• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.249-252
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• 1993

In speech signal processing, The accurate detection of the voiced/unvoiced is important for robust word recognition and analysis. This algorithm is based on the MD in the frame of speech signals that does not require statistical information about either signal or background-noise to decide a voiced/unvoiced. This paper presents a method of estimation the Characteristic of Magnitude Distribution from noisy speech and also of estimation the optimal threshold based on the MD of the voiced/unvoiced decision. The performances of this detectors is evaluated and compared to that obtained from classifying other paper.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.235-237
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• 2003

본 논문에서는 음성인식을 위한 전처리 단계로 음성인식의 대상을 찾아내는 음성경계 추출에 대하여 기술한다. 음성경계 추출을 위한 특징 벡터로는 시간 정보인 RMS와 주파수 정보인 MFBE를 사용한다. 사용하는 알고리즘은 학습을 통해 규칙을 생성하는 퍼지연상기억장치에 음성의 시간 정보를 적용하기 위해 순환노드를 추가한 새로운 형태의 순환 퍼지연상기억장치를 제안한다.

• Honam Mathematical Journal
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• v.30 no.1
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• pp.33-45
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• 2008

Lee weight is more appropriate for some practical situations than Hamming weight as it takes into account magnitude of each digit of the word. In this paper, we obtain a sufficient condition over the number of parity check digits for codes correcting random errors and simultaneously detecting burst errors with Lee weight consideration.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.681-682
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• 2016

본 논문에서는 화자 식별에서 음성신호의 애매한 점을 보완할 수 있는 신경회로망의 오차역전파학습 알고리즘과 모음구간 검출에 기초하여 입력되는 음성의 화자 패턴을 구분하는 일본어 단어 패턴인식 알고리즘을 제안한다. 제안하는 알고리즘에서는 일본어 데이터베이스로부터의 단어를 사용하여 음성의 특징벡터를 추출하여 분석하고 이러한 음성의 특징벡터의 차이를 이용하여 일본어 화자에 대한 패턴인식 실험을 수행하였다.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.168-171
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• 2003

This study is about modeling pronunciation dictionary necessary for PLU(phoneme like unit) level word recognition. The recognition of nonnative speakers' pronunciation enables an automatic diagnosis and an error detection which are the core of English pronunciation tutoring system. The above system needs two pronunciation dictionaries. One is for representing standard English pronunciation. The other is for representing Korean speakers' English Pronunciation. Both dictionaries are integrated to generate pronunciation networks for variants.

• MALSORI
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• no.46
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.76-80
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• 2000

This paper describes a coordinate measuring technique based on optical triangulation using the two images. To overcome the defect of structured light system which measures coordinate point by point, light source is replaced by CCD camera. Pixels in CCD camera were considered as virtual light source. The overall geometry including two camera images is modeled. Using this geometry, the formula for calculating 3D coordinate of specified point is derived. In a word, the ray from a virtual light source was reflected on measuring point and the corresponding image point was made on the other image. Through the simulation result, validation of formula is verified. This method enables to acquire multiple points detection by photographing.

• MALSORI
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• no.67
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• pp.149-166
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• 2008

In spoken document retrievals (SDR), subword (typically phonemes) indexing term is used to avoid the out-of-vocabulary (OOV) problem. It makes the indexing and retrieval process independent from any vocabulary. It also requires a small corpus to train the acoustic model. However, subword indexing term approach has a major drawback. It shows higher word error rates than the large vocabulary continuous speech recognition (LVCSR) system. In this paper, we propose an probabilistic slot detection and n-gram based string matching method for phone based spoken document retrievals to overcome high error rates of phone recognizer. Experimental results have shown 9.25% relative improvement in the mean average precision (mAP) with 1.7 times speed up in comparison with the baseline system.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.01a
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• pp.111-113
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• 2016

빠른 속도로 쏟아지고 있는 각종 발행물, 논문들에 대한 표절 검토는 표절 검출 알고리즘을 통해 직접적인 복제, 짜깁기, 말 바꾸어 쓰기 등을 검토하거나 표절 검토자가 직접 해당 문서의 키워드를 검색하여 확인하는 방식으로 이루어지고 있다. 하지만 점점 더 늘어나는 방대한 양의 문서들에 대한 표절 검토 작업은 더욱 정교한 검토 방법론을 필요로 하고 있으며, 이를 돕기 위해 문서의 직접적인 단어나 복제 비교에서 더 나아가 문서의 내용을 비교하여 비슷한 내용의 문서들을 필터링 및 검출할 수 있는 방법을 제안한다. 문서의 내용을 비교하기 위해 키워드 추출 알고리즘을 선행하며, 이를 통해 문서의 핵심 내용을 비교할 수 있는 기반을 마련하여 표절 검토자의 작업의 정확성과 속도를 향상시키고자 한다.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.71-74
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• 2003

In this paper, we present some of experimental results developed in computer-based English Pronunciation Correction System for Korean speakers. The aim of the system is to detect incorrectly pronounced phonemes in spoken words and to give correction comment to users. Speech data were collected from 254 native speakers and 411 Koreans, then used for phoneme modeling and test. We built two types of acoustic phoneme models: native speaker model and Korean speaker model. We also built langugage models to reflect Koreans' commonly occurred mispronunications. The detection rate was over 90% in insertion/deletion/replacement of phonemes, but we got under 75% detection rate in diphthong split and accents.