• 제목/요약/키워드: spoken language corpus

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한국어교육학에서의 담화 연구 분석 (Issues of Discourse Studies in Korean Language Education)

  • 강현화
    • 한국어교육
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    • 제23권1호
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    • pp.219-256
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    • 2012
  • The aim of this study is to observe the trend of discourse study in language education and analyze the main issues by investigating the literatures related to discourse in Korean language education in the last ten years. This study observed the discourse study conducted in Korean language education from the perspectives of study subject, study method and study data. Moreover, based on the results, it estimated the achievements and effectiveness of the discourse study conducted in Korean language education. The subject of discourse study was mainly dealt with discourse function, discourse pattern, discourse marker, discourse structure. In the study methods, analysis of corpus and survey were mainly used as the study methods, and spoken corpus, written corpus and semi-spoken corpus were used as study materials. In particular, the semi-spoken corpus was used at a very high rate among them. This showed that discourse study in Korean language education was mainly focused on spoken corpus study. This study divided the detailed field of Korean language education into four fields of linguistic knowledge, communication function, teaching activities and learning activities, and observed the trends of discourse study in each field. Overall, it was recognized that relatively many studies were focused on linguistic knowledge, particularly in pragmatic perspective. It can be said that the study based on discourse has a language educational effectiveness in that it is based on actual data and improves practical communication skills in the environment of various languages.

언어모델 인터뷰 영향 평가를 통한 텍스트 균형 및 사이즈간의 통계 분석 (Statistical Analysis Between Size and Balance of Text Corpus by Evaluation of the effect of Interview Sentence in Language Modeling)

  • 정의정;이영직
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 2002년도 하계학술발표대회 논문집 제21권 1호
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    • pp.87-90
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    • 2002
  • This paper analyzes statistically the relationship between size and balance of text corpus by evaluation of the effect of interview sentences in language model for Korean broadcast news transcription system. Our Korean broadcast news transcription system's ultimate purpose is to recognize not interview speech, but the anchor's and reporter's speech in broadcast news show. But the gathered text corpus for constructing language model consists of interview sentences a portion of the whole, $15\%$ approximately. The characteristic of interview sentence is different from the anchor's and the reporter's in one thing or another. Therefore it disturbs the anchor and reporter oriented language modeling. In this paper, we evaluate the effect of interview sentences in language model for Korean broadcast news transcription system and analyze statistically the relationship between size and balance of text corpus by making an experiment as the same procedure according to varying the size of corpus.

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한국인의 영어 음성 코퍼스 설계 및 구축 (Design and Construction of Korean-Spoken English Corpus(K-SEC))

  • 이석재;이숙향;강석근;이용주
    • 대한음성학회지:말소리
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    • 제46호
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    • pp.159-174
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    • 2003
  • K-SEC (Korean-Spoken English Corpus) is a kind of speech database that is being under construction by the authors of this paper This article discusses the needs of the K-SEC from various academic disciplines and industrial circles, and it introduces the characteristics of the K-SEC design, its catalogues and contents of the recorded database, exemplifying what are being considered from both Korean and English languages' phonetics and phonologies. The K-SEC can be marked as a beginning of a parallel speech corpus, and it is suggested that a similar corpus should be enlarged for the future advancements of the experimental phonetics and the speech information technology.

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음성대화시스템 워크벤취로서의 DialogStudio 개발 (DialogStudio: A Spoken Dialog System Workbench)

  • 정상근;이청재;이근배
    • 대한음성학회지:말소리
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    • 제63호
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    • pp.101-112
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    • 2007
  • Spoken dialog system development includes many laborious and inefficient tasks. Since there are many components such as speech recognition, language understanding, dialog management and knowledge management in a spoken dialog system, a developer should take an effort to edit corpus and train each model separately. To reduce a cost for editing corpus and training each model, we need more systematic and efficient working environment. For the working environment, we propose DialogStudio as a spoken dialog system workbench.

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Prosodic Contour Generation for Korean Text-To-Speech System Using Artificial Neural Networks

  • Lim, Un-Cheon
    • The Journal of the Acoustical Society of Korea
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    • 제28권2E호
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    • pp.43-50
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    • 2009
  • To get more natural synthetic speech generated by a Korean TTS (Text-To-Speech) system, we have to know all the possible prosodic rules in Korean spoken language. We should find out these rules from linguistic, phonetic information or from real speech. In general, all of these rules should be integrated into a prosody-generation algorithm in a TTS system. But this algorithm cannot cover up all the possible prosodic rules in a language and it is not perfect, so the naturalness of synthesized speech cannot be as good as we expect. ANNs (Artificial Neural Networks) can be trained to learn the prosodic rules in Korean spoken language. To train and test ANNs, we need to prepare the prosodic patterns of all the phonemic segments in a prosodic corpus. A prosodic corpus will include meaningful sentences to represent all the possible prosodic rules. Sentences in the corpus were made by picking up a series of words from the list of PB (phonetically Balanced) isolated words. These sentences in the corpus were read by speakers, recorded, and collected as a speech database. By analyzing recorded real speech, we can extract prosodic pattern about each phoneme, and assign them as target and test patterns for ANNs. ANNs can learn the prosody from natural speech and generate prosodic patterns of the central phonemic segment in phoneme strings as output response of ANNs when phoneme strings of a sentence are given to ANNs as input stimuli.

