• Phonetics and Speech Sciences
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• v.14 no.2
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• pp.11-17
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• 2022

English vowels play an important role in verbal communication. However, Korean students tend to experience difficulty pronouncing a certain set of vowels despite extensive education in English. The aim of this study is to apply speech recognition software to evaluate Korean students' pronunciation of English vowels in minimal pair words and then to examine acoustic characteristics of the pairs in order to check their pronunciation problems. Thirty female Korean college students participated in the recording. Speech recognition rates were obtained to examine which English vowels were correctly pronounced. To compare and verify the recognition results, such acoustic analyses as the first and second formant trajectories and durations were also collected using Praat. The results showed an overall recognition rate of 54.7%. Some students incorrectly switched the tense and lax counterparts and produced the same vowel sounds for qualitatively different English vowels. From the acoustic analyses of the vowel formant trajectories, some of these vowel pairs were almost overlapped or exhibited slight acoustic differences at the majority of the measurement points. On the other hand, statistical analyses on the first formant trajectories of the three vowel pairs revealed significant differences throughout the measurement points, a finding that requires further investigation. Durational comparisons revealed a consistent pattern among the vowel pairs. The author concludes that speech recognition and analysis software can be useful to diagnose pronunciation problems of English-language learners.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.3
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• pp.247-252
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• 2017

The purpose of this study is to suggest the visual teaching method for the English vowel pronunciation, especially for the hearing-impaired who mostly rely on the visual aids, based on the SVM technique. By extracting phonetic features using the SVM technique from the sounds that are hard to hear by ear, the lip shapes for each vowel were refined. The lip shape refinement for vowels is advantageous in that language learners can easily see the movement of articulators by eye, and it is helpful for learning and teaching English vowels for the hearing-impaired.

• Journal of Korea Multimedia Society
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• v.22 no.8
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• pp.852-859
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• 2019

With the development of IT technology and smart devices, various applications utilizing image information are being developed. In order to provide an intuitive interface for pronunciation recognition, there is a growing need for research on pronunciation recognition using mouth feature values. In this paper, we propose a system to distinguish Korean vowel pronunciations by detecting feature points of lips region in images and applying Bayesian based learning model. The proposed system implements the recognition system based on Bayes' theorem, so that it is possible to improve the accuracy of speech recognition by accumulating input data regardless of whether it is speaker independent or dependent on small amount of learning data. Experimental results show that it is possible to effectively distinguish Korean vowels as a result of applying probability based Bayesian classification using only visual information such as mouth shape features.

• Phonetics and Speech Sciences
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• v.6 no.2
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• pp.163-174
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• 2014

Korean L2 speakers have many problems learning the pronunciation of English words. One of these problems is vowel epenthesis. Vowel epenthesis is the insertion of vowels into or between words, and Korean learners of English typically do this between successive consonants, either within clusters, or across syllables, word boundaries or following final coda consonants. The aim of this study was to investigate whether individual differences in vowel epenthesis are more closely related to the perception and production of segments (vowels and consonants) and prosody or if they are relatively independent from these processes. Subjects completed a battery of production and perception tasks. They read sentences, identified vowels and consonants, read target words likely to have epenthetic vowels (e.g., abduction) and demonstrated stress recognition and epenthetic vowel perception. The results revealed that Korean second-language learners (L2) have problems with vowel epenthesis in production and perception, but production and perception abilities were not correlated with one another. Vowel epenthesis was strongly related to vowel production and perception, suggesting that problems with segments may be combined with L1 phonotactics to produce epenthesis.

• Phonetics and Speech Sciences
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• v.5 no.4
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• pp.145-155
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• 2013

This study investigated the articulatory characteristics of Korean singleton and geminate sonorants in the word-medial position, effects of the duration of the sonorant consonant and the preceding vowel on perception, and the difference between native Korean speakers and foreign learners of Korean in perceiving the singleton and geminate consonant contrast. The Korean sonorant consonants(/m, n, l/) are examined from the VCCV, VCV sequences through speech production and perception experiments. The results suggest that the duration of the sonorant consonant is the most important factor for native Korean speakers to recognize whether sonorants are overlapped, and the duration of preceding vowel and other factors affect the recognition of singleton/geminate consonant contrast if the duration is not obvious. A perception experiment showed Chinese Korean language learners did not clearly distinguish singleton consonants from geminate consonants. The results of this study provide basic data for recognition of singleton/geminate consonant contrast in word-medial of Korean language, and can be utilized for teaching Korean pronunciation as a foreign language.

• Phonetics and Speech Sciences
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• v.7 no.3
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• pp.139-149
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• 2015

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 [ɥi] and [$w{\varepsilon}$]. 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.

• KIISE Transactions on Computing Practices
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• v.20 no.11
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• pp.567-572
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• 2014

In recent years, computing and networking technologies have been developed, and the communication equipments have become smaller and the mobility has increased. In addition, the demand for easily-operated speech recognition has increased. This paper proposes method of recognizing the Korean phoneme 'ㅏ'. A phoneme is the smallest unit of sound, and it plays a significant role in speech recognition. However, the precise recognition of the phonemes has many obstacles since it has many variations in its pronunciation. This paper proposes a simple and efficient method that can be used to recognize a Korean vowel 'ㅏ'. The proposed method is based on the common features that are extracted from the 'ㅏ' waveform sequences, and this is simpler than when using the previous complex methods. The experimental results indicate that this method has a more than 90 percent accuracy in recognizing 'ㅏ'.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.4
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• pp.9-16
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• 2020

Pronunciation recognition systems that use only video information and ignore voice information can be applied to various customized services. In this paper, we develop a system that applies a Bayesian classifier to distinguish Korean vowels via lip shapes in images. We extract feature vectors from the lip shapes of facial images and apply them to the designed machine learning model. Our experiments show that the system's recognition rate is 94% for the pronunciation of 'A', and the system's average recognition rate is approximately 84%, which is higher than that of the CNN tested for comparison. Our results show that our Bayesian classification method with feature values from lip region landmarks is efficient on a small training set. Therefore, it can be used for application development on limited hardware such as mobile devices.

• Journal of the Korea Computer Industry Society
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• v.2 no.6
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• pp.867-874
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• 2001

In this paper, considering the pronunciation characteristic of Korean, recognition units which can shorten the recognition time and reflect the coarticulation effect simultaneously are suggested. These units are composed of monophone and hipbone ones. Monophone units are applied to the vowels which represent stable characteristic. Biphones are used to the consonant which vary according to adjacent vowel. In the experiment of word recognition of PBW445 database, the compound units result in comparable recognition accuracy with 57％ speed up compared with triphone units and better recognition accuracy with similar speed. In addition, we can reduce the memory size because of fewer units.

• The Journal of the Acoustical Society of Korea
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• v.6 no.2
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• pp.38-47
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• 1987

As Korean language can be phonemically classified according to the characteristic and structure of its pronunciation, Korean syllables can be divided into the phonemes such as consonant and vowel. The divided phonemes are analyzed by using the method of partial autocorrelation, and the order of partial autocorelation coefficient is 15. In analysis, it is shown that each characteristic of the same consonants, vowels, and end consonant in syllables in similar. The experiments is carried out by dividing 675 syllables into consonants, vowels, and end consonants. The recognition rate of consonants, vowels, end-consonants, and syllables are $85.0(\%)$, $90.7(\%)$, $85.5(\%)$and $72.1(\%)$ respectively. In conclusion, it is shown that Korean syllables, divided by the phonemes, are analyzed and recognized with minimum data and short processing time. Furthermore, it is shown that Korean syllables, words and sentences are recognized in the same way.