• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2415-2418
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• 2003

In this paper, we present a new filter to adjust formant information. Spectral envelope in speech analysis shows information about characteristics of speech and formant information determines speech timbre. So, if formant position is adjusted, we can verify adjusted speech timbre. A presented filter is to adjust this formant. This filter is composed of triangular filters. Using this filter we could locate the formant frequency at target position.

• Speech Sciences
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• v.10 no.2
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• pp.85-95
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• 2003

In speech signal processing, it is very important to detect the pitch exactly in speech recognition, synthesis and analysis. If we exactly pitch detect in speech signal, in the analysis, we can use the pitch to obtain properly the vocal tract parameter. It can be used to easily change or to maintain the naturalness and intelligibility of quality in speech synthesis and to eliminate the personality for speaker-independence in speech recognition. In this paper, we proposed a new pitch detection algorithm. First, positive center clipping is process by using the incline of speech in order to emphasize pitch period with a glottal component of removed vocal tract characteristic in time domain. And rough formant envelope is computed through peak-fitting spectrum of original speech signal infrequence domain. Using the roughed formant envelope, obtain the smoothed formant envelope through calculate the linear interpolation. As well get the flattened harmonics waveform with the algebra difference between spectrum of original speech signal and smoothed formant envelope. Inverse fast fourier transform (IFFT) compute this flattened harmonics. After all, we obtain Residual signal which is removed vocal tract element. The performance was compared with LPC and Cepstrum, ACF. Owing to this algorithm, we have obtained the pitch information improved the accuracy of pitch detection and gross error rate is reduced in voice speech region and in transition region of changing the phoneme.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.381-384
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• 2002

In speech signal processing, it Is very important to detect the pitch exactly in speech recognition, synthesis and analysis. but, it is very difficult to pitch detection from speech signal because of formant and transition amplitude affect. therefore, in this paper, we proposed a pitch detection using the spectrum flattening techniques. Spectrum flattening is to eliminate the formant and transition amplitude affect. In time domain, positive center clipping is process in order to emphasize pitch period with a glottal component of removed vocal tract characteristic. And rough formant envelope is computed through peak-fitting spectrum of original speech signal in frequency domain. As a results, well get the flattened harmonics waveform with the algebra difference between spectrum of original speech signal and smoothed formant envelope. After all, we obtain residual signal which is removed vocal tract element The performance was compared with LPC and Cepstrum, ACF 0wing to this algorithm, we have obtained the pitch information improved the accuracy of pitch detection and gross error rate is reduced in voice speech region and in transition region of changing the phoneme.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.526-533
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• 2009

This paper proposes a formant synthesis method of Haegeum sounds using cepstral envelope for spectral modeling. Spectral modeling synthesis (SMS) is a technique that models time-varying spectra as a combination of sinusoids (the "deterministic" part), and a time-varying filtered noise component (the "stochastic" part). SMS is appropriate for synthesizing sounds of string and wind instruments whose harmonics are evenly distributed over whole frequency band. Formants extracted from cepstral envelope are parameterized for synthesis of sinusoids. A resonator by Impulse Invariant Transform (IIT) is applied to synthesize sinusoids and the results are bandpass filtered to adjust magnitude. The noise is calculated by first generating the sinusoids with formant synthesis, subtracting them from the original sound, and then removing some harmonics remained. Linear interpolation is used to model noise. The synthesized sounds are made by summing sinusoids, which are shown to be similar to the original Haegeum sounds.

• Phonetics and Speech Sciences
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• v.7 no.2
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• pp.157-162
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• 2015

This study reports on the effective way of displaying dynamic formant information on F1-F2 space. Conventional ways of F1-F2 space (different name of vowel triangle or vowel rectangle) have been used for investigating vowel characteristics of a speaker or a language based on statistics of the F1 and F2 values, which were computed by spectral envelope search method. Those methods were dealing mainly with the static information of the formants, not the changes of the formant values (i.e. dynamic information). So a better way of investigating dynamic informations from the formant values of speech signal is suggested so that more convenient and detailed investigation of the dynamic changes can be achieved on F1-F2 space. Suggested method used visualization of static and dynamic information in overlapped way to be able to observe the change of the formant information easily. Finally some examples of the implemented display on some cases of the continuous vowels are shown to prove the usefulness of suggested method.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.15 no.2
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• pp.98-111
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• 2004

