• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1042-1045
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• 2003

In this paper, we propose the speaker identification system that uses vowel that has speaker's characteristic. System is divided to speech feature extraction part and speaker identification part. Speech feature extraction part extracts speaker's feature. Voiced speech has the characteristic that divides speakers. For vowel extraction, formants are used in voiced speech through frequency analysis. Vowel-a that different formants is extracted in text. Pitch, formant, intensity, log area ratio, LP coefficients, cepstral coefficients are used by method to draw characteristic. The cpestral coefficients that show the best performance in speaker identification among several methods are used. Speaker identification part distinguishes speaker using Neural Network. 12 order cepstral coefficients are used learning input data. Neural Network's structure is MLP and learning algorithm is BP (Backpropagation). Hidden nodes and output nodes are incremented. The nodes in the incremental learning neural network are interconnected via weighted links and each node in a layer is generally connected to each node in the succeeding layer leaving the output node to provide output for the network. Though the vowel extract and incremental learning, the proposed system uses low learning data and reduces learning time and improves identification rate.

• Speech Sciences
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• v.2
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• pp.25-44
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• 1997

When listening the various speech synthesis systems developed and being used in our country, we find that though the quality of these systems has improved, they lack naturalness. Moreover, since the voice color of these systems are limited to only one recorded speech DB, it is necessary to record another speech DB to create different voice colors. 'Voice Color' is an abstract concept that characterizes voice personality. So speech synthesis systems need a voice color control function to create various voices. The aim of this study is to examine several factors of voice color control rules for the text-to-speech system which makes natural and various voice types for the sounding of synthetic speech. In order to find such rules from natural speech, glottal source parameters and frequency characteristics of the vocal tract for several voice colors have been studied. In this paper voice colors were catalogued as: deep, sonorous, thick, soft, harsh, high tone, shrill, and weak. For the voice source model, the LF-model was used and for the frequency characteristics of vocal tract, the formant frequencies, bandwidths, and amplitudes were used. These acoustic parameters were tested through multiple regression analysis to achieve the general relation between these parameters and voice colors.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.26 no.2
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• pp.117-121
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• 2015

Background : Cepstral analysis which is obtained from Fourier transformation of spectrum has been known to be effective indicator to analyze the voice disorder. To evaluate the voice disorder, phonation of sustained vowel /a/ sound or continuous speech have been used but the former was limited to capture hoarseness properly. This study is aimed to compare the effectiveness in analysis of cepstrum between the sustained vowel /a/ sound and continuous speech. Methods : From March 2012 to December 2014, total 72 patients was enrolled in this study, including 24 unilateral vocal cord palsy, vocal nodule and vocal polyp patients, respectively. The entire patient evaluated their voice quality by VHI (Voice Handicap Index) before and after treatment. Phonation of sustained vowel /a/ sample and continuous speech using the first sentence of autumn paragraph was subjected by cepstral analysis and compare the pre-treatment group and post-treatment group. Results : The measured values of pre and post treatment in CPP-a (cepstral peak prominence in /a/ vowel sound) was 13.80, 13.91 in vocal cord palsy, 16.62, 17.99 in vocal cord nodule, 14.19, 18.50 in vocal cord polyp respectively. Values of CPP-s (cepstral peak prominence in text-based speech) in pre and post treatment was 11.11, 12.09 in vocal cord palsy, 12.11, 14.09 in vocal cord nodule, 12.63, 14.17 in vocal cord polyp. All 72 patients showed subjective improvement in VHI after treatment. CPP-a showed statistical improvement only in vocal polyp group, but CPP-s showed statistical improvement in all three groups (p<0.05). Conclusion : In analysis of cepstrum, text-based analysis is more representative in voice disorder than vowel sound speech. So when the acoustic analysis of voice by cepstrum, both phonation of sustained vowel /a/ sound and text based speech should be performed to obtain more accurate result.

• Proceedings of the KSPS conference
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• 1996.10a
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• pp.542-547
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• 1996

Prosodic characteristics of natural speech, especially intonation, in many cases represent specific feelings of the speaker at the time of the utterance, with relatively vast variations of speaking styles over the same text. We analyzed a collected speech corpus, recorded with ten Slovene speakers. Interpretation of observed intonation contours was done for the purpose of modelling the intonation contour in synthesis process. We devised a scheme for modeling the intonation contour for different types of intonation units based on the results of analyzing intonation contours. The intonation scheme uses a superpositional approach, which defines the intonation contour as the sum of global (intonation unit) and local (accented syllables or syntactic boundaries) components. Near-to-natural intonation contour was obtained by rules, using only the text of the utterance as input.

