• 정보처리학회논문지B
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• 제10B권7호
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• pp.829-836
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• 2003

본 논문에서는 사전과 시소러스를 이용하여 문장음성 이해를 위한 확률모델을 제안한다. 제안한 확률모델은 입력되는 음성과 텍스트 문장에서 단어를 추출한다. 컴퓨터가 선택한 카테고리의 사전 DB와 입력된 문장에서 추출된 단어와 비교하고 확률모델로부터 확률값을 얻는다. 이때 컴퓨터로부터 상위어 정보를 알아내고 상위어 사전을 검색하여 단어를 추출하고 입력된 단어와 확률 모델을 비교하여 결과값을 얻는다. 사전과 상위어 사전으로부터 얻은 두개의 확률값을 더하고 그 값을 미리 정해진 임계값과 비교하여 문장의 이해도를 측정한다. 이와 같은 이해 시스템을 스무고개 게임에 적용시켜 그 성능을 평가 하였다. 상위어 확률 값($\alpha$)이 0.9이고 임계값 ($\beta$)은 0.38일 때 문장음성 이해의 정확도는 79.8%였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2435-2438
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• 2003

In this paper, we propose a Korean speech understanding model using dictionary and thesaurus. The proposed model search the dictionary for the same word with in input text. If it is not in the dictionary, the proposed model search the high level words in the high level word dictionary based on the thesaurus. We compare the probability of sentence understanding model with threshold probability, and we'll get the speech understanding rate. We evaluated the performance of the sentence speech understanding system by applying twenty questions game. As the experiment results, we got sentence speech understanding accuracy of 79.8％. In this case probability of high level word is 0.9 and threshold probability is 0.38.

• 말소리와 음성과학
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• 제3권1호
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• pp.117-123
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• 2011

Most individuals with hearing impairment have difficulty in understanding speech in noisy situations. This study was conducted to investigate sentence recognition ability using the Korean Standard-Sentence Lists for Preschoolers (KS-SL-P2) in pre-school age children with cochlear implants and hearing aids. The subjects of this study were 10 pre-school age children with hearing aids, 12 pre-school age children with cochlear implants, and 10 pre-school age children with normal hearing. Three kinds of signal-to-noise (SNR) conditions (+10 dB, +5 dB, 0 dB) were applied. The results for all pre-school age children with cochlear implants and hearing aids presented a significant increase in the score for sentence recognition as SNR increased. The sentence recognition score in speech noise were obtained with the SNR +10 dB. Significant differences existed between groups in terms of their sentence recognition ability, with the cochlear implant group performing better than the hearing aid group. These findings suggest the presence of a sentence recognition test using speech noise is useful for evaluating pre-school age children's listening skill.

• 음성과학
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• 제7권2호
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• pp.37-50
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• 2000

This paper describes a test of everyday speech understanding ability, in which a listener's utilization of the context-situational information of speech is assessed, and is compared with the utilization of acoustic-phonetic information. The test items are sentences which are presented in a babble type of noise, and the listener response is the key word in the sentence. The key words are always two-syllabic nouns and the questioning sentences are added to obtain the responding key words. Two types of sentences are used. One is the high-predictable sentences for which the key word is somewhat predictable from the context. The other is the low-predictable sentences for which the key-word cannot be predicted from the context. Both types are included in six 40-item forms of the test, which are balanced for intelligibility, key-word familiarity and predictability, phonetic content, and length. Performance of normally hearing listeners shows significantly different functions for various signal-to-noise ratios. The potential applications of this test, particularly in the assessment of speech understanding ability in the hearing impaired, are discussed.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2011년도 하계학술대회
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• pp.89-91
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• 2011

In this paper, phrase boundaries in sentence are predicted and a phrase break information is applied to an HMM-based Korean Text-to-Speech synthesis system. Synthesis with phrase break information increases a naturalness of the synthetic speech and an understanding of sentences. To predict these phrase boundaries, context-dependent information like forward/backward POS(Part-of-Speech) of eojeol, a position of eojeol in a sentence, length of eojeol, and presence or absence of punctuation marks are used. The experimental results show that the naturalness of synthetic speech with phrase break information increases.

