• Title/Summary/Keyword: Speech speed

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Relationship between Changes in Manic Symptoms and in Thyroid Hormone Level (조증 증상 변화와 갑상선 호르몬 변화의 관계)

  • Shin, Jong-Ho;Woo, Kwang-Eun;Park, Jin-Han
    • Korean Journal of Psychosomatic Medicine
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    • v.4 no.1
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    • pp.37-43
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    • 1996
  • This study was designed to investigate the relationship between changes in manic symptoms and in thyroid hormone level in manic patients. Thyroid hormones(T3, T4) and TSH were measured, and Young's Mania Rating Scale(YMRS) was scored in twenty manic inpatients, at the time of admission and 6 weeks later. Mean value of T3 was slightly increased(increase : 9, decrease : 11). Mean value of T4 was fairly decreased(increase 4, decrease 16), while that of TSH was increased(increase 14, decrease : 6). Mean total score of YMRS was fairly decreased and mean values of each eleven subscales were decreased. Subjects were classified as increased, decreased and unchanged group for each thyroid hormones. for T3, there was statistically significant differences in YMRS subscale of 6(speech : speed/amount), 7(language, thought disturbance) and 10(appereance) between 3 groups. With the above results, the changes of manic symptom during the course of illness could probably be indicated by the thyroid hormon change, and manic symptoms could be classified as subtypes in terms of thyroid hormone change.

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Korean Phoneme Recognition Using Self-Organizing Feature Map (SOFM 신경회로망을 이용한 한국어 음소 인식)

  • Jeon, Yong-Koo;Yang, Jin-Woo;Kim, Soon-Hyob
    • The Journal of the Acoustical Society of Korea
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    • v.14 no.2
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    • pp.101-112
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    • 1995
  • In order to construct a feature map-based phoneme classification system for speech recognition, two procedures are usually required. One is clustering and the other is labeling. In this paper, we present a phoneme classification system based on the Kohonen's Self-Organizing Feature Map (SOFM) for clusterer and labeler. It is known that the SOFM performs self-organizing process by which optimal local topographical mapping of the signal space and yields a reasonably high accuracy in recognition tasks. Consequently, SOFM can effectively be applied to the recognition of phonemes. Besides to improve the performance of the phoneme classification system, we propose the learning algorithm combined with the classical K-mans clustering algorithm in fine-tuning stage. In order to evaluate the performance of the proposed phoneme classification algorithm, we first use totaly 43 phonemes which construct six intra-class feature maps for six different phoneme classes. From the speaker-dependent phoneme classification tests using these six feature maps, we obtain recognition rate of $87.2\%$ and confirm that the proposed algorithm is an efficient method for improvement of recognition performance and convergence speed.

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A Study on the Development Plan to Increase Supplement of Voice over Internet Protocol (인터넷전화의 보급 확산을 위한 발전방안에 관한 연구)

  • Park, Jae-Yong
    • Management & Information Systems Review
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    • v.28 no.3
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    • pp.191-210
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    • 2009
  • Internet was first designed only for sending data, but as the time passed, internet started to evolve into a broadband multi-media web that is capable of transmitting sound, video, high-capacity data and more due to the demands of internet users and the rapid changing internet-communication technology. Domestically, in January, 2000 Saerom C&T, launched a free VoIP, but due to limited ways of conversation(PC to PC) and absence of a revenue model, and bad speech quality, it had hit it's growth limit. This research studied VoIP based on technological enhancement in super-speed internet. According to IDC, domestic internet market's size was 80,800 million in 2008, and it formed a percentage of 12.5% out of the whole sound-communication market. in case of VoIP, it is able to maximize it's profit by connecting cable and wireless network, also it has a chance of becoming firm-concentrated monopoly market by fusing with IPTV. Considering the fact that our country is insignificant in MVNO revitalization, regulating organizations will play a significant roll on regulating profit between large and small businesses. Further research should be done to give VoIP a secure footing to prosper and become popularized.

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Improvement of Recognition Speed for Real-time Address Speech Recognition (실시간 주소 음성인식을 위한 인식 시스템의 인식속도 개선)