Background and Objectives : The purpose of this study is to analyze the difference of Fundamental Frequency(Hz), Closed Quotient(Qx ; %), Intensity(dB), Vocal tract length and width(cm), formant frequency(Hz), level of formant frequency(dB) depending on the larynx position. Materials and Methods : One professional male singer(career : 28 years) produced sustained vowel /a/,/e/,/i/,/o/,/u/ in two larynx position (higher, lower) with Dr. Speech and video fluoroscopy was used to quantify the vocal tract morphology. Results : In lower larynx position, CQ is increased 9.8% and Intensity is increased about 10% and level of Formant Frequency is increased. And also Vocal tract length is longer 2.4cm, Vocal tract width(Anterior width : 0.4cm, lateral width : 0.2cm) is wider than in higher larynx position. Conclusions : Singer's formant has a prominent spectrum envelope peak near 2400-2600Hz by clustering of F3, F4 and F5 near 3400Hz in lower larynx position.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.122-126
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• 2002

In this study, we find features of 3 emotions (Happiness, Angry, Surprise) as the fundamental research of emotion recognition. Speech signal with emotion has several elements. That is, voice quality, pitch, formant, speech speed, etc. Until now, most researchers have used the change of pitch or Short-time average power envelope or Mel based speech power coefficients. Of course, pitch is very efficient and informative feature. Thus we used it in this study. As pitch is very sensitive to a delicate emotion, it changes easily whenever a man is at different emotional state. Therefore, we can find the pitch is changed steeply or changed with gentle slope or not changed. And, this paper extracts formant features from speech signal with emotion. Each vowels show that each formant has similar position without big difference. Based on this fact, in the pleasure case, we extract features of laughter. And, with that, we separate laughing for easy work. Also, we find those far the angry and surprise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.12
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• pp.1324-1335
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• 1991

In this paper, a phoneme separation and an establishment of discriminative pattern of Korean phonemes are studied on experiment. The separation uses parameters such as pitch extraction, glottal peak pulse width of each pitch. speech duration. envelope and amplitude bias. The first pitch is extracted by deviations of glottal peak and width. energy and normalization on a bias on the top of vowel envelope. And then, it traces adjacent pitch to vowel in whole. On vewel, amethod to be reduced gliding pattern and the possible of vowel distinction to be used just second formant are proposed, and shrinking pitch waveform has nothing to do with pitch length is estimated. A pattern of envelope, spectrum, shrinking waveform, and a method of analysis by mutual relation among phonemes and manners of articulation on consonant are detected. As experimental results, 90% on vowel phoneme, 80% and 60% on initial and final consonant are discriminated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3A
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• pp.196-204
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• 2002

The Sinusoidal Transform Coding(STC) is a vocoding scheme based on a sinusoidal model of a speech signal. The low bit-rate speech coding based on sinusoidal model is a method that models and synthesizes speech with fundamental frequency and its harmonic elements, spectral envelope and phase in the frequency region. In this paper, we propose the 2.4kbps low-rate speech coding algorithm using the sinusoidal model of a speech signal. In the proposed coder, the pitch frequency is estimated by choosing the frequency that makes least mean squared error between synthetic speech with all spectrum peaks and speech synthesized with chosen frequency and its harmonics. The spectral envelope is estimated using SEEVOC(Spectral Envelope Estimation VOCoder) algorithm and the discrete all-pole model. The phase information is obtained using the time of pitch pulse occurrence, i.e., the onset time, as well as the phase of the vocal tract system. Experimental results show that the synthetic speech preserves both the formant and phase information of the original speech very well. The performance of the coder has been evaluated in terms of the MOS test based on informal listening tests, and it achieved over the MOS score of 3.1.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.196-203
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• 2000

On the assumption that the voices of the cows are produced by the linear prediction filter, we characterized the cows' voices. The order of this filter is determined by examining the voices characteristics both in time and frequency domains. The proposed order of the linear prediction filter is 15 for modeling voice production of the cow. The combination of the two parameters of the fundamental frequency, the slope of the straight line regressed from the log-log spectra of the amplitude-envelope and the only one coefficient involved in the linear prediction filter can differentiate the two cows.