• 로봇학회논문지
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• 제14권1호
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• pp.22-30
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• 2019

For effective human-robot interaction, robots need to understand the current situation context well, but also the robots need to transfer its understanding to the human participant in efficient way. The most convenient way to deliver robot's understanding to the human participant is that the robot expresses its understanding using voice and natural language. Recently, the artificial intelligence for video understanding and natural language process has been developed very rapidly especially based on deep learning. Thus, this paper proposes robot vision to audio description method using deep learning. The applied deep learning model is a pipeline of two deep learning models for generating natural language sentence from robot vision and generating voice from the generated natural language sentence. Also, we conduct the real robot experiment to show the effectiveness of our method in human-robot interaction.

• 대한음성학회:학술대회논문집
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• 대한음성학회 1997년도 7월 학술대회지
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• pp.81-91
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• 1997

This paper deals with the problems of English listening comprehension: the rate of understanding difference in positions and sentence structures, parts of speech easily missed to understand, English sounds only in English(not in Korean), confusion of sounds, unaccented prefixes and suffixes, polysemy, homonym, juncture, understanding as one word by two different words, and sound blending in a normal speed of connected speech. Bearing those in mind I taught Suwon University freshmen video English with the mixed idea of Peterson's bottom-up and top-down methods putting in a meaningful context with thought group rather than word to word understanding. As a consequence, their errors come: prepositions, conjunctions, unstressed prefixes and suffixes, -ing from the present progressives and so forth. Assignments to have students transcribe the TV commercials and the names of reporters or Korean related news from English broadcastings are of use and help.

• Journal of Electrical Engineering and information Science
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• 제1권1호
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• pp.1-9
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• 1996

A key issue in spoken language processing has become the integration of speech understanding and natural language processing(NLP). This paper presents a parallel computational model for the integration of speech and NLP. The model adopts a hierarchically-structured knowledge base and memory-based parsing techniques. Processing is carried out by passing multiple markers in parallel through the knowledge base. Speech-specific problems such as insertion, deletion, and substitution have been analyzed and their parallel solutions are provided. The complete system has been implemented on the Semantic Network Array Processor(SNAP) and is operational. Results show an 80% sentence recognition rate for the Air Traffic Control domain. Moreover, a 15-fold speed-up can be obtained over an identical sequential implementation with an increasing speed advantage as the size of the knowledge base grows.

• 음성과학
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• 제7권4호
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• pp.219-234
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• 2000

The study of boundary tones in connected speech or dialogues is one of the most underdeveloped areas of Korean prosody. This. paper concerns the boundary tones of intonational phrase-final morphemes which are shown in the speech corpus of dialogues. Results of phonetic analysis show that different kinds of boundary tones are realized, depending on the positions of the intonational phrase-final morphemes in the sentences.. This study has also shown that boundary tone patterning is somewhat related to the sentence structure, and for better speech recognition and speech synthesis, it presents a simple model of boundary tones based on the fundamental frequency contour. The results of this study will contribute to our understanding of the prosodic pattern of Korean connected speech or dialogues.

• 한국컴퓨터정보학회논문지
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• 제5권4호
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• pp.48-54
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• 2000

본 논문에서는 한ㆍ영 기계번역을 위한 한국어의 품사를 분류하였고 각 품사의 형태론적 특징을 고찰하였다. 한국어 표준문법에서 제시되는 품사 분류 기준은 의미, 기능, 형태의 세 가지 기준을 적용하고 있으며, 자연언어처리에서도 같은 분류 기준을 바탕으로 하고 있다. 품사 분류에 여러 가지 기준을 적용하는 것은 문법구조 이해 및 품사 분류를 어렵게 한다. 또한 한 영 기계번역시 품사의 불일치로 전처리가 필요하다. 이러한 문제를 해결하기 위하여 본 논문에서는 하나의 기준을 적용하여 품사를 분류하였다. 방법으로 한국어 표준문법에 의하여 말뭉치에 태깅하고 문제점을 찾아내며, 새로운 기준에 의하여 품사를 분류하였다. 본 논문에서 분류된 품사는 한국어 문장에서 통사적 역할이 동일하고, 영어에서의 사전 품사와 동일하며, 품사 분류의 모호성을 제거하고, 한국어의 문장 구조를 명확히 표현한다. 또한 한ㆍ영 기계번역시 패턴 매칭에 의한 목적언어 생성이 가능하게 한다.