• 대한전기학회논문지
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• 제40권8호
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• pp.782-791
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• 1991

In the fields of pattern recognition such as speech recognition, several new techniques using Artifical Neural network Models have been proposed and implemented. In particular, the Multilayer Perception Model has been shown to be effective in static speech pattern recognition. But speech has dynamic or temporal characteristics and the most important point in implementing speech recognition systems using Artificial Neural Network Models for continuous speech is the learning of dynamic characteristics and the distributed cues and contextual effects that result from temporal characteristics. But Recurrent Multilayer Perceptron Model is known to be able to learn sequence of pattern. In this paper, the results of applying the Recurrent Model which has possibilities of learning tedmporal characteristics of speech to phoneme recognition is presented. The test data consist of 144 Vowel+ Consonant + Vowel speech chains made up of 4 Korean monothongs and 9 Korean plosive consonants. The input parameters of Artificial Neural Network model used are the FFT coefficients, residual error and zero crossing rates. The Baseline model showed a recognition rate of 91% for volwels and 71% for plosive consonants of one male speaker. We obtained better recognition rates from various other experiments compared to the existing multilayer perceptron model, thus showed the recurrent model to be better suited to speech recognition. And the possibility of using Recurrent Models for speech recognition was experimented by changing the configuration of this baseline model.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2000년도 7월 학술대회지
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• pp.312-320
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• 2000

This presentation aims to explore some possibility of non-segmental phonetics usually ignored in phonetics education. In pedagogical phonetics, especially ESL/EFL oriented phonetics speech sounds tend to be classified in two criteria 1) 'pronunciation' which deals with segments and 2) 'prosody' or 'suprasegmentals', a criterion that deals with non-segmental elements such as stress and intonation. However, speech involves more dynamic processing. It is non-linear and multi-dimensional in spite of the linear sequence of symbols in phonetic/phonological transcriptions. No word is without pitch or voice quality apart from segmental characteristics whether it is spoken in isolation or cut out from continuous speech. This simply tells the dichotomy of pronunciation and prosody is merely a useful convention. There exists some room to consider dynamic non-segmental phonetics. Examples of non-segmental phonetic investigation, some of the analyses conducted within the frame of Firthian Prosodic Analysis, especially of the relation between vowel variants and foot types, are examined and we see what kind of auditory phonetic training is required to understand impressionistic transcriptions which lie behind the non-segmental phonetics.

• 인지과학
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• 제19권3호
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• pp.283-295
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• 2008

SMS나 메신저의 사용이 증가함에 따자 의도적으로 음절을 해체한 새로운 형태의 문장들이 젊은이들 사이에서 습관적으로 사용되고 있다. 이러한 상황에서 자연어 인터페이스 시스템을 개발하기 위해서는 해체된 한글 음절을 결합하여 올바른 문장을 만들어 주는 기술이 먼저 개발되어야 한다. 본 논문에서는 해체된 음절을 2단계 규칙을 이용하여 결합해주는 방법을 제안한다. 1단계에서는 수동으로 자성한 휴리스틱을 이용하여 단순하게 초성, 중성, 종성으로만 해체된 음절을 결합한다. 그리고 2단계에서는 매핑 테이블과 변환기반 학습을 이용하여 복자음까지 해체된 음절을 결합한다. 실험 결과, 제안한 방법은 단순 해체 음절의 결합과 복자음 해체 음절의 결합에서 각각 100%와 99.98%라는 매우 높은 정확률을 보였다.

• 말소리와 음성과학
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• 제5권4호
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• pp.129-136
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• 2013

This study investigated how acoustic characteristics (i.e., duration, F1, F2) of English high front vowels /i, ɪ/ are modulated by boundary- and prominence-induced strengthening in native vs. non-native (Korean) speech production. The study also examined how the durational difference in vowels due to the voicing of a following consonant (i.e., voiced vs. voiceless) is modified by prosodic strengthening in two different (native vs. non-native) speaker groups. Five native speakers of Canadian English and eight Korean learners of English (intermediate-advanced level) produced 8 minimal pairs with the CVC sequence (e.g., 'beat'-'bit') in varying prosodic contexts. Native speakers distinguished the two vowels in terms of duration, F1, and F2, whereas non-native speakers only showed durational differences. The two groups were similar in that they maximally distinguished the two vowels when the vowels were accented (F2, duration), while neither group showed boundary-induced strengthening in any of the three measurements. The durational differences due to the voicing of the following consonant were also maximized when accented. The results are discussed further in terms of phonetics-prosody interface in L2 production.

