Earticle

복층이 있는 공간의 음향 특성을 계산식, 시뮬레이션 및 실측을 통해 비교해 보았다. 언더발코니 스피커의 바로 뒤 지역은 메인스피 커와 딜레이 차이가 생기며, 중/저음 부분에서 충분한 음압저하가 이뤄지지 않아 컴필터링(Comb-Filtering) 현상이 크게 발생하게 된다. 또한 언더발코니 스피커의 바로 하부 지역은 스피커와 거리가 2～3m 내외로 언더발코니 스피커의 음압이 메인 스피커보다 커져 강대상과 음상일치가 깨지게 된다. 언더발코니 스피커에서 5～6m 이상 벗어나는 지역은 음의 역자승법칙에 따라 언더발코니 스피커 하부 지역보다 10dB이상 차이가 발생하며, 메인스피커에서도 중/고역 주파수(Mid/High Frequency) 음이 유입되지 않아 주 파수별 음압 편차가 크게 발생하여 집중도가 떨어지게 된다. 이러한 음향 문제를 최소화하기 위해서 메인스피커의 위치 및 출력에 따른 언더발코니 스피커의 적절한 배치와 출력이 요청된다. 발코니 하부 지역을 더 쾌적한 음향 환경으로 개선하기 위해서는 언더발 코니 스피커에 대한 적절한 음향설계 방향이 제시되어야 한다.

Formula acoustic characteristics of the room with a double layer , are compared through simulation and actual measurement. The rear area of the under- balcony speakers will cause a delay difference between the main speaker. In the mid / bass parts do not generate sufficient pressure is lowered and comb-Filtering phenomenon occurs significantly. The lower right area of the under- balcony speakers and speaker distance is the sound pressure of the under- balcony speakers to around 2 ~ 3m bigger than the main speakers and the sound image matches the pulpit is broken. Also, under area is more than 5 ~ 6m from the balcony outside speakers and causes differ by more than 10dB lower than the under- balcony speakers depending on the local laws of Translator wins Well, the main speaker at mid / high frequency sounds do not enter the sound pressure variations will drop by a significant. Appropriate arrangement and the output of the speaker according to the position under the balcony , and output of the main speakers are requested to minimize this problem sound . The proper sound design direction for the under- balcony speakers must be presented in order to improve the lower balcony area more pleasant acoustic environment.

This paper proposes a simple sound source localization (SSL) method based on signal energies comparison and partial cross correlation for TDOA computation. Many sound source localization methods include multiple TDOA computations in order to eliminate front-back confusion. Multiple TDOA computations however increase the methods’ computation times which need to be as minimal as possible for real-time applications. Our aim in this paper is to achieve the same results of localization using fewer computations. Using three microphones, we first compare signal energies to predict which quadrant the sound source is in, and then we use partial cross correlation to estimate the TDOA value before computing the azimuth value. Also, we apply a threshold value to reinforce our prediction method. Our experimental results show that the proposed method has less computation time; spending approximately 30% less time than previous three microphone methods.

This paper proposes a fast sound source localization method using a TDOA sign–based algorithm. We present an L-shaped microphone set-up which creates four major regions in the range of 0°~360° by the intersection of the positive and negative regions of the individual microphone pairs. Then, we make an initial source region prediction based on the signs of two TDOA estimates before computing the azimuth value. Also, we apply a threshold and angle comparison to tackle the existing front-back confusion problem. Our experimental results show that the proposed method is comparable in accuracy to previous three microphone array methods; however, it takes a shorter computation time because we compute only two TDOA values.

This paper presents a fast Time Difference of Arrival (TDOA) estimation for sound source localization. TDOA is the time difference between the arrival times of a signal at two sensors. We propose a partial cross correlation method to increase the speed of TDOA estimation for sound source localization. We do this by predicting which part of the cross correlation function contains the required TDOA value with the help of the signal energies, and then we compute the cross correlation function in that direction only. Experiments show approximately 50% reduction in the cross correlation computation time thereby increasing the speed of TDOA computation. This makes it very relevant for real world surveillance.

These days, the researches related with the emotional robots are actively investigated and in progress. And human language, expression, action etc. are merged in the emotional robot to understand the human emotion. However, there are so many sound sources and background noise around the robot, that the robots should be able to separate the mixture of these sound sources into the original sound sources, moreover to understand the meaning of voice of a specific person. Also they should be able to turn or move to the direction of a specific person to observe his expression or action effectively. Until now, the researches on the localization and separation of sound sources have been so theoretical and computative that real-time processing is hardly possible. In this reason for the practical emotional robot, fast computation should be realized by using simple principle. In this paper the methods for detecting the direction of sound sources by using the phase difference between peaks on spectrums, and the separating the sound sources by using fundamental frequency and its overtones of human voice, are proposed. Also by using these methods, it is shown that the effective and real-time localization and separation of sound sources in living room are possible.

