• Speech Sciences
• /
• v.12 no.2
• /
• pp.29-41
• /
• 2005

This paper is to show the diphthong system of Jeju dialect speakers in their 70s or more on the basis of the acoustic analysis of their phonetic data. It is revealed through the analysis of their phonetic data that they clearly distinguish such diphthongs as [we], [w$\epsilon$], [yc] and [yo]. However, this paper shows that they are phonetically insensitive to the separation between [ye] and [y$\epsilon$] and they seldom make a precise pronunciation of diphthong [iy], which male speakers tend to pronounce to be [i] and female speakers to be [i].

• Phonetics and Speech Sciences
• /
• v.2 no.3
• /
• pp.47-63
• /
• 2010

This study provides a description of the glottal characteristics of the word-initial low vowels /a, $\ae$/ in terms of a set of acoustic parameters and discusses glottal configuration as their acoustic correlates. Furthermore, it examines the effect of prosodic boundary on the glottal properties of the vowels, seeking an account of the possible role of prosodic structure based on prosodic theory. Acoustic parameters reported to indicate glottal characteristics were obtained from the measurements made directly from the speech spectrum on recordings of Korean and English collected from 45 speakers. They consist of two separate groups of native Korean and native English speakers, each including both male and female speakers. Based on the three acoustic parameters of open quotient (OQ), first-formant bandwidth (B1), and spectral tilt (ST), comparisons were made between the speech of males and females, between the speech of native Korean and native English speakers, and between Korean and English produced by native Korean speakers. Acoustic analysis of the experimental data indicates that some or all glottal parameters play a crucial role in differentiating the speech groups, despite substantial interspeaker variations. Statistical analysis of the Korean data indicates prosodic strengthening with respect to the acoustic parameters B1 and OQ, suggesting acoustic enhancement in terms of the degree of glottal abduction and the glottal closure during a vibratory cycle.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2003.10a
• /
• pp.137-142
• /
• 2003

A fundamental study for developing a system of fault diagnosis of a pump is performed by using neural network. The acoustic signals were obtained and converted to frequency domain for normal products and artificially deformed products. The signals were obtained in various driving frequencies in order to obtain many types of data from a limited number of pumps. The acoustic data in frequency domain were managed to multiples of real driving frequency with the aim of easy comparison. The neural network model used in this study was 3-layer type composed of input, hidden, and output layer. The normalized amplitudes at the multiples of real driving frequency were chosen as units of input layer, Various sets of teach signals made from original data by eliminating some random cases were used in the training. The average errors were approximately proportional to the number of untaught data. The results showed neural network trained by acoustic signals can be used as a simple method far a detection of machine malfunction or fault diagnosis.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.13 no.5
• /
• pp.81-86
• /
• 2004

A fundamental study for developing a system of fault diagnosis of a pump is performed by using neural network. The acoustic signals were obtained and converted to frequency domain for normal products and artificially deformed products. The signals were obtained in various driving frequencies in order to obtain many types of data from a limited number of pumps. The acoustic data in frequency domain were managed to multiples of real driving frequency with the aim of easy comparison. The neural network model used in this study was 3-layer type composed of input, hidden, and output layer. The normalized amplitudes at the multiples of real driving frequency were chosen as units of input layer. Various sets of teach signals made from original data by eliminating some random cases were used in the training. The average errors were approximately proportional to the number of untaught data. The results showed neural network trained by acoustic signals can be used as a simple method for a detection of machine malfuction or fault diagnosis.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.9
• /
• pp.21-27
• /
• 2019

In this paper, we propose a deep auto-encoder-based pipe leak detection (PLD) technique from time-series acoustic data collected by microphone sensor nodes. The key idea of the proposed technique is to learn representative features of the leak-free state using leak-free time-series acoustic data and the deep auto-encoder. The proposed technique can be used to create a PLD model that detects leaks in the pipeline in an unsupervised learning manner. This means that we only use leak-free data without labeling while training the deep auto-encoder. In addition, when compared to the previous supervised learning-based PLD method that uses image features, this technique does not require complex preprocessing of time-series acoustic data owing to the unsupervised feature extraction scheme. The experimental results show that the proposed PLD method using the deep auto-encoder can provide reliable PLD accuracy even considering unsupervised learning-based feature extraction.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
• /
• v.12 no.1
• /
• pp.17-21
• /
• 2001