• 한국음향학회지
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• 제20권3호
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• pp.70-75
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• 2001

본 논문은 우리말 연속음성에 대한 음절단위 분할법을 제안한다. 이 방법은 다음 3단계로 이루어진다: (1) 음성의 시간영역 분할 파라메터인 피치, 에너지, ZCR, PVR을 이용하여 음성데이터를 자음, 자음. 묵음 단위로 라벨링하여 토큰 (Token)을 형성, (2) 형성된 토큰을 유한상태오토마타를 이용하여 한국어 음절구조로 파서 (Parser)를 설계하여 스캐닝 (Scanning), (3) 의사 음절핵 정보를 이용하여 두개 혹은 여러 개의 음절을 가지는 음성부분에 대한 재분할을 통하여 음절단위 분할 완성. 제안된 방법에 대한 성능 평가를 위해서 문장과 단어단위 연속음성에 대한 분할 실험결과 각각 73.7％와 85.9％의 분할률을 얻었다.

• 대한음성학회:학술대회논문집
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• 대한음성학회 1996년도 10월 학술대회지
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• pp.198-206
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• 1996

Using eighteen text materials from various goners of present-day Japanese, we collected phonologically reduced forms frequently observed in conversational Japanese, and classified them in search of unified explanation of phonological reduction phenomena. We found 7,516 cases of reduced forms which we divided into 43 categories according to the types of phonological changes they have undergone. The general tendencies ale that deletion and fusion of a phoneme or an entire syllable takes place frequently, resulting in the decrease in the number of syllable. Typical examples frequently observed throughout the materials are : $~/noda/{\rightarrow}~/nda/,{\;}-/teiru/{\rightarrow}~/teru/,{\;}~/dewa/{\rightarrow}~/zja/,{\;}~/tesimau/{\rightarrow}~/cjau/$. From morphosyntactic point of view phonological reduction often occurs at the NP and VP morpheme boundaries. The following findings are drawn from phonological observations of reduction. (1) Vowels are more easily deleted than consonants. (2) Bilabials(/m/, /b/, and /w/ are the most likely candidates for deletion. (3) In a concatenation of vowels, closed vowels are absorbed into open vowels, or two adjacent vowels come to create another vowel, in which case reconstruction of the original sequence is not always predictable. (4) Alveolars are palatalized under the influence of front vowels. (5) Regressive assimilation takes place in a syllable starting with ill, changing the entire syllable into phonological choked sound or a syllabic nasal, depending on the voicing of following phoneme.

• 음성과학
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• 제8권4호
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• pp.229-241
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• 2001

Using eighteen texts from various genera of present-day Japanese, I collected phonologically reduced forms frequently observed in conversational Japanese, and classified them in search of a unified. explanation of phonological phenomena. I found 7,516 cases of reduced forms which I divided into 43 categories according to the types of phonological changes they have undergone. The general tendencies are that deletion and fusion of a phoneme or an entire syllable takes place frequently, resulting in the decrease in the number of syllables. From a morphosyntactic point of view, phonological reduction often occurs at the NP and VP morpheme boundaries. The following findings are drawn from phonetical observations of reduction. (1) Vowels are more easily deleted than consonants. (2) Bilabials ([m], [b], and [w]) are the most likely candidates for deletion. (3) In a concatenation of vowels, closed vowels are absorbed into open vowels, or two adjacent vowels come to create another vowel, in which case reconstruction of the original sequence is not always predictable. (4) Alveolars are palatalized under the influence of front vowels. (5) Regressive assimilation takes place in a syllable starting with [r], changing the entire syllable into a phonological choked sound or a syllabic nasal, depending on the voicing of the following phoneme.

• 한국음향학회지
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• 제25권2호
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• pp.88-95
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• 2006

본 논문에서는 대화체 음성에 대한 음성 인식의 성능을 향상시키기 위한 방법으로, 고속 발화음에 대해 강인한 음성 인식 방법을 제안하고 성능을 평가하였다. 제안된 기법은 입력된 음성의 속도를 정량화하여 나타내기 위한 부가적인 음성 인식 과정이 필요치 않으며, 특정 대역내의 에너지 분포를 이용하여 모음 구간을 판정하고, 단위 시간당 모음의 개수를 구하여 음성의 속도를 측정하였다. 빠른 발성음에 대한 음성 인식의 성능을 향상시키기 위해, 기존의 방법은 표준 음소 길이와 측정된 음소 길이간의 비율을 이용하여 특징 벡터를 시간축으로 확장하였다. 제안된 방법에서는 발성 속도에 따라 음성을 분류하고, 분류된 음성에 대해 서로 다른 시간축 확장 비율을 정하도록 하였다. 여기서 분류에 필요한 문턱치들과 시간축 확장 비율들은 최대 우도 방법을 이용하여 구하였다. 10자리 이동 전화 번호에 대한 음성 인식의 실험 결과, 제안된 기법에 의해 전체적으로 $17.8\%$ 오류율이 감소되는 것을 확인할 수 있었다.