• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2003년도 추계공동학술대회
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• pp.721-727
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• 2003

This study designed and implemented a system to extract of vowel from a word. The system is comprised of a voice feature extraction module and a neutral network module. The voice feature extraction module use a LPC(Linear Prediction Coefficient) model to extract a voice feature from a word. The neutral network module is comprised of a learning module and voice recognition module. The learning module sets up a learning pattern and builds up a neutral network to learn. Using the information of a learned neutral network, a voice recognition module extracts a vowel from a word. A neutral network was made to learn selected vowels(a, eo, o, e, i) to test the performance of a implemented vowel extraction recognition machine. Through this experiment, could confirm that speech recognition module extract of vowel from 4 words.

• 비교문화연구
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• 제48권
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• pp.391-417
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• 2017

동남아시아 언어들은 모음체계가 매우 복잡한 것으로 알려져 있어 자연언어 모음체계의 보편성을 논의하는 데 매우 중요한 위치를 차지하고 있다. 본 연구는 이를 위한 기초연구로 7개의 동남아시아 국어 또는 공식어 중 우선적으로 그 체계가 비교적 단순한 타갈로그어, 말레이어, 타이어의 3개 언어를 대상으로 모음체계의 보편성에 대해 논의한 것이다. 모음의 보편성에 대해서는 여러 학자들의 견해가 있지만 본 연구에서는 209개 언어의 분절음을 구축한 SPAP(Stanford Phonology Archive Project)나 451개 언어의 분절음을 구축한 UPSID(UCLA Phonological Segment Inventory Database)와 같은 대규모 말뭉치를 이용하여 모음체계의 보편성을 논의한 선행연구들을 바탕으로, 그 연구들에 제시된 6가지의 보편성 분석 기준을 위 세 언어의 모음체계에 실험적으로 적용하여 분석을 시도하였다. 그 6가지 기준은 유형적 보편성에 속하는 (1) 모음 수(또는 모음 목록 크기)와 (2) 단계성에 따른 모음 구성의 두 가지, 그리고 음성적 보편성이라 할 수 있는 (3) 저설성 (4) 균형성과 대칭성 (5) 전설성 (6) 원순성의 네 가지이다. 그리고 위의 세 언어에 이 6가지 기준을 적용함에 있어 보편성을 판별하는 또 다른 기준인 기술적 보편성과 분석적 보편성의 두 가지 관점 모두에서 분석하였다. 논의의 결과 분석적 보편성의 관점에서는 세 언어 모두 6가지 기준에서 '높음' 단계의 보편성을 보이지만 기술적 보편성에서는 타갈로그 어는 모음 수와 단계성에 따른 모음 구성, 그리고 저설성에서 상대적으로 보편성이 낮으며, 타이어는 균형성은 다른 두 언어와 마찬가지로 높은 보편성을 보이지만 대칭성에 있어서는 '보통' 단계의 보편성을 보이고 있다. 한편, 말레이어는 모든 기준에서 '높음' 단계의 보편성을 보이는 매우 안정적인 모음체계를 가지고 있음을 확인하였다.

• 음성과학
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• 제10권2호
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• pp.287-301
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• 2003

The purpose of this study was to examine whether the same vowel sounds are perceived differently by the two local dialect speakers, Seoul dialect speakers (SDS) and Kyungnam dialect speakers (KDS), whose vowel systems differ each other. In the first experiment SDS and KDS heard vowels synthesized in vowel space with F1 by F2 and categorized them into one of 10 Korean monophthongs. The results showed that SDS and KDS perceived the synthesized vowels differently. For example, /$\varepsilon$ versus /e/ contrast, ${\o}$/, and /y/ are differentiated by SDS, whereas they are perceptually confused by KDS. We also observed that /i/ could not be perceived unless the vowel synthesis included F3 or higher formants. In the second experiment SDS and KDS performed the similarity rating task of 10 synthesized Korean monophthongs. Two-dimensional MDS solution based on the similarity rating scores was obtained for each dialect group. The first dimension can be named 'vowel advancement' and the second 'vowel height'. The comparison of the two MDS solutions showed that the overall psychological distances among the vowels are shorter in KDS than SDS and that especially the distance between /$\Lambda$/ and /i/ is shorter in KDS than SDS. The result suggested that perception or mental representation of vowels depends on the vowel system of the listener's dialect or language. Further research problems were discussed in the final section.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1042-1045
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• 2003

In this paper, we propose the speaker identification system that uses vowel that has speaker's characteristic. System is divided to speech feature extraction part and speaker identification part. Speech feature extraction part extracts speaker's feature. Voiced speech has the characteristic that divides speakers. For vowel extraction, formants are used in voiced speech through frequency analysis. Vowel-a that different formants is extracted in text. Pitch, formant, intensity, log area ratio, LP coefficients, cepstral coefficients are used by method to draw characteristic. The cpestral coefficients that show the best performance in speaker identification among several methods are used. Speaker identification part distinguishes speaker using Neural Network. 12 order cepstral coefficients are used learning input data. Neural Network's structure is MLP and learning algorithm is BP (Backpropagation). Hidden nodes and output nodes are incremented. The nodes in the incremental learning neural network are interconnected via weighted links and each node in a layer is generally connected to each node in the succeeding layer leaving the output node to provide output for the network. Though the vowel extract and incremental learning, the proposed system uses low learning data and reduces learning time and improves identification rate.

