• Phonetics and Speech Sciences
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• v.1 no.1
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• pp.77-86
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• 2009

This study observes how the combined intervention program effects on the acquisition reading pronunciation of Korean phonological process words and the acquisition aspects of each phonological process rules to four Korean learners whose first language is Chinese. The training program is the combination of multisensory Auditory, Visual and Kinethetic (AVK) approach, wholistic approach, and metalinguistic approach. The training purpose is to evaluate how accurately they read the words of the phonological process which have fortisization, nasalization, lateralization, intermediate sound /ㅅ/ (/${\int}iot"$/). We access how they read the untrained words which include the four factors above. The intervention effects are analyzed by the multiple probe across subjects design. The results indicate that the combined phonological process rule explanation and the words activity intervention affects the four Chinese subjects in every type of word. The implications of the study are these: First, it suggests the effect of Korean pronunciation intervention in a concrete way. Second, it offers how to evaluate the phonological process and how to train people who are learning Korean language.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.14-18
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• 2023

본 연구는 한국어 음성-텍스트 데이터에서 보편적으로 나타난 휴지의 실현 양상을 분석하고, 이를 토대로 데이터셋을 선별해 보편적이고 규격화된 한국어 휴지 예측을 위한 모델을 제안하였다. 이를 위해 전문적인 발성 훈련을 받은 성우 등의 발화가 녹음된 음성-텍스트 데이터셋을 수집하고 MFA와 같은 음소 정렬기를 사용해 휴지를 라벨링하는 등의 전처리를 하고, 다양한 화자의 발화에서 공통적으로 나타난 휴지를 선별해 학습데이터셋을 구축하였다. 구축된 데이터셋을 바탕으로 LLM 중 하나인 KULLM 모델을 미세 조정하고 제안한 모델의 휴지 예측 성능을 평가하였다.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.21-26
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• 2002

This paper presents the new approach of identifying human emotional states such as anger, happiness, normal, sadness, or surprise. This is accomplished by using discrete duration continuous hidden Markov models(DDCHMM). For this, the emotional feature parameters are first defined from input speech signals. In this study, we used prosodic parameters such as pitch signals, energy, and their each derivative, which were then trained by HMM for recognition. Speaker adapted emotional models based on maximum a posteriori(MAP) estimation were also considered for speaker adaptation. As results, the simulation performance showed that the recognition rates of vocal emotion gradually increased with an increase of adaptation sample number.

• Phonetics and Speech Sciences
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• v.1 no.2
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• pp.37-42
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• 2009

The purpose of the present study was to determine the effect of the management program known as vocal function exercise (VFE) on voice quality. Typical VFE was modified and applied to patients with vocal nodules by controlling intensity of voice and relieving the vocal fold to solve hyperfunctional problems in VFE. Eight female subjects aged between 28 and 54 who had been diagnosed with vocal nodules took part in the study. The patients performed VFEs once a week for eight weeks. Vocal function exercises consist of voice hygiene, respiratory training, phonation training, and glide training. The subjects' voices were analyzed pre and post therapy on the aspects of acoustics, maximum phonation time (MPT), GRBAS, and voice handicap index (VHI). As a result, it was found that fundamental frequency ($F_o$) was significant increased, shimmer decreased remarkably and that noise to harmonic ratio (NHR) lowered obviously in the acoustic parameter. In addition, MPT was increased significantly. The scale of GRBAS indicated significant improvement in grade, roughness, and strained voice. VHI indicated significant improvement in an emotional part. In conclusion, VFE was effective in improving voice quality for patients with vocal nodules.

• The Transactions of the Korea Information Processing Society
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• v.4 no.1
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• pp.280-287
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• 1997

The introduction of phonological knowledge, prosodic information to speech recognition and synthesis systems is very important to build successful spoken language systems. First, related works of computational phonology is overviewed and the theoretical and experimental studies of prosodic structures and boundaries in Korean are summarized. The main focus of this study is to decide which prosodic phrasing trained on a simple recurrent network. The results show information other than phonetic features. This method can be combined with other useful information to predict the boundaries more correctly and to help segmentation, which are vital for the successful speech recognition and synthesis systems.

• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.3-8
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• 1999

Previous variable vocabulary speech recognition systems with context-independent acoustic modeling, could not represent the effect of neighboring phonemes. To solve this problem, we use allophone-based context-dependent acoustic model. This paper describes the method to improve acoustic model of the system effectively. Acoustic model is improved by using allophone clustering technique that uses entropy as a similarity measure and the optimal allophone model is generated by changing the number of allophones. We evaluate performance of the improved system by using Phonetically Optimized Words(POW) DB and PC commands(PC) DB. As a result, the allophone model composed of six hundreds allophones improved the recognition rate by 13% from the original context independent model m POW test DB.