Aims of study : The purpose of this study is to measure the chronic and daily voice burden of the professionals in their actual working places. These will be a valuable guideline for preventing and controlling the voice production of professionals. Material and method : Our study was selected to the 10 female telephone operators in the Asan Medical Center, ages ranging from 22 to 38 years old. The symptoms and acoustic analysis of both telephone operators and the controls were evaluated before and after their working. The symptoms were evaluated with questionaires, and the acoustic analysis was measured by using CSL (computerized speech laboratory) system. Results : The symptoms of the professional voice abusers are same as those symptoms in laryngeal fatigue. The acoustic analysis before their working were significantly increased in jitter and shimmer, in comparison with the data of the control. This shows that the experimental group is exposed to the chronic burden of voice production. The jitter, shimmer, and NHR after their working are significantly increased in comparison with the data of the acoustic analysis before their working. This also shows that the experimental group is exposed to the daily burden of voice production. Conclusion : The acoustic analysis of the professional voice overusers has objectively measured that there are chronic and daily overloading to the voice of operators, and these will be a valuable data for preventing and controlling the professionals that abuse their voice.

• The Journal of the Acoustical Society of Korea
• /
• v.19 no.5
• /
• pp.46-52
• /
• 2000

Internal waves existing in the stratified ocean significantly affect acoustic propagation. In order to understand the effects of internal waves on acoustic propagation, the sound speed fluctuations due to internal waves are generated based on the Garrett-Munk spectrum which is derived from measured data in the East Sea. The acoustic propagation, where internal waves are present, is simulated numerically using a Galerkin higher order parabolic equation method(SNUPE). These results show favorable comparison to in-situ acoustic propagation data from the East Sea. To investigate the effects of acoustic propagation in random media, scintillation index is adopted and comparison between the measured and numerically simulated data is made.

• Proceedings of the Earthquake Engineering Society of Korea Conference
• /
• 2000.04a
• /
• pp.63-69
• /
• 2000

Korea Institute of Geology Mining and Materials(KIGAM) cooperating with Southern Methodist University(SMU) has been operating seismo-acoustic array in Chul-Won area to discriminate man-made explosions from natural earthquakes since at the end of July 1999. In order to characterize propagation parameters of detected seismo-acoustic signal and to associate these signals as a blast event accompanying seismic and acoustic signals simultaneously it is necessary to understand infrasound wave propagation in the atmosphere. Two comparable Effective Sound Velocity Structures(ESVS) in atmosphere were constructed by using empirical model (MSISE90 and HWM93) and by aerological observation data of Korea Meteorological Administration (KMA) at O-San area. Infrasound propagation path computed by empirical model resulted in rare arival of refracted waves on ground less than 200km from source region. On the other hand Propagation paths by KMA more realistic data had various arrivals at near source region and well agreement with analyzed seismo-acoustic signals from Chul-Won data. And infrasound propagation in specific direction was very influenced by horizontal wind component in that direction. Linear travel time curve drawn up by 9 days data of the KMA in autumn season showed 335.6m/s apparent sound velocity in near source region. The propagation characteristics will be used to associate seismo-acoustic signals and to calculate propagation parameters of infrasound wave front.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.4
• /
• pp.136-141
• /
• 2011

In this paper, we propose an approach to improve the data detection performance of the acoustic data transmission system based on the modulated complex lapped transform (MCLT). We first present an effective analysis of the features and the detection method of data in the acoustic data transmission system. And then feature vectors which are applied to the Gaussian mixture model (GMM) are selected from relevant parameters of the previous system for the efficient data detection. For the purpose of evaluating the performance of the proposed algorithm, Bit error rate (BER) of the received data was measured at different environments (music genres (rock, pop, classic, jazz) and different distances (1m∼5m) from the loudspeaker to the microphone in a office room) and yields better results compared with the conventional scheme of the acoustic data transmission system based on the MCLT.

• The Journal of the Acoustical Society of Korea
• /
• v.43 no.3
• /
• pp.285-292
• /
• 2024

When calculating sonar detection probability, underwater acoustic uncertainty is assumed to be normal distributed with a standard deviation of 8 dB to 9 dB. However, due to the variability in experimental areas and ocean environmental conditions, predicting detection performance requires accounting for underwater acoustic uncertainty based on ocean experimental data. In this study, underwater acoustic uncertainty was determined using measured mid-frequency (2.3 kHz, 3 kHz) noise level and transmission loss data collected in the shallow water of the East Sea. After calculating the predictable probability of detection reflecting underwater acoustic uncertainty based on ocean experimental data, we compared it with the conventional detection probability results, as well as the predictable probability of detection results considering the uncertainty of the Rayleigh distribution and a negatively skewed distribution. As a result, we confirmed that differences in the detection area occur depending on each underwater acoustic uncertainty.