• 한국음향학회지
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• 제21권2호
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• pp.160-166
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• 2002

본 논문에서는 CV (Consonant Vowel), VCCV (Vowel Consonant Consonant Vowel), VC (Vowel Consonant) 인식 단위를 이용한 새로운 어휘 독립 음성인식 시스템을 구현하였다. 이 인식 단위는 음절의 안정된 모음 구간에서 분할하여 구성했기 때문에 분할이 용이하다. VCCV단위가 존재하지 않을 경우에는 VC와 CV 반음절 모델을 결합하여 대체모델을 구성하였다. 모음군 군집화 (clustering)와 VCCV 모델이 존재하지 않을 경우 대체모델에 결합규칙을 적용하여 제 1후보에서 90.4% (모델 A)에서 95.6% (모델 C)로 5.2%의 인식 성능향상을 가져왔다. 인식실험결과 제 2후보에서 98.8%의 인식률로 제안된 방법이 효율적임을 확인하였다.

• IEIE Transactions on Smart Processing and Computing
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• 제5권3호
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• pp.215-221
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• 2016

This paper describes an automatic vowel sequence reproduction system for a talking robot built to reproduce the human voice based on the working behavior of the human articulatory system. A sound analysis system is developed to record a sentence spoken by a human (mainly vowel sequences in the Japanese language) and to then analyze that sentence to give the correct command packet so the talking robot can repeat it. An algorithm based on a short-time energy method is developed to separate and count sound phonemes. A matching template using partial correlation coefficients (PARCOR) is applied to detect a voice in the talking robot's database similar to the spoken voice. Combining the sound separation and counting the result with the detection of vowels in human speech, the talking robot can reproduce a vowel sequence similar to the one spoken by the human. Two tests to verify the working behavior of the robot are performed. The results of the tests indicate that the robot can repeat a sequence of vowels spoken by a human with an average success rate of more than 60%.

• 대한음성언어의학회:학술대회논문집
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• 대한음성언어의학회 2003년도 제19회 학술대회
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• pp.170-173
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• 2003

There are more than five systems for transcribing English vowels. Because of this diversity, teachers of English and students are confronted with not a little problems with the English vowel symbols used in the English-Korean dictionaries, English text books, books for Phonetics and Phonology. This study was designed to suggest criterions for the phonemic transcription of English vowels on the basis of phonetic properties of the vowels and a system of English vowel transcription based on the criterions in order to minimize the problems with inter-system differences. A speaker (phonetician) of RP English uttered a series of isolated minimal pairs containing the vowels in question. The suggested vowel symbols are as follows: 1) Simple vowels : /i:/ in beat, /I/ bit, /$\varepsilon$/ bet,/${\ae}$/ bat, /a:/ father, /Dlla/ bod, /$\jmath$:/ bawd, /u/ put, /u:/ boot /$\Lambda$/ but, and /$\partial$/ about /$\Im$:ll$\Im$:r/ bird. 2) Diphthongs : /aI/ in bite, /au/ bout, /$\jmath$I/ boy, /$\Im$ullou/ boat, /er/ bait, /e$\partial$lle$\partial$r/ air, /u$\partial$llu$\partial$r/ poor, /i$\partial$lli$\partial$r/ beer. Where two symbols are shown corresponding to the vowel in a single word, the first is appropriate for most speakers of British English and the second for most speakers of American English.

• 대한음성학회지:말소리
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• 제62호
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• pp.1-17
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• 2007

The purpose of this study was to investigate and quantitatively describe the acoustic characteristics of current Korean monophthongs. Recordings were made of 33 men and 27 women producing the vowels /i, e, ${\epsilon}$, a, ${\partial}$, o, u, i/ in a carrier phrase "This character is ___." A listening test was conducted in which 19 participants judged each vowel. F1, F2, and F3 were measured from the vowels judged as intended vowels by more than 17 people from the listening test. Analysis of formant data shows some interesting results including the undeniable confirmation of the 7-vowel system in modern Korean. It turns out that quite different sounding Korean vowels and English vowels happen to have very similar formant measurements. Also the difference between "citation-form reading" vs. "natural utterance reading" is discussed.

• 음성과학
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• 제7권4호
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• pp.169-186
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• 2000

This paper aims to confirm the mispronunciation of native Korean students due to the phonetic and phonological system differences between English and Korean, and to find the works-to-do by experiment. Many Korean students tend to differentiate the sounds of word-final stop consonants not by vowel duration or the allophones but by the phoneme of the consonant itself. In English, Stop sounds change through the conditions of the aspirated, unaspirated, or unreleased sounds. But in Korean they are not allophones of phonemes but distinct phonemes. Therefore, many Korean students are apt to add an extra vowel sound /i/ after the final stop consonant in the eve form due to both the unperception of the differences between the phonemes and the allophones of stop consonants, and the influence of the Korean sound-sequence relationship. Since the replacement of the allophones and extra vowel addition does not change the meaning, the importance was almost lost. Nevertheless, this kind of study is essential for the precise learning and the use of the English language.

• 음성과학
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• 제10권1호
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• pp.3-13
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• 2003

The devoicing vowel is a phonological process whose contrast in sonority is lost or reduces in a particular phonetic environment. Phonetically, the vocal fold vibration originates from the abduction/adduction of the glottis in relation to supraglottal articulatory movements. The purpose of this study is to investigate Korean vowel devoicing by means of experimental instruments. The interrelated laryngeal adjustments and aerodynamic effects for this voicing can clarify the redundant articulatory gestures relevant to the distinctive feature of sonority. Five test words were selected, being composed of the high vowel /i/, between the fricative and strong aspirated or lenis affricated consonants. The subjects uttered the test words successively at a normal or at a faster speed. The EMG, the sensing tube Gaeltec S7b and the High-Speech Analysis system and MSL II were used in these studies. Acoustically, three different types of speech waveforms and spectrograms were classified, based on the voicing variation. The intraoral air pressure curves showed differences, depending on the voicing variations. The activity patterns of the PCA and the CT for devoicing vowels appeared differently from those showing the partially devoicing vowels and the voicing vowels.