• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• 제28권1호
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• pp.17-19
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• 2017

Opera singers train their vocal organ to have a good timbre of voice. They train and train again to have a strong resonance, large range of voice, homogenous color of voice, a voice goes far and to avoid vocal disorder, etc. This article is analyzing from scientific and medical perspective. It could approach the secret of the great art of 400 years history - . Furthermore standardizing voice training method based on will facilitate to train, therapy and care the voice professional user and voice disorders.

• Journal of the Ergonomics Society of Korea
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• 제21권1호
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• pp.51-65
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• 2002

As the method of providing information is getting multimedia, the synthetic voice is used in not only CTI(Computer Telephony Integration), information service for the blind, but also applications on internet. But properties of synthetic voice, such as speech rate, pitch, timbre and so on, are not adjusted to customers' preference but providers' preference. In order to consider customers' preference, this study proposed four subjective factors of voice through the evaluation of voice using the method of sensibility ergonomics. And the relation synthetic voice to be agreeable to the ear with emotional images was formulated as a fuzzy model. Consequently, this study proposed the speech rate and pitch of synthetic voice which is agreeable to the ear.

• Proceedings of the Acoustical Society of Korea Conference
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• 한국음향학회 2002년도 하계학술발표대회 논문집 제21권 1호
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• pp.541-544
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• 2002

피치 (pitch)는 주파수와 관련된 인간이 실제 느끼는 음의 높이로 라우드니스 (loudness), 음색 (timbre)과 함께 소리의 음질을 결정하는 중요한 요소로 알려져 있다. 이러한 피치는 음성 해석 및 분리를 위해 많은 연구가 이루어진 반면 소음 분석 및 음질 향상을 위한 방향으로의 연구는 부족한 상황이다. 본 연구에서는 기저막 (basilar membrane)의 위치에 따른 주파수 분리 이론인 위치이론 (place theory)을 기본으로 한 기존의 가상 피치 (virtual pitch) 분석 알고리즘을 소음에 적용하기 위해서 수정하고, 절러가지 소음에 적용하였다. 본 연구에서의 알고리즘은 소음의 주파수 특성에 의존한 방법이기 때문에, 토널 (tonal) 성분이 존재하는 소음의 적용에는 적합한 결과를 나타냈지만, 그 이외의 소음에 대해서는 정확한 분석이 어렵다. 따라서 기본 주파수 (fundamental frequency)와 이와 관련된 고조파음(harmonics)이 음질에 중요한 영향을 미치는 소음의 음질 해석 린 음질 향상을 위해 본 연구의 알고리즘에 의한 피치 분석과 기존의 음질 인자를 적용하면 보다 효율적인 결과를 얻을 수 있을 것이다. 이런 소음의 예로는 엔진의 부밍 소음이나 기어 whine 소음 등이다.

• Journal of the HCI Society of Korea
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• 제10권2호
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• pp.5-11
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• 2015

Yoseong sound is one of the Piri's representative techniques including unique timbre of Korean traditional musical instrument. This paper presents the acoustic characteristics of Yoseong sound by analyzing the sound of Piri and suggests audio filters that make Yoseong sound from ordinary sound of the Piri.

• Proceedings of the Korea Information Processing Society Conference
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• 한국정보처리학회 2019년도 춘계학술발표대회
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• pp.470-471
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• 2019

서로 다른 음성 데이터 분류를 위한 연구는 많이 진행되고 있지만 개인이 갖고 있는 목소리 또는 각 악기들이 갖고 있는 음색 러닝 연구는 부족한 실정이다. 본 논문에서는 음색 러닝을 위한 합성 곱 신경망 분석 연구를 진행한다. 음색이란 음정과 세기가 같을 경우에도 두 소리를 구분할 수 있는 복합적인 요소이다.

