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- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
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한국인 화자의 외래어 발음 변이 양상과 음절 기반 외래어 자소-음소 변환
류혁수(Ryu, Hyuksu),나민수(Na, Minsu),정민화(Chung, Minhwa) 한국음성학회 2015 말소리와 음성과학 Vol.7 No.3
This paper aims to analyze pronunciation variations of loanwords produced by Korean and improve the performance of pronunciation modeling of loanwords in Korean by using syllable-based segmentation and phonological knowledge. The loanword text corpus used for our experiment consists of 14.5k words extracted from the frequently used words in set-top box, music, and point-of-interest (POI) domains. At first, pronunciations of loanwords in Korean are obtained by manual transcriptions, which are used as target pronunciations. The target pronunciations are compared with the standard pronunciation using confusion matrices for analysis of pronunciation variation patterns of loanwords. Based on the confusion matrices, three salient pronunciation variations of loanwords are identified such as tensification of fricative [s] and derounding of rounded vowel [?i] and [w?]. In addition, a syllable-based segmentation method considering phonological knowledge is proposed for loanword pronunciation modeling. Performance of the baseline and the proposed method is measured using phone error rate (PER)/word error rate (WER) and F-score at various context spans. Experimental results show that the proposed method outperforms the baseline. We also observe that performance degrades when training and test sets come from different domains, which implies that loanword pronunciations are influenced by data domains. It is noteworthy that pronunciation modeling for loanwords is enhanced by reflecting phonological knowledge. The loanword pronunciation modeling in Korean proposed in this paper can be used for automatic speech recognition of application interface such as navigation systems and set-top boxes and for computer-assisted pronunciation training for Korean learners of English.
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조음자질을 이용한 한국인 학습자의 영어 발화 자동 발음 평가
류혁수(Ryu, Hyuksu),정민화(Chung, Minhwa) 한국음성학회 2016 말소리와 음성과학 Vol.8 No.4
This paper aims to propose articulatory features as novel predictors for automatic pronunciation assessment of English produced by Korean learners. Based on the distinctive feature theory, where phonemes are represented as a set of articulatory/phonetic properties, we propose articulatory Goodness-Of-Pronunciation(aGOP) features in terms of the corresponding articulatory attributes, such as nasal, sonorant, anterior, etc. An English speech corpus spoken by Korean learners is used in the assessment modeling. In our system, learners’ speech is forced aligned and recognized by using the acoustic and pronunciation models derived from the WSJ corpus (native North American speech) and the CMU pronouncing dictionary, respectively. In order to compute aGOP features, articulatory models are trained for the corresponding articulatory attributes. In addition to the proposed features, various features which are divided into four categories such as RATE, SEGMENT, SILENCE, and GOP are applied as a baseline. In order to enhance the assessment modeling performance and investigate the weights of the salient features, relevant features are extracted by using Best Subset Selection(BSS). The results show that the proposed model using aGOP features outperform the baseline. In addition, analysis of relevant features extracted by BSS reveals that the selected aGOP features represent the salient variations of Korean learners of English. The results are expected to be effective for automatic pronunciation error detection, as well.
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일본인 한국어 학습자의 분절음 실현과 발음 평가의 상관성
홍혜진(Hong, Hyejin),류혁수(Ryu, Hyuksu),정민화(Chung, Minhwa) 한국음성학회 2014 말소리와 음성과학 Vol.6 No.4
This study investigates the effects of Japanese learners’ Korean segmental production on pronunciation evaluation by Korean native raters. Read speech from 24 learners whose native language is Japanese are transcribed at the phonemic level, and confusion matrices are generated based on the phonemic transcriptions. The deviance from the canonical pronunciation found in the learners’ speech is analyzed in terms of phoneme substitutions, vowel insertions, and consonant deletions. Each learner’s pronunciation is rated impressionistically by 5 Korean native raters. The result shows that the deviance from the canonical pronunciation is strongly correlated with the pronunciation evaluation scores. Especially, the rates of phoneme substitutions and vowel insertions which are very strongly correlated with the pronunciation evaluation scores.
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