  • Hwang Cheol-Jun;Oh Se-Jin;Kim Bum-Koog;Jung Ho-Youl;Chung Hyun-Yeol
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.74-77
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    • 1999
  • 본 논문에서는 본 연구실에서 개발한 주소 음성인식 시스템의 인식 속도를 개선시키기 위하예 새로운 가변 프루닝 문턱치를 적용하는 방법을 제안하고 실험을 통하여 그 유효성을 확인하였다. 기존의 가변 프루닝 문턱치는 일정 프레임이 경과하면 일정 값을 가진 문턱치를 계속하여 감소시켜나가는 방법을 반복하기 때문에, 불필요한 탐색공간을 탐색하게 된다. 본 논문에서 새로이 제안하는 가변 프루닝 문턱치를 채용하는 방법은 처음 일정 구간이 경과되면 일정 문턱치를 감소시키나, 다음 일정 프레임에서는 탐색되어야할 후보에 따라서 문턱치를 변화시켜 프루닝시키기 때문에 탐색공간을 효과적으로 감소시킬 수 있다. 제안된 방법의 유효성을 확인하기 위하여, 본 연구실에서 개발한 한국어 주소 입력 시스템에 적용하였다. 이 시스템은 48개의 연속 HMM 유사음소단위(Phoneme Like Units; PLUs)를 인식의 기본단위로 하고, .사용환경 변화에 의한 인식성능의 저하를 최소화하기 위해 최대사후 확률추정법(Maximum A Posteriori Probability Estimation; MAP)을 사용하며, 인식알고리즘으로는OPDP(One Pass Dynamic Programming)법을 이용하고 있다. 남성화자 3인에 의한 75개의 연결주소명을 이용하여 인식 실험을 수행한 결과 고정 프루닝 문턱치를 적용한 경우 인식률은 평균 $96.0\%$, 인식 시간은 5.26초였고, 기존의 가변 프루닝 문턱치의 경우 인식률은 평균 $96.0\%$, 인식 시간은 5.1초인 데 비하여, 새로운 가변 프루닝 문턱치를 적용찬 경우에는 인식률 저하없이 인식 시간이 4.34초로, 기존에 비해 각각 0.92초, 0.76초 인식 시간이 감소되어 제안한 방법의 유효성을 확인할 수 있었다.는 달리 각 산란 영역에서 그 지수는 1씩 작은 값을 갖는다.향에 따라 음장변화가 크게 다를 것이 예상되므로 이를 규명하기 위해서는 궁극적으로 3차원적인 음장분포 연구가 필요하다. 음향센서를 해저면에 매설할 경우 수충의 수온변화와 센서 주변의 수온변화 사이에는 어느 정도의 시간지연이 존재하게 되므로 이에 대한 영향을 규명하는 것도 센서의 성능예측을 위해서 필요하리라 사료된다.가지는 심부 가스의 개발 성공률을 증가시키기 위하여 심부 가스가 존재하는 지역의 지질학적 부존 환경 및 조성상의 특성과 생산시 소요되는 생산비용을 심도에 따라 분석하고 생산에 수반되는 기술적 문제점들을 정리하였으며 마지막으로 향후 요구되는 연구 분야들을 제시하였다. 또한 참고로 현재 심부 가스의 경우 미국이 연구 개발 측면에서 가장 활발한 활동을 전개하고 있으며 그 결과 다수의 신뢰성 있는 자료들을 확보하고 있으므로 본 논문은 USGS와 Gas Research Institute(GRI)에서 제시한 자료에 근거하였다.ऀĀ耀Ā삱?⨀؀Ā Ā?⨀ጀĀ耀Ā?돀ꢘ?⨀硩?⨀ႎ?⨀?⨀넆돐쁖잖⨀쁖잖⨀/ࠐ?⨀焆덐瀆倆Āⶇ퍟ⶇ퍟ĀĀĀĀ磀鲕좗?⨀肤?⨀⁅Ⴅ?⨀쀃잖⨀䣙熸ጁ↏?⨀

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Physiologic Phonetics for Korean Stop Production (한국어 자음생성의 생리음성학적 특성)

  • Hong, Ki-Hwan;Yang, Yoon-Soo
    • Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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    • v.17 no.2
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    • pp.89-97
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    • 2006
  • The stop consonants in Korean are classified into three types according to the manner of articulation as unaspirated (UA), slightly aspirated (SA) and heavily aspirated (HA) stops. Both the UA and the HA types are always voiceless in any environment. Generally, the voice onset time (VOT) could be measured spectrographically from release of consonant burst to onset of following vowel. The VOT of the UA type is within 20 msec of the burst, and about 40-50 msec in the SA and 50-70 msec in the HA. There have been many efforts to clarify properties that differentiate these manner categories. Umeda, et $al^{1)}$ studied that the fundamental frequency at voice onset after both the UA and HA consonants was higher than that for the SA consonants, and the voice onset times were longest in the HA followed by the SA and UA. Han, et $al^{2)}$ reported in their speech synthesis and perception studies that the SA and UA stops differed primarily in terms of a gradual versus a relatively rapid intensity build-up of the following vowel after the stop release. Lee, et $al^{3)}$ measured both the intraoral and subglottal air pressure that the subglottal pressure was higher for the HA stop than for the other two stops. They also compared the dynamic pattern of the subglottal pressure slope for the three categories and found that the HA stop showed the most rapid increase in subglottal pressure in the time period immediately before the stop release. $Kagaya^{4)}$ reported fiberscopic and acoustic studies of the Korean stops. He mentioned that the UA type may be characterized by a completely adducted state of the vocal folds, stiffened vocal folds and the abrupt decreasing of the stiffness near the voice onset, while the HA type may be characterized by an extensively abducted state of the vocal folds and a heightened subglottal pressure. On the other hand, none of these positive gestures are observed for the SA type. Hong, et $al^{5)}$ studied electromyographic activity of the thyroarytenoid and posterior cricoarytenoid (PCA) muscles during stop production. He reported a marked and early activation of the PCA muscle associated with a steep reactivation of the thyroarytenoid muscle before voice onset in the production of the HA consonants. For the production of the UA consonants, little or no activation of the PCA muscle and earliest and most marked reactivation of the thyroarytenoid muscle were characteristic. For the SA consonants, he reported a more moderate activation of the PCA muscle than for the UA consonant, and the least and the latest reactivation of the thyroarytenoid muscle. Hong, et $al^{6)}$ studied the observation of the vibratory movements of vocal fold edges in terms of laryngeal gestures according to the different types of stop consonants. The movements of vocal fold edges were evaluated using high speed digital images. EGG signals and acoustic waveforms were also evaluated and related to the vibratory movements of vocal fold edges during stop production.

