• Proceedings of the KSLP Conference
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• 2003.11a
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• pp.170-173
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• 2003

There are more than five systems for transcribing English vowels. Because of this diversity, teachers of English and students are confronted with not a little problems with the English vowel symbols used in the English-Korean dictionaries, English text books, books for Phonetics and Phonology. This study was designed to suggest criterions for the phonemic transcription of English vowels on the basis of phonetic properties of the vowels and a system of English vowel transcription based on the criterions in order to minimize the problems with inter-system differences. A speaker (phonetician) of RP English uttered a series of isolated minimal pairs containing the vowels in question. The suggested vowel symbols are as follows: 1) Simple vowels : /i:/ in beat, /I/ bit, /$\varepsilon$/ bet,/${\ae}$/ bat, /a:/ father, /Dlla/ bod, /$\jmath$:/ bawd, /u/ put, /u:/ boot /$\Lambda$/ but, and /$\partial$/ about /$\Im$:ll$\Im$:r/ bird. 2) Diphthongs : /aI/ in bite, /au/ bout, /$\jmath$I/ boy, /$\Im$ullou/ boat, /er/ bait, /e$\partial$lle$\partial$r/ air, /u$\partial$llu$\partial$r/ poor, /i$\partial$lli$\partial$r/ beer. Where two symbols are shown corresponding to the vowel in a single word, the first is appropriate for most speakers of British English and the second for most speakers of American English.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.99-106
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• 2004

The syllable restoration is a process restoring a phonetic value recognized in a speech recognition device with the notation form that a vocalization is former. In this paper a syllable restoration rule was composed of a based on standard pronunciation for a syllable restoration process. A syllable restoring regulation was used, and a generation method of a notation candidate set was researched. Also, A study is held to reduce the number of created notation candidate. Three phases of reduction processes were suggested. Reduction of a notation candidate has the non-notation syllable, non-vocabulary syllable and non-stem syllable. As a result of experiment, an average of 74％ notation candidate decrease rates were shown.

• Journal of the Korean Society of Costume
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• v.57 no.6 s.115
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• pp.112-121
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• 2007

Gamtu was a name recorded in Korean in respect of 'Mo(帽), Moja(帽子), Somoja(小帽子), Jeongmoja(頂帽子), Jeonmo(氈帽), Yangmomo(羊毛帽), Tangjeon(宕巾)' from the beginning to the end of Joseon dynasty which includes various shapes and uses according to wordbook. Also, Gamtu has various phonetic transcriptions, however Manchu pronunciation of 'Moja(帽子)' is indicated as 'Kamtoo' in $\ulcorner$Dongmunyuhae(同文類解)$\lrcorner$ so the origin of the word Gamtu should be discussed. Accordingly, I want to clearly define the concept of Gamtu in this research by studying the history and shape of Gamtu, and Chinese entries annotated in Korean as Gamtu. Even though we can assume that the etymology of Gamtu is Manchu language as Manchu pronunciation of 'Moja(帽子)' is indicated as 'Kamtu' in $\ulcorner$Dongmunyuhae(同文類解)$\lrcorner$, I think the Korean pronunciation of Gamtu already existed because there already was a Chinese transcription of 'Gamtu' in the Goryeosa(高麗史). So, we can conjecture that Gamtu could be originated from Yeojin language which is the same lineage of Manchu. As a conclusion, Somoja(小帽子), Jeongmoja(頂帽子), Moja(帽子), Jeonmo(氈帽), Yangmomo(羊毛帽), Tangjeon(宕巾) had a common feature that they were produced to fit head without visor, and were annotated as Gamtu per woolen cloth was used as Jeonmo(氈帽), Yangmomo(羊毛帽), and Gamtu was just a Korean transcription that includes these names.

• ETRI Journal
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• v.46 no.1
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• pp.127-136
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• 2024

The Korean language has written (formal) and spoken (phonetic) forms that differ in their application, which can lead to confusion, especially when dealing with numbers and embedded Western words and phrases. This fact makes it difficult to automate Korean speech recognition models due to the need for a complete transcription training dataset. Because such datasets are frequently constructed using broadcast audio and their accompanying transcriptions, they do not follow a discrete rule-based matching pattern. Furthermore, these mismatches are exacerbated over time due to changing tacit policies. To mitigate this problem, we introduce a data-driven Korean spoken-to-written transcription conversion technique that enhances the automatic conversion of numbers and Western phrases to improve automatic translation model performance.