• Phonetics and Speech Sciences
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• v.4 no.4
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• pp.147-154
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• 2012

The purpose of this study is to examine the effect of voice improvement when vocal training, which relaxes the vocal contact, is applied to children with vocal nodules. Subjects included 20 5- to 12-year-old boys with vocal nodules in Otolaryngology and for whom voice therapy had been advised. The vocal therapy was conducted for 40 minutes per a week for a total of eight times. Results were evaluated by videostroboscopy, auditory-perceptual evaluation of GRBAS Scale, aerodynamic test, and acoustic analysis before and after therapy. As a result, first, the size of vocal nodules was reduced and the unstable pattern of vocal contact was improved. Glottic closure was increased and Phase symmetry was decreased during vocal vibration. Mucosal wave was increased and muscle tension of the larynx was reduced. Second, auditory-perceptual evaluation showed that subjects' overall quality of voice improved. GRBAS Scale Evaluation showed that the characteristics of the subjects' voice which were rough, breathy, and strained and breathy were reduced after therapy. Third, the measurements of acoustic parameters showed a statistically significant improvement. The fundamental frequency of the subejects' voice was increased and values of Jitter and Shimmer, NHR, [H1-H2] decreased. Fourth, the maximum phonation time of children was increased. These results imply that vocal relaxation training conducted in this study has a very positive effect to improve the voice of children with vocal nodules.

• Speech Sciences
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• v.13 no.3
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• pp.133-149
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• 2006

This study attempted to compare acoustic parameters, physiological observation and perceptual evaluation values obtained from the treatment and control groups in order to find out which of the self voice feedback therapies was better and which methods to train them were more effective. The experimental group carried out various self voice feedback therapies while the control group did only vocal hygiene. The acoustic measurement and voice manipulation for providing the patients visual, auditory feedback were done by a speech analysis software, Praat. The authors designed vocal hygiene, abdominal respiration and Praat self voice feedback therapies and applied them to 15 patients while applying only one vocal hygiene to 15 of the control group. For the purpose of examining the degree of their voice improvement after the treatment, pre- mid- and final evaluations were made for the two groups at the beginning, the 6th week and immediately after the 8th treatment session. Results of this study were as follows: The treatment group showed much improvement after receiving the voice treatment. In particular, acoustical and physiological indices from the optical endoscopy, pitch variation(Jitter), amplitude variation (Shimmer), maximum phonation time(MPT), and psychoacoustic evaluation showed statistically significant improvements over the control groups.

• Speech Sciences
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• v.8 no.3
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• pp.173-184
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• 2001

The purpose of this study was to examine the effects of manipulating loudness and pitch in terms of speech intelligibility and voice of a patient with Parkinson's Disease. The subject, who was diagnosed as a patient with Parkinson's disease 11 years ago, demonstrated a severely breath voice with low intensity. The accuracy of articulation in consonants was intelligible only at the single word level, and the overall intelligibility in continuous speech was low. The results showed that the subject's articulation accuracy and speech intelligibility was significantly improved after having loudness and pitch training. Habitual Fo, Jitter, Shimmer, Fo tremor, Amp tremor were decreased after training. In addition, the value of HNR also increased after training. It was shown that the changes of these acoustic parameters were closely related to the decrease of breathiness in Parkinson's voice, and this decrease of breathiness affected speech intelligibility considerably. Based on the experimental results, it was claimed that the vocal training by manipulating the loudness and pitch could be highly effective in improving the voice quality and speech intelligibility in Parkinson's Disease.

• The Journal of the Acoustical Society of Korea
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• v.16 no.1
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• pp.96-99
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• 1997

This paper proposes a very fast preprocessor for isolated word recognition. The proposed preprocessor has a small computational cost for extracting candidate words. In the preprocessor, we used a feature sorting algorithm instead of vector quantization to reduce the computational cost. In order to show the effectiveness of our preprocessor, we compared it to a speech recognition system based on semi-continuous hidden Markov Model and a VQ-based preprocessor by computing their recognition performances of a speaker independent isolated word recognition. For the experiments, we used the speech database consisting of 244 words which were uttered by 40 male speakers. The set of speech data uttered by 20 male speakers was used for training, and the other set for testing. As the results, the accuracy of the proposed preprocessor was 99.9% with 90% reduction rate for the speech database.