• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1675-1682
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• 2017

This paper deals with three dimensional orientation estimation algorithm for an attitude and heading reference system (AHRS) based on nine-axis inertial/magnetic sensor signals. In terms of the orientation estimation based on the use of a Kalman filter (KF), the quaternion is arguably the most popular orientation representation. However, one critical drawback in the quaternion representation is that undesirable magnetic disturbances affect not only yaw estimation but also roll and pitch estimations. In this paper, a sequential direction cosine matrix-based orientation KF for AHRS has been presented. The proposed algorithm uses two linear KFs, consisting of an attitude KF followed by a heading KF. In the latter, the direction of the local magnetic field vector is projected onto the heading axis of the inertial frame by considering the dip angle, which can be determined after the attitude KF. Owing to the sequential KF structure, the effects of even extreme magnetic disturbances are limited to the roll and pitch estimations, without any additional decoupling process. This overcomes an inherent issue in quaternion-based estimation algorithms. Validation test results show that the proposed method outperforms other comparison methods in terms of the yaw estimation accuracy during perturbations and in terms of the recovery speed.

• Speech Sciences
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• v.7 no.4
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• pp.3-10
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• 2000

This paper presents a time-based Pitch Determination Algorithm (PDA) for the reliable estimation of Pitch Period (PP) in speech signals. Based on the Dyadic Wavelet Transform (DyWT) , the proposed PDA detects the presence of Glottal Closure Instants (GCI) and uses the information to determine the pitch period. We also examine the problem of conventional PDAs based on DyWT; their performance is compared with the proposition of this paper. The effectiveness of the proposed method is tested with real speech signals containing a transition between the voiced and the unvoiced interval where the energy of the voiced signal is unsteady. The result shows that the proposed method provides good performance in estimating both the unsteady GCI positions as well as the steady parts.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.197-200
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• 2000

This paper presents a time-based Pitch Determination Algorithm (PDA) for reliable estimation of pitch Period (PP) in speech signal. In proposed method, we use the Dyadic Wavelet Transform (DyWT), which detects the presence of Glottal Closure Instants (GCI) and uses the information to determine the pitch period. And, the proposed method also uses the periodicity property of DyWT to detect unsteady GCI. To evaluate the performance of the proposed methods, that of other PDAs based on DyWT are compared with what this paper proposed. The effectiveness of the proposed method is tested with real speech signals containing a transition between voiced and the unvoiced interval where the energy of voiced signal is unsteady. The result shows that the proposed method provides a good performance in estimating the both the unsteady GCI positions as well as the steady parts.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.247-256
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• 2021

In this paper, we propose a packet loss concealment (PLC) algorithm using pitch harmonic motion prediction and adaptive signal amplitude prediction and. The spectral motion prediction method divides the spectral motion of the previous usable frame into predetermined sub-bands to predict and restore the motion of the lost signal. In the proposed algorithm, the speech signal is classified into voiced and unvoiced sounds. In the case of voiced sounds, it is further divided into pitch harmonics using the pitch frequency to predict and restore the pitch harmonic motion of the lost frame, and for the unvoiced sound, the lost frame is restored using the spectral motion prediction method. When the continuous loss of speech frames occurs, a method of adjusting the gain using the least mean square (LMS) predictor is proposed. The performance of the proposed algorithm was evaluated through the objective evaluation method, PESQ (Perceptual Evaluation of Speech Quality) and was showed MOS 0.1 improvement over the conventional method.

• Journal of IKEEE
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• v.27 no.4
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• pp.472-476
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• 2023

Fundamental frequency/pitch period are major characteristics of speech signals. They are used in many speech applications like speech coding, speech recognition, speaker identification, and so on. In this paper, some of inflection points are used to estimate the pitch which is the inverse of the fundamental frequency. The inflection points are defined as points where local maxima, local minima or the slope changes occur. The speech signal is preprocessed to remove unnecessary inflection points due to the high frequency components using a low pass filter. Only the inflection points from local maxima are used to get the pitch period. While the existing pitch estimation methods process speech signals in blockwise, the proposed method detects the inflection points in sample and produces the pitch period/fundamental frequency estimates along the time. Computer simulation shows the usefulness of the proposed method as a fundamental frequency estimator.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.42-46
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• 2012

A simple and accurate depth estimation algorithm for an IBVS (Image-Based Visual Servoing) is presented. Specifically, this algorithm is useful for under-actuated systems such as visual-guided quadrotor UAVs (Unmanned Aerial Vehicles). Since the image of a marker changes with changing pitch and roll angles of quadrotor, it is difficult to estimate depth. The proposed algorithm compensates a shape of the marker, so that the system acquire more accurate depth information without complicated processes. Also, the roll and pitch channels are decoupled so that the IBVS algorithm can be used in an under-actuated quadrotor system.

• Phonetics and Speech Sciences
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• v.11 no.4
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• pp.9-18
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• 2019

This study aimed to investigate the correlation between speaker's chronological age (CA) and perceived age (PA) and to specify the effect of pitch and speech rate as acoustic cue on judging age, using perceptual testing and acoustic analysis. Three tasks were conducted to identify the degree of listener's accuracy about age estimation. Three perception tasks were conducted to measure the accuracy of 80 Korean listeners when presented with different types of speech. In all the tasks, participants listened to speech samples and gave their estimate of the speaker's age in figures. It was found that Korean listeners are able to gauge the age of a speaker fairly precisely. CA and mean PA were positively correlated in all three tasks. It is clear that the amount and type of information included in the voice samples affected the accuracy of a listener's judgement. Moreover, the result revealed that listeners make use of acoustic information such as pitch and speech rate to estimate speaker's age.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1040-1048
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• 2013

In this paper, a sensorless pitch angle control method for a wind generation system is suggested. One-step-ahead prediction control law is adopted to control the pitch angle of a wind turbine in order for electric output power to track target values. And it is shown that this control scheme using the inverse dynamics of the controlled system enables us to predict current wind speed without an anemometer, to a considerable precision. The inverse input-output of the controlled system is realized by use of an artificial neural network. The proposed control and wind speed prediction method is applied to a Double-Feed Induction Generation system connected to a simple power system through computer simulation to show its effectiveness. The simulation results demonstrate that the suggested method shows better control performances with less control efforts than a conventional Proportional-Integral controller.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.149-153
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• 1995

In this paper, wavelet transform with multi-resolution property is used to improve the accuracy of pitch estimation of speech signal. Pitch detection of speech signal is based on the local maxima by using wavelet transform. The wavelet transform of a signal is a multiscale decomposition that is well localized in space and frequency. The proposed pitch defection algorithm is suitable for both low-pitched and high-pitched speakers.

• Speech Sciences
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• v.5 no.1
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• pp.23-33
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• 1999

Mallat has shown that, with a proper choice of wavelet function, the local maxima of wavelet transformed signal indicate a sharp variation in the signal. Since the glottal closure causes sharp discontinuities in the speech signal, dyadic wavelet transform can be useful for detecting abrupt change in the voiced sounds, i.e., epochs. In this paper, we investigate the glottal closure instants obtained from the wavelet analysis of speech signal and compare them with those obtained from the EGG signal. Then, we detect pitch period of speech signal on the basis of these results. Experimental results demonstrated that local maxima of wavelet transformed signal give accurate estimation of epoch and pitch periods of voiced sound obtained by the proposed algorithm also correspond to those from EGG well.