• Phonetics and Speech Sciences
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• v.8 no.4
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• pp.103-113
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• 2016

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.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.4
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• pp.418-430
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• 2012

The present paper reviews the micro and nano nondestructive evaluation(NDE) technique that is possible to investigate the surface and measure the acoustic properties. The technical theory, features and applications of the ultrasonic atomic force microscopy(UAFM) and scanning acoustic microscopy(SAM) are illustrated. Especially, these technologies are possible to evaluate the mechanical properties in micro/nano structure and surface through the measurement of acoustic properties in addition to the observation of surface and subsurface. Consequently, it is thought that technique developments and applications of these micro/nano NDE in advanced industrial parts together with present nondestructive industry are widely possible hereafter.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.07a
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• pp.585-591
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• 2000

The wavelet transform is the most recent technique for processing signals with time-varying spectra. In this paper, the wavelet transform is utilized to improved the assessment and multi-resolution analysis of acoustic emission signals generating in partial discharge. This paper especially deals with the assessment of process statistical parameter using the features extracted from the wavelet coefficients of measured acoustic emission signals in case of applied voltage 20[kv]. Since the parameter assessment using all wavelet coefficients will often turn out leads to inefficient or inaccurate results, we selected that level-3 stage of multi decomposition in discrete wavelet transform. We applied FIR(Finite Impulse Response)digital filter algorithm in discrete to suppression for random noise. The white noise be included high frequency component denoised as decomposition of discrete wavelet transform level-3. We make use of the feature extraction parameter namely, maximum value of acoustic emission signal, average value, dispersion, skewness, kurtosis, etc. The effectiveness of this new method has been verified on ability a diagnosis transformer go through feature extraction in stage of acting(the early period, the last period) .

• MALSORI
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• no.21_24
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• pp.43-89
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• 1992

In this thesis, the prominent aspect of word accent in standard Korean is studied by auditory test and acoustic analysis experiment. The definition of 'accent' is, following Hoyoung Lee's discussion(1990), to be described as 'the means whereby a focused part of an utterance is made to stand out in order to concentrate the hearer's attention on it.' That is to say, the ten of 'accent' may be described in terms of phonological phenomenon and the accented syllable can be phonetically prominent as the result of those phonological process. Prosodic features may have different characteristics in different languages whether they contain linguistically important functions or not. Thus the characteristics of word accent in standard Korean will be determined as the content and trait of prosodic features. Following this viewpoint, present study looked over prosodic features which may effect the characteristics of word accent in standard Korean, through systematic experimental procedure. And the result of this experiment has been verified by statistical method, the T-test, for the purpose of identifying the relatedness among prosodic features(parameters). This thesis, therefore, aimed to investigate the intrinsic acoustic and physical qualities of the word accent in standard Korean. Nonsense words composed by 'mal' and 'ma' which can be divided into 'heavy syllable' and 'light syllable' quoted from Hyman(1975) have been classified into 28 types with respect to syllable numbers(2 syl., 3 sy1., 4 syl.) and these words have become the target of auditory test and acoustic experiment. As the result of those experimental Procedures, the word accent in standard Korean may be said that it has a tendency of fixing first two syllables regardless of syllable numbers. The syllable types of HH, HL, LL in the first two syllables may be prominent at first syllable and the type of H may be at second syllable. Various prosodic features(parameters) including duration, intensity, and Fo(purely phonetic terms) were also strengthened in those positions. The result of this experiment can be cleared up like these : 1. The most important feature is proved as 'duration', the feature of intensity resulted in more subsidiary one than the feature of duration. 2. Fo( fundamental frequency) could be observed as having some coherent contour through almost all syllable types(99 ％), that is, in 2 syllable types, it had rising contour, in 2 syllable types, rising-falling contour, and in 4 syllable types, it contained rising-falling-rising contour. The result of auditory test was different with those contour forms of all Fo surveyed. With respect to these results, the discuss for Fo is determined' to be excluded comparing other features. 3. Finally, this thesis resulted in a decision that the word accent in standard Korean may has fixed(somewhat weaker) accent, especially fixed at first two syllables in almost all words. 4. Various kinds of syllable types related with 2,3,4 syllables, therefore, can be reclassified into 4 types of HH, HL, LH, LL following the concept of accent fixing placement(i.e. first two syllables). In these 4 types, the types of HH, HL, LL were prominent at the position of the first syllable , and the type of LH was prominent at the second syllable otherwise.

