• Speech Sciences
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• v.11 no.3
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• pp.131-142
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• 2004

Speaker identification system basically functions by comparing spectral energy of an individual production model with that of an input signal. This study aimed to develop a new speaker identification system from two parameters from the spectral energy of numeric sounds: difference sum and correlation coefficient. A narrow-band spectrogram yielded more stable spectral energy across time than a wide-band one. In this paper, we collected empirical data from four male speakers and tested the speaker identification system. The subjects produced 18 combinations of three-digit numeric. sounds !en times each. Five productions of each three-digit number were statistically averaged to make a model for each speaker. Then, the remaining five productions were tested on the system. Results showed that when the threshold for the absolute difference sum was set to 1200, all the speakers could not pass the system while everybody could pass if set to 2800. The minimum correlation coefficient to allow all to pass was 0.82 while the coefficient of 0.95 rejected all. Thus, both threshold levels can be adjusted to the need of speaker identification system, which is desirable for further study.

• The Journal of the Acoustical Society of Korea
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• v.27 no.8
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• pp.418-426
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• 2008

In this paper, we propose an algorithm for the frequency channel segmentation using peaks and valleys in spectrogram. The frequency channel segments means that local groups of channels in frequency domain that could be arisen from the same sound source. The proposed algorithm is based on the smoothed spectrum of the input sound. Peaks and valleys in the smoothed spectrum are used to determine centers and boundaries of segments, respectively. To evaluate a suitableness of the proposed segmentation algorithm before that the grouping stage is applied, we compare the synthesized results using ideal mask with that of proposed algorithm. Simulations are performed with mixed speech signals with narrow band noises, wide band noises and other speech signals.

• Speech Sciences
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• v.9 no.3
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• pp.3-16
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• 2002

We examined some problems in speaker identification procedures: transformation of acoustic parameters into auditory scales, invalid measurement values, and comparability of spectral energy values across the frequency range. To resolve those problems, we analyzed the acoustic spectral energy of three Korean numbers produced by ten female students from narrow-band spectrograms at 19 proportional time points of each voiced segment. Then, cells of the first five spectral matrices were averaged to form a matrix model for each speaker. The correlation coefficients and sum of the absolute amplitude difference in each pair of the spectral models of the ten subjects were obtained. Also, some individual matrix models were compared to those of the same subject or the other subject with a similar spectral model. Results showed that in numbers '2' and '9' subjects could not be clearly distinguished from the others but in number '4' it shed some possibility of setting threshold values for speaker identification if we employed the coefficients and the sum of absolute difference. Further studies would be desirable on various combinations of the range of long-term average spectra and the degree of signal pre-emphasis.

• Phonetics and Speech Sciences
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• v.3 no.3
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• pp.99-108
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• 2011

The perturbation parameters like jitter, shimmer, and signal-to-noise ratio (SNR) are largely estimated in the particular segment from the subjective or whole portion of the given pathological voice signal although there are many possible regions to be able to analyze the voice signals. In this paper, the pathological voice signals were classified as type 1, 2, 3, or 4 according to narrow band spectrogram and the value differences of the perturbation parameters extracted in the subjective and entire portion tended to be getting bigger as from type 1 to type 4 signals. Therefore, sample selection method based on moving window to analyze type 2 and 3 signals as well as type 1 signals is proposed. Although type 3 signals cannot be analyzed using the perturbation analysis, the type 3 signals by selecting out the samples in which error count is less than 10 through moving window were analyzed. At present, there is no method to be able to analyze the type 4 signals. Future research will endeavor to determine the best way to evaluate such voices.

• Phonetics and Speech Sciences
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• v.13 no.3
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• pp.31-37
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• 2021

The fundamental frequency, or f0, is an important acoustic measure in the prosody of human speech. The current study examined the f0 distribution of a corpus of spontaneous speech in order to provide normative data for Korean speakers. The corpus consists of 40 speakers talking freely about their daily activities and their personal views. Praat scripts were created to collect f0 values, and a majority of obvious errors were corrected manually by watching and listening to the f0 contour on a narrow-band spectrogram. Statistical analyses of the f0 distribution were conducted using R. The results showed that the f0 values of all the Korean speakers were right-skewed, with a pointy distribution. The speakers produced spontaneous speech within a frequency range of 274 Hz (from 65 Hz to 339 Hz), excluding statistical outliers. The mode of the total f0 data was 102 Hz. The female f0 range, with a bimodal distribution, appeared wider than that of the male group. Regression analyses based on age and f0 values yielded negligible R-squared values. As the mode of an individual speaker could be predicted from the median, either the median or mode could serve as a good reference for the individual f0 range. Finally, an analysis of the continuous f0 points of intonational phrases revealed that the initial and final segments of the phrases yielded several f0 measurement errors. From these results, we conclude that an examination of a spontaneous speech corpus can provide linguists with useful measures to generalize acoustic properties of f0 variability in a language by an individual or groups. Further studies would be desirable of the use of statistical measures to secure reliable f0 values of individual speakers.