech disorder degree by 3 groups, each of which consisted of 12 professionals (3 SLP, 3 neurologist, and 3 nurse). In the result, a rating of 'acceptable' was given for speech intelligibility tasks and the voice quality of /ah-/ prolongation, and other sub-tests were marked as 'good-excellent' by the experts with different areas of medical expertise. For the tasks marked as 'acceptable', the subjects were video-trained for 3 weeks and the differences were compared before and after their training. Consequently, the differences in the examiners' ratings in the speech intelligibility tasks showed a significant decrease and the accuracy of their voice quality ratings showed a significant increase. In the result of research on the correlation between the accuracy of the sub-test ratings and the amount of clinic experience, speech therapists developed more accuracy in rating a picture description task and a speech intelligibility task as their experience accumulated. Meanwhile, doctors and nurses showed more accurate ratings in picture description tasks with greater clinical experience. The results of this study suggest that assessing the neurologic-communicative disorders of stroke patients requires ongoing training and experience, especially for speech disorders. It was also found that the rating reliability in this case could be improved by training.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1115-1120
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• 2003

The present paper shows the possible development of particle swarm optimization (PSO) based fuzzy-neural networks (FNN) which can be employed as an important building block in real life robot systems, controlled by voice-based commands. The PSO is employed to train the FNNs which can accurately output the crisp control signals for the robot systems, based on fuzzy linguistic spoken language commands, issued by an user. The FNN is also trained to capture the user spoken directive in the context of the present performance of the robot system. Hidden Markov Model (HMM) based automatic speech recognizers are developed, as part of the entire system, so that the system can identify important user directives from the running utterances. The system is successfully employed in a real life situation for motion control of a redundant manipulator.

• The Journal of the Acoustical Society of Korea
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• v.34 no.3
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• pp.227-233
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• 2015

In this paper, we propose music and voice separation using kernel sptectrogram models backfitting based on log-spectral amplitude estimator. The existing method separates sources based on the estimate of a desired objects by training MSE (Mean Square Error) designed Winer filter. We introduce rather clear music and voice signals with application of log-spectral amplitude estimator, instead of adaptation of MSE which has been treated as an existing method. Experimental results reveal that the proposed method shows higher performance than the existing methods.

• Journal of Sensor Science and Technology
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• v.22 no.2
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• pp.156-161
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• 2013

This study was aimed to implement the electroglottography (EGG) system for analyzing fundamental frequency of the phonation. EGG was recorded from the conductance between ring electrodes attached to the neck skin area near thyroid cartilage with high frequency carrier electric signals during vocalization, and voice signal was recorded with microphone simultaneously. EGG and voice signals were transmitted to the audio port in PC and recorded with stereo sound recording program. From the digitized data, several parameters such as pitch, jitter, shimmer, CQ and SQ were analyzed from the vowel sounds. For the voice training, sound fundamental frequency was displayed during the vocalization and singing a song using pitches analyzed from the EGG. The system implemented in this study could be used for vocal exercise.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.335-338
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• 2010

A new method that improves the performance of large scale voice dialling system is presented using speaker adaptation. Since SI (Speaker Independent) based speech recognition system with phoneme HMM uses only the phoneme string of the input sentence, the storage space could be reduced greatly. However, the performance of the system is worse than that of the speaker dependent system due to the mismatch between the input utterance and the SI models. A new method that estimates the phonetic string and adaptation vectors iteratively is presented to reduce the mismatch between the training utterances and a set of SI models using speaker adaptation techniques. For speaker adaptation the stochastic matching methods are used to estimate the adaptation vectors. The experiments performed over actual telephone line shows that proposed method shows better performance as compared to the conventional method. with the SI phonetic recognizer.