• The Journal of the Acoustical Society of Korea
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• v.16 no.4
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• pp.106-109
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• 1997

In the area of the speech synthesis techniques, the waveform coding methods maintain the intelligibility and naturalness of synthetic speech. In order to apply the waveform coding techniques to synthesis by rule, however, we must be able to alter the pitches for prosody control of synthetic speech. In this paper, we propose a new pitch alteration technique in time-frequency hybrid domain, that compensates phase distortion of the cepstral pitch alteration method with time scaling method in the time domain. This method can remove some phase spectrum distortion which is occurred in conjunction point between the waveforms in continued frames. Also, we can obtain little magnitude spectrum distortion below 1.18% for pitch alteration of 200%.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1210-1216
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• 2014

This paper deals with an application of Teager Energy Operator (TEO) and Energy Separation Algorithm(ESA) to detect and determine various voltage waveform distortions like harmonics, inter-harmonics and frequency variation. Because the TEO and DESA algorithm was initially proposed for speech or communication analysis, its applications are limited to some types of waveform in the power quality analysis area. For example, an undistorted voltage signal is similar with a pure sinusoid. A voltage fluctuation is very similar with an amplitude-modulated signal, from the viewpoint of signal theory. And a continuous frequency variation is similar with a frequency-modulated signal, which is also known as a chirp signal. This paper is written to show that the TEO and DESA algorithm can be used for detecting occurrences of the representative waveform distortions and determining their instantaneous information of amplitude and frequency.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2439-2442
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• 2003

In this paper, we examine the acoustic characteristics of Korean vowels on pitch alteration utterance. The prosody is known as an indicator of acoustic characteristics of emotions. Also, speech is acoustically differenced according to the emotional variation and environmental variation, although speaker utters the same speech. We analyzed the spectral envelopes and formants from the voiced regions as data points on the speech waveform.

• ETRI Journal
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• v.38 no.3
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• pp.425-434
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• 2016

A novel average magnitude difference function (AMDF)-based pitch detection scheme (PDS) is proposed to achieve better performance in speech quality. A performance evaluation of the proposed PDS is carried out through both a simulation and a real-time implementation of a speech analysis-synthesis system. The parameters used to compare the performance of the proposed PDS with that of PDSs that are based on either a cepstrum, an autocorrelation function (ACF), an AMDF, or circular AMDF (CAMDF) methods are as follows: percentage gross pitch error (%GPE); a subjective listening test; an objective speech quality assessment; a speech intelligibility test; a synthesized speech waveform; computation time; and memory consumption. The proposed PDS results in lower %GPE and better synthesized speech quality and intelligibility for different speech signals as compared to the cepstrum-, ACF-, AMDF-, and CAMDF-based PDSs. The computational time of the proposed PDS is also less than that for the cepstrum-, ACF-, and CAMDF-based PDSs. Moreover, the total memory consumed by the proposed PDS is less than that for the ACF- and cepstrum-based PDSs.

• Phonetics and Speech Sciences
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• v.9 no.2
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• pp.9-22
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• 2017

The purpose of this paper is to report the whole process of developing Korean Standard Speech Database (KSS DB). This project is supported by SPO (Supreme Prosecutors' Office) research grant for three years from 2014 to 2016. KSS DB is designed to provide speech data for acoustic-phonetic and phonological studies and speaker recognition system. For the samples to represent the spoken Korean, sociolinguistic factors, such as region (9 regional dialects), age (5 age groups over 20) and gender (male and female) were considered. The goal of the project is to collect over 3,000 male and female speakers of nine regional dialects and five age groups employing direct and indirect methods. Speech samples of 3,191 speakers (2,829 speakers and 362 speakers using direct and indirect methods, respectively) are collected and databased. KSS DB designs to collect read and spontaneous speech samples from each speaker carrying out 5 speech tasks: three (pseudo-)spontaneous speech tasks (producing prolonged simple vowels, 28 blanked sentences and spontaneous talk) and two read speech tasks (reading 55 phonetically and phonologically rich sentences and reading three short passages). KSS DB includes a 16-bit, 44.1kHz speech waveform file and a orthographic file for each speech task.

• 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.

• 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.

• Journal of Digital Convergence
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• v.10 no.5
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• pp.233-238
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• 2012

In a speech coding system using excitation source of voiced and unvoiced, it would be a distortion of speech waveform in case of exist a voiced and an unvoiced consonants in a frame. To solve this problem, this paper present a method of LMS-MPC uses individual pitch and LMS(Least Mean Square). I evaluate the MPC and LMS-MPC using LMS. As a result, SNRseg of LMS-MPC was improved 1.5dB for female voice and 1.3dB for male voice respectively. Compared to the MPC, SNRseg of LMS-MPC has been improved that I was able to control the distortion of the speech waveform finally. And so, I expect to be able to this method for cellular phone and smart phone using excitation source of low bit rate.

• Speech Sciences
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• v.12 no.2
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• pp.81-88
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• 2005

Electrodermal activity(EDA) is a bio-electric signal which occurs at the skin surface during the sweating. EDA reflects the activity of the sympathetic axis of the autonomic nervous system. EDA is associated with the eccrine sweat gland at the palmar and plamar surface. This study was aimed to characterize the relationship between EDA and auditory stimulus intensities. Acoustic stimulus used in this study were 500 Hz, 1 kHz, 2 kHz of narrow band noise, which were representative of speech frequencies in audible range. Stimulus intensity between 90 and 30 dB in 10 dB within dynamic range. After deriving the minimum stimulus intensity(threshold of skin potential) which elicited skin potential, and then the latency and amplitude were derived from waveform of skin potential, each latency and amplitude were compared to stimulus intensity. The waveform of skin potential were recorded stably, and the threshold of skin potential appeared nearly the hearing threshold level of the participant. The latency was decreased and the amplitude was increased according to the increase of the stimulus intensity. These results suggest that auditory evoked skin potential can be applicable to auditory assessment and audiological diagnosis tool.

• Proceedings of the KSLP Conference
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• 1995.11a
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• pp.141-153
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• 1995

CSpeech is a software package that implements an audio waveform/speech analysis workstation on an IBM Personal Computer or hardware compatible computer. Features include digitizing audio waveforms on single or multiple channels, displaying the digitized waveforms, playing back audio waveforms from selected intervals of sing1e channels, saving and retrieving waveforms from binary format disk files, and analysing audio waveforms for their temporal and spectral properties. The distinguishing characteristics of CSpeech are its support for multiple channels, minimal restrictions on sample rate and waveform duration support fur a variety of hardware configurations, fast graphics display, and its user- extensible menu- based command structure.