• 대한음성학회:학술대회논문집
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• 대한음성학회 1996년도 10월 학술대회지
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• pp.529-533
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• 1996

There are some similar phonological properties shared by different languages. The phenomenon of vowel length is just one of them which shows distinctive futures. In some languages long vowels serve to differentiate meanings. In that case the phonological context it creates is important and so it has to be incorporated into the phonemic inventory of the language, otherwise there will be misunderstanding. In this paper I will try to explain the Turkish vowel system as well as the Korean, and then to show how long vowels take their forms in Turkish and Korean.

• 대한음성학회지:말소리
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• 제42호
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• pp.37-46
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• 2001

Recently speech technologies have shown notable advancements and they now play major roles in computer-aided language learning systems. In the current paper, use of speech recognition technologies is viewed with our system for teaching English pronunciation to Japanese speakers.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2000년도 7월 학술대회지
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• pp.17-28
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• 2000

Recently speech technologies have shown notable advancements and they now play major roles in computer-aided language learning systems. In the current paper, use of speech recognition technologies is viewed with our system for teaching English pronunciation to Japanese speakers.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2003년도 5월 학술대회지
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• pp.176-179
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• 2003

This study was conducted to extract the feature set of English writing error for suggesting adequate English writing program and making automated scoring system. The frequent committed error and the error across the level of writing proficiency were reported. Also, It is reported that the correlation between type of error and native speaker's rating score.

• 대한음성학회지:말소리
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• 제54호
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• pp.73-83
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• 2005

The goal of our research is to build a text-independent speaker identification system that can be used in any condition without any additional adaptation process. The performance of speaker recognition systems can be severely degraded in some unknown mismatched microphone and noise conditions. In this paper, we show that PCA(principal component analysis) can improve the performance in the situation. We also propose an augmented PCA process, which augments class discriminative information to the original feature vectors before PCA transformation and selects the best direction for each pair of highly confusable speakers. The proposed method reduced the relative recognition error by 21%.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2003년도 5월 학술대회지
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• pp.32-35
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• 2003

This paper describes our recent work for developing a baseline platform for Korean spoken dialog recognition. In our work, We have collected about 65 hour speech corpus with auditory transcriptions. Linguistic information on various levels such as mophology, syntax, semantics, and discourse is attached to the speech database by using automatic or semi-automatic tools for tagging linguistic information.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2003년도 5월 학술대회지
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• pp.145-148
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• 2003

In this paper, we carried out comparative study about various feature parameters for the effective speaker recognition such as LPC, LPCC, MFCC, Log Area Ratio, Reflection Coefficients, Inverse Sine, and Delta Parameter. We also adopted cepstral liftering and cepstral mean subtraction methods to check their usefulness. Our recognition system is HMM based one with 4 connected-Korean-digit speech database. Various experimental results will help to select the most effective parameter for speaker recognition.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2010년도 추계학술발표대회
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• pp.687-690
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• 2010

본 논문에서는 우즈베케스탄 사람을 대상으로 한국의학에서 사용되고 있는 사상체질진단법을 적용하여 실험하였으며, 먼저 설문조사방법으로 체질을 진단하는 QSCC II(Questionnaire for Sasang Constitution Classification II)라는 진단기구와 음성분석으로 체질을 진단하는 PSSC(Phonetic System of Sasang Constitution)를 사용하여 체질을 진단한 후, 한국인과 마찬가지로 우즈베키스탄인들에게도 적용이 가능한지를 살펴보았다. 실험결과 우즈베키스탄인도 사상체질로 분류됨을 보았다.

• 대한음성학회지:말소리
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• 제62호
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• pp.113-131
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• 2007

It is reported that the segmental feature based recognition system shows better results than conventional feature based system in the previous studies. On the other hand, the various studies of combining neural network and hidden Markov models within a single system are done with expectations that it may potentially combine the advantages of both systems. With the influence of these studies, tandem approach was presented to use neural network as the classifier and hidden Markov models as the decoder. In this paper, we applied the trend information of segmental features to tandem architecture and used posterior probabilities, which are the output of neural network, as inputs of recognition system. The experiments are performed on Auroral database to examine the potentiality of the trend feature based tandem architecture. From the results, the proposed system outperforms on very low SNR environments. Consequently, we argue that the trend information on tandem architecture can be additionally used for traditional MFCC features.

• 대한음성학회지:말소리
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• 제46호
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• pp.87-102
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• 2003

In this paper, we present an English pronunciation correction system for Korean speakers and show some of experimental results on it. The aim of the system is to detect mispronounced phonemes in spoken words and to give appropriate correction comments to users. There are several English pronunciation correction systems adopting speech recognition technology, however, most of them use conventional speech recognition engines. From this reason, they could not give phoneme based correction comments to users. In our system, we build two kinds of phoneme models: standard native speaker models and Korean's error models. We also design recognition network based on phonemes to detect Koreans' common mispronunciations. We get 90% detection rate in insertion/deletion/replacement of phonemes, but we cannot get high detection rate in diphthong split and accents.