• Speech Sciences
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• v.10 no.2
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• pp.7-25
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• 2003

Predicting the right prosodic elements is a key factor in improving the quality of synthesized speech. Prosodic elements include break, pitch, duration and loudness. Pitch, which is realized by Fundamental Frequency (F0), is the most important element relating to the quality of the synthesized speech. However, the previous method for predicting the F0 appears to reveal some problems. If voiced and unvoiced sounds are not correctly classified, it results in wrong prediction of pitch, wrong unit of triphone in synthesizing the voiced and unvoiced sounds, and the sound of click or vibration. This kind of feature is usual in the case of the transformation from the voiced sound to the unvoiced sound or from the unvoiced sound to the voiced sound. Such problem is not resolved by the method of grammar, and it much influences the synthesized sound. Therefore, to steadily acquire the correct value of pitch, in this paper we propose a new model for predicting and classifying the voiced and unvoiced sounds using the CART tool.

• Speech Sciences
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• v.1
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• pp.295-314
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• 1997

In this study, we will implement a flexible formant analysis and synthesis system. In the analysis part, the two-channel (i.e., speech & EGG signals) approach is investigated for accurate estimation of formant information. The EGG signal is used for extracting exact pitch information that is needed for the pitch synchronous LPC analysis and closed phase LPC analysis. In the synthesis part, Klatt formant synthesizer is modified so that the user can change synthesis parameters arbitarily. Experimental results demonstrate the superiority of the two-channel analysis method over the one-channel(speech signal only) method in analysis as well as in synthesis. The implemented system is expected to be very helpful for studing the effects of synthesis parameters on the quality of synthetic speech and for the development of Korean text-to-speech(TTS) system with the formant synthesis method.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2431-2434
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• 2003

In this research, our goal is to realize Korean Distribute TTS system with server/client function in wireless network. The speech databases and some routines of TTS system is stuck with the server which has strong functions and we made Korean speech databases and accomplished research about DB which is suitable for distributed TTS. We designed a terminal has the minimum setting which operate this TTS and designed proper protocol so we will check action of Distributed TTS.

• The Journal of the Acoustical Society of Korea
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• v.20 no.4E
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• pp.31-38
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• 2001

A large-scale synthesis database for a unit selection based synthesis method usually retains redundant synthesis unit instances, which are useless to the synthetic speech quality. In this paper, to eliminate those instances from the synthesis database, we proposed a new pruning method called weighted vector quantization (WVQ). The WVQ reflects relative importance of each synthesis unit instance when clustering the similar instances using vector quantization (VQ) technique. The proposed method was compared with two conventional pruning methods through the objective and subjective evaluations of the synthetic speech quality: one to simply limit maximum number of instance, and the other based on normal VQ-based clustering. The proposed method showed the best performance under 50% reduction rates. Over 50% of reduction rates, the synthetic speech quality is not seriously but perceptibly degraded. Using the proposed method, the synthesis database can be efficiently reduced without serious degradation of the synthetic speech quality.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.10
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• pp.138-145
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• 1990

This paper present a rule-based speech synthesis method for improving the naturalness of synthetic speech and using the small data base based on demisyllable units. A 12-pole Linear Prediction Coding method is used to analyses demisyllable speech signals. A syllable and vowel concatenation rule is developed to improve the naturalness and intelligibility of the synthetic speech. in addiion, phonological structure transform rule using neural net and prosody rules are applied to the synthetic speech.

• The Journal of the Acoustical Society of Korea
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• v.18 no.4E
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• pp.26-30
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• 1999

This paper introduces a prosodic phrasing method in Korean to improve the naturalness of speech synthesis, especially in text-to-speech conversion. In prosodic phrasing, it is necessary to understand the structure of a sentence through a language processing procedure, such as part-of-speech (POS) tagging and parsing, since syntactic structure correlates better with the prosodic structure of speech than with other factors. In this paper, the prosodic phrasing procedure is treated from two perspectives: dependency parsing and prosodic phrasing using dependency relations. This is appropriate for Ural-Altaic, since a prosodic boundary in speech usually concurs with a governor of dependency relation. From experimental results, using the proposed method achieved 12% improvement in prosody boundary prediction accuracy with a speech corpus consisting 300 sentences uttered by 3 speakers.