• The Journal of the Acoustical Society of Korea
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• v.35 no.1
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• pp.63-73
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• 2016

It is widely acknowledged that the human auditory system is organized tonotopically and people generally listen to sounds as a function of frequency distribution through the auditory system. However, it is still unclear how acoustic features of speech sounds are indicated to the human brain in terms of speech perception. Thus, the purpose of this study is to investigate whether two sounds with similar high-frequency characteristics in the acoustic analysis show similar results at the level of auditory brainstem. Thirty three young adults with normal hearing participated in the study. As stimuli, two Korean monosyllables (i.e., /ja/ and /cha/) and four frequencies of toneburst (i.e., 500, 1000, 2000, and 4000 Hz) were used to elicit the auditory brainstem response (ABR). Measures of monosyllable and toneburst were highly replicable and the wave V of waveform was detectable in all subjects. In the results of Pearson correlation analysis, the /ja/ syllable had a high correlation with 4000 Hz of toneburst which means that its acoustic characteristics (i.e., 3671~5384 Hz) showed the same results in the brainstem. However, the /cha/ syllable had a high correlation with 1000 and 2000 Hz of toneburst although it has acoustical distribution of 3362~5412 Hz. We concluded that there was disagreement between acoustic features and physiology outcomes at the auditory brainstem level. This finding suggests that an acoustical-perceptual mapping study is needed to scrutinize human speech perception.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.37-43
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• 2021

Using the acoustic features of speech, important social and linguistic information about the speaker can be obtained, and one of the key features is the dialect. A speaker's use of a dialect is a major barrier to interaction with a computer. Dialects can be distinguished at various levels such as phonemes, syllables, words, phrases, and sentences, but it is difficult to distinguish dialects by identifying them one by one. Therefore, in this paper, we propose a lightweight Korean dialect classification model using only MFCC among the features of speech data. We study the optimal method to utilize MFCC features through Korean conversational voice data, and compare the classification performance of five Korean dialects in Gyeonggi/Seoul, Gangwon, Chungcheong, Jeolla, and Gyeongsang in eight machine learning and deep learning classification models. The performance of most classification models was improved by normalizing the MFCC, and the accuracy was improved by 1.07% and F1-score by 2.04% compared to the best performance of the classification model before normalizing the MFCC.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.47-54
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• 2003

Research during the past several years has established the effectiveness of acoustic emission (AE)-based sensing methodologies for machine condition analysis and process. AE has been proposed and evaluated for a variety of sensing tasks as well as for use as a technique for quantitative studies of manufacturing process. STD11 has been known as difficult-to-cut materials. The micro-grooving machine was developed for this study and the experiments were performed using CBN blade for machining STD11. Evaluating the machining conditions, frequency spectrum analysis of acoustic emission (AE) signals according to each conditions were applied. Fuzzy clustering method for associating the preprocessor outputs with the appropriate decisions was followed by frequency spectrum analysis. FFT is used to decompose AE signal into different frequency bands in time domain, the root mean square (RMS) values extracted from the decomposed signal of each frequency band were used as features.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.818-821
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• 2002

In this paper, we propose Neuro-Fuzzy discrimination method of the new and old bill using bill money acoustic data. The concept of the histogram is introduced to improve the processing time into the proposal system. The adaptative filter is used in order to remove the motor sound from an observed bill money acoustic data. The output signal of this adaptive digital filter is converted into not only a spectrum but also a histogram. It became easy that features of the paper money sound were extracted from the bill money acoustic data. The spectral data and the histogram is obtained like this, and it become an input pattern of the neural network(NN). Then, the discrimination result of the NN is finally judged by the fuzzy inferece in the new bill or the exhaustion bill.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.245-248
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• 1997

The distilled water is used for the ultrasonic wave propagating material in the measurements of broadband ultrasonic attenuation (BUA) that is applied in industrial and medical applications, The acoustic impedance of water is significantly changed with its temperature. Therefore, the quantitative evaluation of BUA with temperature and the ultrasonic wave propagating distance is highly needed. In this study, we evaluated the variation of attenuation with change in temperature. To measure the variation of BUA in the low frequency region at the temperatures, 27$^{\circ}C$, 29$^{\circ}C$, and 31$^{\circ}C$, we tested the Plyethylene, Teflon, MC-Nylon, Urethane specimens and analyzed the center frequency, frequency bandwidth, spectral peak amplitude. The results showed that BUA value appeared to be lower with increasing temperature. This may be due to the fact that the frequency feature of ultrasonic wave is affected by not only the specific gravity, acoustic impedence, but material crystalline, porosity, the distance of ultrasonic wave propagation in water.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.4
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• pp.22-28
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• 2006

Detection of exit burr is very important in manufacturing automation. In this paper, acoustic emission(AE) was used to detect the burr formation during milling. By using wavelet transformation, AE data was compressed without unnecessary details. Then the transformed data were used as selected features (inputs) of a back-propagation artificial neural net. In order to validate the proposed scheme, the wavelet based ANN results were compared with cutting condition(cutting speed, feed, depth of cut, etc.) based ANN results.