• Journal of Korea Multimedia Society
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• 제22권6호
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• pp.639-645
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• 2019

This paper proposes a salient chromagram components extraction method based on the temporal discrete cosine transform of a chromagram block to improve cover song retrieval accuracy. The proposed salient chromagram emphasizes tonal contents of music, which are well-preserved between an original song and its cover version, while reducing the effects of timbre difference. We apply the proposed salient chromagram extraction method as a preprocessing step for the Fourier-transform based cover song matching. Experiments on two cover song datasets confirm that the proposed salient chromagram improves the cover song search accuracy.

• Proceedings of the Korea Information Processing Society Conference
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• 한국정보처리학회 2013년도 춘계학술발표대회
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• pp.208-211
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• 2013

인터넷의 발달과 온라인 음악서비스로 인해 많은 사람들이 손쉽게 원하는 곡들을 선택하여 청취할 수 있다. 수많은 곡들 중 자기가 선호하는 음악을 듣고 찾기엔 많은 시간이 필요할 뿐만 아니라 검색하기 위해 곡 제목이나 아티스트 및 연도에 관한 정보도 숙지해야 할 것이다. 또한 질의에 해당하는 키워드가 포함되는 리스트만 제공되는 기존 음악 다운 사이트의 환경을 개선하고자, 영국 헤리엇와트 대학 연구진의 결과를 토대로 한 성격유형을 매칭시켜 해당된 장르를 구하고 컨텐트 기반인 음색유사도를 통해 질의에 해당된 음악을 추천해 주는 시스템을 설계하고자 한다. 4Shared.com과 비교 분석하였고 누구나 아는 유명한 곡들보다 한번도 들어보지 못한 곡들을 추천함으로써 유용성에 대한 기대감을 높이고자 한다.

• Journal of the Korean Institute of Intelligent Systems
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• 제20권6호
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• pp.884-889
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• 2010

Recently, a music genre classification has been studied. However, experts use different criteria to classify each of these classifications is difficult to derive accurate results. In addition, when the emergence of a new genre of music genre is a newly re-defined. Music as a genre rather than to separate search should be classified as emotional words. In this paper, the feelings of people on the basis of brightness and darkness tries to categorize music. The proposed classification system by applying VCM(Variance Considered Machines) is the contrast of the music. In this paper, we are using three kinds of musical characteristics. Based on surveys made throughout the learning, based on musical attributes(beat, timbre, note) was used to study in the VCM. VCM is classified by the trained compared with the results of the survey were analyzed. Note extraction using the MATLAB, sampled at regular intervals to share music via the FFT frequency analysis by the sector average is defined as representing the element extracted note by quantifying the height of the entire distribution was identified. Cumulative frequency distribution in the entire frequency rage, using the difference in Timbre and were quantified. VCM applied to these three characteristics with the experimental results by comparing the survey results to see the contrast of the music with a probability of 95.4% confirmed that the two separate.

• Journal of IKEEE
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• 제13권4호
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• pp.43-46
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• 2009

This paper deals with feeling recognition from people's voice to fine feature vectors. Voice signals include the people's own information and but also people's feelings and fatigues. So, many researches are being progressed to fine the feelings from people's voice. In this paper, We analysis Selectable Mode Vocoder(SMV) that is one of the standard 3GPP2 codecs of ETSI. From the analyzed result, we propose voices features for recognizing feelings. And then, feeling recognition algorithm based on gaussian mixture model(GMM) is proposed. It uses feature vectors is suggested. We verify the performance of this algorithm from changing the mixture component.

• The Journal of the Acoustical Society of Korea
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• 제30권3호
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• pp.136-141
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• 2011

In this paper, a method for measuring rhythmic similarity between two sound signals for auditory memory game is proposed. The proposed method analyzes energy fluctuation, the temporal duration of energy peak, the timbre of two signals, and detects beat positions for each signal. Then, it determines the rhythm vector after compensating a difference in tempo and the number of beats between two signals. Finally, a method for rhythmic similarity measurement is defined as a function of the dissimilarity between two rhythm vectors and a difference in the number of beats. The rhythmic similarity measured by the proposed method and that by the subjective listening test are compared, and the correlation of 0.86 between two results is achieved.