Enhancement of a language model using two separate corpora of distinct characteristics

  • 조세형;정태선
    • 한국지능시스템학회논문지
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    • 제14권3호
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    • pp.357-362
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    • 2004
  • 언어 모델은 음성 인식이나 필기체 문자 인식 등에서 다음 단어를 예측함으로써 인식률을 높이게 된다. 그러나 언어 모델은 그 도메인에 따라 모두 다르며 충분한 분량의 말뭉치를 수집하는 것이 거의 불가능하다. 본 논문에서는 N그램 방식의 언어모델을 구축함에 있어서 크기가 제한적인 말뭉치의 한계를 극복하기 위하여 두개의 말뭉치, 즉 소규모의 구어체 말뭉치와 대규모의 문어체 말뭉치의 통계를 이용하는 방법을 제시한다. 이 이론을 검증하기 위하여 수십만 단어 규모의 방송용 말뭉치에 수백만 이상의 신문 말뭉치를 결합하여 방송 스크립트에 대한 퍼플렉시티를 30% 향상시킨 결과를 획득하였다.

영어 완화 표지와 한국어 종결어미 비교 - 영어권 학습자를 위한 문법 설명 - (English Hedge Expressions and Korean Endings: Grammar Explanation for English-Speaking Leaners of Korean)

  • 김영아
    • 한국어교육
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    • 제25권1호
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    • pp.1-27
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    • 2014
  • This study investigates how common English hedge expressions such as 'I think' and 'I guess' appear in Korean, with the aim of providing explicit explanation for English-speaking leaners of Korean. Based on a contrastive analysis of spoken English and Korean corpus, this study argues three points: Firstly, 'I guess' appears with a wider variety of modalities in Korean than 'I think'. Secondly, this study has found that Korean textbooks contain inappropriate use of registers regarding the English translations of '-geot -gat-': although these markers are used in spoken Korean, they were translated into written English. Therefore, this study suggests that '-geot -gat-' be translated into 'I think' in spoken English, and into 'it seems' in the case of written English and narratives. Lastly, the contrastive analysis has shown that when 'I think' is used with deontic modalities such as 'I think I have to', Korean use '-a-ya-get-': the use of hedge marker 'I think' with 'I have to', which shows obligation or speaker's volition turns the deontic modalities into expressions of speaker's opinion.

음성대화시스템 워크벤취로서의 DialogStudio 개발 (DialogStudio;A Spoken Dialog System Workbench)

  • 정상근;이청재;이근배
    • 대한음성학회:학술대회논문집
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    • 대한음성학회 2007년도 한국음성과학회 공동학술대회 발표논문집
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    • pp.311-314
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    • 2007
  • Spoken dialog system development includes many laborious and inefficient tasks. Since there are many components such as speech recognizer, language understanding, dialog management and knowledge management in a spoken dialog system, a developer should take an effort to edit corpus and train each model separately. To reduce a cost for editting corpus and training each models, we need more systematic and efficent working environment. For the working environment, we propose DialogStudio as an spoken dialog system workbench.

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Implementation and Evaluation of an HMM-Based Speech Synthesis System for the Tagalog Language

  • ;김경태;김종진
    • 대한음성학회지:말소리
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    • 제68권
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    • pp.49-63
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    • 2008
  • This paper describes the development and assessment of a hidden Markov model (HMM) based Tagalog speech synthesis system, where Tagalog is the most widely spoken indigenous language of the Philippines. Several aspects of the design process are discussed here. In order to build the synthesizer a speech database is recorded and phonetically segmented. The constructed speech corpus contains approximately 89 minutes of Tagalog speech organized in 596 spoken utterances. Furthermore, contextual information is determined. The quality of the synthesized speech is assessed by subjective tests employing 25 native Tagalog speakers as respondents. Experimental results show that the new system is able to obtain a 3.29 MOS which indicates that the developed system is able to produce highly intelligible neutral Tagalog speech with stable quality even when a small amount of speech data is used for HMM training.

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통계적 언어 모델의 clustering 알고리즘과 음성인식에의 적용 (A clustering algorithm of statistical langauge model and its application on speech recognition)

  • 김우성;구명완
    • 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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    • 한국정보과학회언어공학연구회 1996년도 제8회 한글 및 한국어 정보처리 학술대회
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    • pp.145-152
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    • 1996
  • 연속음성인식 시스템을 개발하기 위해서는 언어가 갖는 문법적 제약을 이용한 언어모델이 요구된다. 문법적 규칙을 이용한 언어모델은 전문가가 일일이 문법 규칙을 만들어 주어야 하는 단점이 있다. 통계적 언어 모델에서는 문법적인 정보를 수작업으로 만들어 주지 않는 대신 그러한 모든 정보를 학습을 통해서 훈련해야 하기 때문에 이를 위해 요구되는 학습 데이터도 엄청나게 증가한다. 따라서 적은 양의 데이터로도 이와 유사한 효과를 보일 수 있는 것이 클래스에 의거한 언어 모델이다. 또 이 모델은 음성 인식과 연계시에 탐색 공간을 줄여 주기 때문에 실시간 시스템 구현에 매우 유용한 모델이다. 여기서는 자동으로 클래스를 찾아주는 알고리즘을 호텔예약시스템의 corpus에 적용, 분석해 보았다. Corpus 자체가 문법규칙이 뚜렷한 특성을 갖고 있기 때문에 heuristic하게 클래스를 준 것과 유사한 결과를 보였지만 corpus 크기가 커질 경우에는 매우 유용할 것이며, initial map을 heuristic하게 주고 그 알고리즘을 적용한 결과 약간의 성능향상을 볼 수 있었다. 끝으로 음성인식시스템과 접합해 본 결과 유사한 결과를 얻었으며 언어모델에도 음향학적 특성을 반영할 수 있는 연구가 요구됨을 알 수 있었다.

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