• The Journal of the Korea Contents Association
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• v.14 no.2
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• pp.28-38
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• 2014

For western music there has been a volume of researches on music information analysis for automatic transcription or content-based music retrieval. But it is hard to find the similar research on Korean traditional music. In this paper we propose several algorithms to automatically analyze the structure of Korean traditional music 'Pansori'. The proposed algorithm automatically distinguishes between the 'sound' part and 'speech' part which are named 'sori' and 'aniri', respectively, using the ratio of phonetic and pause time intervals. For rhythm called 'jangdan' classification the algorithm makes the robust decision using the majority voting process based on template matching. Also an algorithm is suggested to detect the bar positions in the 'sori' part based on Kalman filter. Every proposed algorithm in the paper works so well enough for the sample music sources of 'Pansori' that the results may be used to automatically transcribe the 'Pansori'.

• MALSORI
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• no.51
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• pp.71-84
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• 2004

In this paper, we propose the automatic speech database verification method(or called automatic verification) based on confidence measure for a large speech database. This method verifies the consistency between given transcription and speech using the confidence measure. The automatic verification process consists of two stages : the word-level likelihood computation stage and multi-level likelihood ratio computation stage. In the word-level likelihood computation stage, we calculate the word-level likelihood using the viterbi decoding algorithm and make the segment information. In the multi-level likelihood ratio computation stage, we calculate the word-level and the phone-level likelihood ratio based on confidence measure with anti-phone model. By automatic verification, we have achieved about 61% error reduction. And also we can reduce the verification time from 1 month in manual to 1-2 days in automatic.

• Proceedings of the KSPS conference
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• 2006.11a
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• pp.135-138
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• 2006

In this paper, we introduce a method for extracting grapheme-to-phoneme conversion rules from the transcription of speech synthesis database and a prosody modeling method using the light version of ToBI for a Korean conversational style TTS. We focused on representing the characteristics of the conversational speech style and the experimental results show that our proposed methods are suitable for developing a Korean conversional style TTS.

• Speech Sciences
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• v.8 no.1
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• pp.33-52
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• 2001

A bilingual sound dictionary in Korean and English has been created for a broad range of sound reference to cross-linguistic, dialectal, native language (L1)-transferred biological and allophonic variations. The paper demonstrates that the pronunciation dictionary of the lexicon is inadequate for sound reference due to the preponderance of unmarked sounds. The audio registry consists of the three-way comparison of 1) English speech from native English speakers, 2) Korean speech from Korean speakers, and 3) English speech from Korean speakers. Several sub-dictionaries have been created as the foundation research for independent development. They are 1) a pronunciation dictionary of the Korean lexicon in a keyboard-compatible phonetic transcription, 2) a sound dictionary of L1-interfered language, and 3) an audible dictionary of Korean sounds. The dictionary was designed to facilitate the exchange of the speech signal and its corresponding text data on various media particularly on CD-ROM. The methodology and findings of the construction are discussed.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.401-403
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• 2000

본 논문에서는 일한 음차 변환을 이용한 음성인식 및 합성기를 구현하였다. 음성인식의 경우 CV, VCCV, VCV, VV, VC 단위를 사용하였다. 이와 같이 단위별로 미리 구축된 모델을 결합함으로써 음성인식 시스템을 구축하였다. 따라서 일한 음차 변환을 적용하게 되면 인식 대상이 일어단어일 경우에도 이를 한글 발음으로 변환한 후 그에 해당하는 모델을 생성함으로써 인식이 가능하다. 음성 합성기의 경우 합성에 필요한 한국어 음성 데이터 베이스를 구축하고, 입력되는 텍스트에 따라 이를 연결하여 합성음을 생성한다. 일어가 입력될 경우 일한 음차 변환 규칙을 이용하여 입력된 일어 발음을 한글로 바꾸어 준 후 입력하게 되므로 별도의 일어 합성기 없이도 합성음을 생성할 수 있다.

• MALSORI
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• no.61
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• pp.101-111
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• 2007

A modified speech recogniser have been proposed for automatic capitalisation generation to improve the readability of English speech recognition output. In this modified speech recogniser, every word in its vocabulary is duplicated: once in a de-caplitalised form and again in the capitalised forms. In addition its language model is re-trained on mixed case texts. In order to evaluate the performance of the proposed system, experiments of automatic capitalisation generation were performed for 3 hours of Broadcast News(BN) test data using the modified HTK BN transcription system. The proposed system produced an F-measure of 0.7317 for automatic capitalisation generation with an SER of 48.55, a precision of 0.7736 and a recall of 0.6942.