• The Journal of the Acoustical Society of Korea
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• v.9 no.3
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• pp.42-47
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• 1990

A neural auditory system is studied for the aim of making better speech recognition systems. The cochlear mechanics is described. A IIR digital filter modeling of basilar membrane is discussed for the speech recognition. A multi-layer model of consonant recognition using phoneme detection filters and discriminant functions for feature estimation is constructed. This model shows more then 90% recognition rate in consonants.

• The Journal of the Acoustical Society of Korea
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• v.9 no.4
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• pp.55-65
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• 1990

To recognize continued speech, it is necessary to segment the connected acoustic signal into phonetic units, In this paper, as a parameter to detect transition regions in continued speech, we propose a new asymmetrical rate. The suggested rate represents a change rate of magnitude of speech signals. As comparing this rate with other rate in adjacent frame, the state of the frame can be distinguished between steady state and transient state.

• The Journal of the Acoustical Society of Korea
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• v.18 no.4
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• pp.47-52
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• 1999

In this paper, we proposed a new approach to weight each feature parameter by considering the dispersion of feature parameters and its degree of contribution to recognition rate. We determined the total distribution factor that is proportional to recognition rate of each feature parameter and the dispersion factor according to the dispersion of each feature parameter. Then. we determined state-dependent weighting using the total distribution factor and dispersion factor. To verify the validity of the proposed approach, recognition experiments were performed using the PLU(Phoneme-Like Unit)-based HMM. Experimental results showed the improvement of 7.7% at the recognition rate using the proposed method.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.199-201
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• 2001

일반적으로 발음열 자동 생성기는 음성 인식 및 음성 합성에 사용되며, 그 주된 역할은 입력된 한글 철자에 대해 발음 나는 데로 표기된 음소열로 출력하는 것이다. 그러나 실제 입력되는 문장에는 특수 기호 및 알파벳. 아라비아 숫자, 영어 단어, 알파벳과 숫자가 혼용된 약어, 기호 단위 명사 등이 포함되어 있다. 게다가 아라비아 숫자의 경우 단위 명사의 종류에 따라서 뿐만 아니라, 문맥에 따라 숫자를 읽는 방식이 달라지게 된다. 이러한 모든 현상들을 발음열 생성기 내부에서 처리하게 되면 선행작업이 상대적으로 크게 되어 과부하 문제 가 발생된다. 또한 어절 내의 문맥 정보만으로 정확한 변환 결과를 얻기 힘들기 때문에 형태소 분석 수행 결과 및 예외처리를 위 한 루틴을 포함하여 한글 자소 단위의 입력형식으로 변환하는 전처리 시스템을 구성하였다.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.10a
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• pp.221-225
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• 1998

본 논문에서는 연속분포(Continuous) HMM(hidden Markov model)을 기반으로 하여 한국어 고립단어인식 시스템을 설계, 구현하였다. 시스템의 학습과 평가를 위해 자동차 항법용 음성 명령어 도메인에서 추출한 10개의 고립단어를 대상으로 음성 데이터 베이스를 구축하였다. 음성 특징 파라미터로는 MFCCs(Mel Frequency Cepstral Coefficients)와 차분(delta) MFCC 그리고 에너지(energy)를 사용하였다. 학습 데이터로부터 추출한 18개의 유사 음소(phoneme-like unit : PLU)를 인식단위로 HMM 모델을 만들었고 조음 결합 현상(채-articulation)을 모델링 하기 위해 트라이폰(triphone) 모델로 확장하였다. 인식기 평가는 학습에 참여한 음성 데이터와 학습에 참여하지 않은 화자가 발성한 음성 데이터를 이용해 수행하였으며 평균적으로 97.5%의 인식성능을 얻었다.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1107-1110
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• 1987

한국어 음소 인식 시스템의 구현을 위한 한 단체로써 한국어 모음의 분류를 위한 시스템을 설계하였다. 특징 파라미터로는 에너지, 영교차율 그리고 제 1, 제 2, 제 3 포르만트를 사용하였다. [아, 어, 오, 우, 으, 이, 에, 애]의 8개의 단모음에 해당하는 총 132개의 음성 데이터에 대하여 실험하였다. 각각의 모음에 대한 포르만트의 평균치를 구한 뒤 이들의 값을 표준 패턴으로 갖는 인식 시스템을 구현한다. 구현된 인식 시스템에 의하여 새로운 음성의 모음부가 어떤 모음인지를 인식하며 결정할 때의 거리 측정 방식으로는 선형분류 함수를 사용하였다. 132개의 모음에 대하여 62.9%의 인식율을 나타내었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.4
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• pp.159-167
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• 1985

It was demonstrated that the glottal waves are different depending on a kind of vowels in deriving the glottal waves directly from Korean vowels/a, e, I, o, u/ w, ch are recorded by a male speaker. After resynthesizing vowels with five simulated glottal waves, the effects of glottal wave shape on the speech synthesis were compared with in terms of waveform. Some changes could be seen in the waveforms of the synthetic vowels with the variation of the shape, opening time and closing time, therefore it was confirmed that in the speech sysnthesis, the glottal wave shape is an important factor in the improvement of the speech quality.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.481-485
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• 1989

The object of this parer is on the design of an broad board classifier for connected. Korean digit. Many approaches have been applied in speech recognition systems: parametric vector quantization, dynamic programming and hiden Markov model. In the 80's the neural network method, which is expected to solve complex speech recognition problems, came bach. We have chosen the rule based system for our model. The phoneme-groups that we wish to classify are vowel_like, plosive_like fricative_like, and stop_like.The data used are 1380 connected digits spoken by three untrained male speakers. We have seen 91.5% classification rate.

• MALSORI
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• no.59
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• pp.1-11
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• 2006

This study was designed to investigate the relationship between intelligibility and phonemic contrasts, and acoustic features in terms of speech development. A total of 212 Putonghua speaking children was participated in the experiment. There were phonemic contrasts significantly related with speech intelligibility: aspirated vs. fricative, retroflex vs. unretroflex, and front vs. back nasal vowel contrast. A regression analysis showed that 88% of the speech intelligibility could be predicted by these phonemic contrasts. Acoustic values were significantly related to the intelligibility of the Putonghua-speaking children's speech: voice onset time of unaspirated stops, and the duration of frication noise in fricatives.

• Proceedings of the KSPS conference
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• 2005.04a
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• pp.99-102
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• 2005

Research efforts have been made for out-of-vocabulary word rejection to improve the confidence of speech recognition systems. However, little attention has been paid to non-recognition sentence rejection. According to the appearance of pronunciation correction systems using speech recognition technology, it is needed to reject non-recognition sentences to provide users with more accurate and robust results. In this paper, we introduce standard phoneme based sentence rejection system with no need of special filler models. Instead we used word spotting ratio to determine whether input sentences would be accepted or rejected. Experimental results show that we can achieve comparable performance using only standard phoneme based recognition network in terms of the average of FRR and FAR.