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Object Tracking Method using Deep Learning and Kalman Filter (딥 러닝 및 칼만 필터를 이용한 객체 추적 방법)

  • Kim, Gicheol;Son, Sohee;Kim, Minseop;Jeon, Jinwoo;Lee, Injae;Cha, Jihun;Choi, Haechul
    • Journal of Broadcast Engineering
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    • v.24 no.3
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    • pp.495-505
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    • 2019
  • Typical algorithms of deep learning include CNN(Convolutional Neural Networks), which are mainly used for image recognition, and RNN(Recurrent Neural Networks), which are used mainly for speech recognition and natural language processing. Among them, CNN is able to learn from filters that generate feature maps with algorithms that automatically learn features from data, making it mainstream with excellent performance in image recognition. Since then, various algorithms such as R-CNN and others have appeared in object detection to improve performance of CNN, and algorithms such as YOLO(You Only Look Once) and SSD(Single Shot Multi-box Detector) have been proposed recently. However, since these deep learning-based detection algorithms determine the success of the detection in the still images, stable object tracking and detection in the video requires separate tracking capabilities. Therefore, this paper proposes a method of combining Kalman filters into deep learning-based detection networks for improved object tracking and detection performance in the video. The detection network used YOLO v2, which is capable of real-time processing, and the proposed method resulted in 7.7% IoU performance improvement over the existing YOLO v2 network and 20 fps processing speed in FHD images.

Audiobook Text Shaping for Synesthesia Voice Training - Focusing on Paralanguages - (오디오북 텍스트 형상화를 위한 공감각적 음성 훈련 연구 - 유사언어를 활용하여 -)

  • Cho, Ye-Shin;Choi, Jae-Oh
    • Journal of Korea Entertainment Industry Association
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    • v.13 no.8
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    • pp.167-180
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    • 2019
  • The purpose of this study is to find out the results of synesthesia speech training using similar language for shaping audiobook text. The audiobook text for training uses Tolstoy's work, and uses similar language of tone, tone, pose, speed, intonation, accent, and expression of emotions. The participants who ten visually impaired trainee in H library were selected for qualitative research. Based on the research questions raised in this study, the results are as follows. First, synesthesia training, in which more than two senses of the five senses work simultaneously in voice training for audio book text shaping, produced the result by visualizing the original purpose, meaning, and background of the text. Second, the use of similar language was helpful in the whole process of expressing the meaning of sentence and dialogue for audiobook text shaping. In addition, although there were some differences among the study subjects, they found commonalities that considered tone, pose, and intonation important. Third, the visually impaired have advanced sensory aspects and memory, which resulted in rapid acquisition of metabolism and acceptance of transmission during training. In addition, the teacher's friendly behavior was a very important key mediator in the training process.

Modeling of Sensorineural Hearing Loss for the Evaluation of Digital Hearing Aid Algorithms (디지털 보청기 알고리즘 평가를 위한 감음신경성 난청의 모델링)

  • 김동욱;박영철
    • Journal of Biomedical Engineering Research
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    • v.19 no.1
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    • pp.59-68
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    • 1998
  • Digital hearing aids offer many advantages over conventional analog hearing aids. With the advent of high speed digital signal processing chips, new digital techniques have been introduced to digital hearing aids. In addition, the evaluation of new ideas in hearing aids is necessarily accompanied by intensive subject-based clinical tests which requires much time and cost. In this paper, we present an objective method to evaluate and predict the performance of hearing aid systems without the help of such subject-based tests. In the hearing impairment simulation(HIS) algorithm, a sensorineural hearing impairment medel is established from auditory test data of the impaired subject being simulated. Also, the nonlinear behavior of the loudness recruitment is defined using hearing loss functions generated from the measurements. To transform the natural input sound into the impaired one, a frequency sampling filter is designed. The filter is continuously refreshed with the level-dependent frequency response function provided by the impairment model. To assess the performance, the HIS algorithm was implemented in real-time using a floating-point DSP. Signals processed with the real-time system were presented to normal subjects and their auditory data modified by the system was measured. The sensorineural hearing impairment was simulated and tested. The threshold of hearing and the speech discrimination tests exhibited the efficiency of the system in its use for the hearing impairment simulation. Using the HIS system we evaluated three typical hearing aid algorithms.

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