Recent development in multi-channel surround is emerging in various formats to provide better stereoscopic and sound effects to consumers in recent broadcasting. The ability sound localize the sound sources in space is most considerable design factor on multi-channel surround system for human earing perception model. However, this paper propose the change of the sound localization according to the spacing of the speakers, which is not covered in the existing research focus on sound system design. Presently the sound system uses the position and number of the speakers to localize the sound. In the multi-channel surround environment, the proposed design uses the sound localization is caused by the directional characteristics of the speaker, the distance between the speakers and the distance between the listener and the speaker according to the directivity is required. The proposed design is simulated using virtual measurement with MATLAB simulation environment and performances are measured.

Acoustic Emission (AE) source localization is a useful implement to diagnose the incipient faults in rotating machine. This paper proposes an improved Near-field Multiple Signal Classification method using four-order cumulants (NFC-MUSIC) to accurately locate the faults position. In order to overcome dispersion effect and revised velocity, the feature sub narrow band is extracted by Wavelet Packet reconstitution (WPR) and Modal Plate Wave Theory (MPWT). For multi-source decorrelation and increasing localized resolution, the four-order cumulants of observed signal can be selected for localization. The experiment results indicate that the improved method can accurately locate multi-rubbing faults. It is an efficient way to assist incipient rubbing faults diagnosis.

Sound Source Localization (SSL) has a wide application in speech separation, recognition and enhancement. Binaural sound source localization based on human spatial hearing mechanism is an important research field of SSL. The recent binaural SSL research is focused on the system robust against noise and reverberation. In order to improve the localization performance in degraded environment, this paper proposes an algorithm to adaptively select the ‘good’ sub-bands to compute the binaural localization cues. Firstly, sub-band Signal-Noise Ratio (SNR) is estimated based on the auto-correlation matrix of binaural sound signals. Then, Inter-aural Time Difference (ITD) is computed by adaptively selecting the sub-bands which have the high SNR. Since the ITD is calculated through the sub-bands which are less affected by the noise, the sound source azimuth is estimated more accurate. The simulation results show that compared to the conventional binaural SSL algorithm, the localization accuracy of the proposed algorithm has been improved significantly.

A sound source localization method is presented herein around the utilization with the sound signal for device fault diagnosis. Firstly, Butterworth wavelet and its filter banks were designed aimed at the background noise separation in the industrial environment, it is proved that the Butterworth wavelet filter can extract the weak fault features in source signals without frequency aliasing phenomenon. Then the algorithms of sound source localization was studied in depth, the generalized cross-correlation(GCC) based time delay estimation(TDE) was presented. Finally the coordinates of sound source location was obtained in the quaternion microphone array model. The experiment results show that in the industrial environment, the error value of positioning accuracy is less than 4cm within an appropriate distance, it can meet the needs of practical application, meanwhile the reliability and the real-time performance is satisfactory.

In this paper, we supposed teller following algorithm that using sound localization for developing dialog type humanoid robot. A sound localization is studied for develop the techniques of an efficient 3-D sound system based on the psychoacoustics of spatial hearing with multimedia or virtual reality. When a robot talk with human, it is necessary that robot follow human for improved human interface and adaptive noise canceling. We apply this algorithm to robot system.

본 연구는 현재 그 수요가 점점 증대되고 있는 음악의 3D Audio 제작을 하기 위한 청음훈련의 필요성에 대한 것이다. 음악의 스테레오나 서라운드는 물론 3D Audio 제작을 위해서는 먼저 듣는 능력과 소양이 갖춰져야 하는데 문제는 음악과 사운드에 대한 개인의 청취 성향과 특성이 다양하고 주관성이 강한 경향이 있기 때문에 제작에 있어서의 음악적,음향적 기준점이 필요함과 동시에 청취에 대한 객관적 능력향상이 요구 된다고 할 수 있다. 더구나 지금 까지 접하지 못한 3D사운드(Immersive sound)는 제작하는 사람 입장에서도 기존의 오디오 포맷에서 듣지 못한 방향에서 들려오는 소리에 대한 해석이나 의미부여가 쉽지 않은 상황이다. 이러한 상황에서 스피커를 통한 3차원적인 소리를 듣고 판별한다는 것은 쉬운 일이 아니다. 이번 연구에서 음악전공자(작곡,연주)와 사운드 엔지니어를 대상으로 3D Audio 포맷(Immersive sound)으로 믹싱된 오케스트라 음악을 3D 스피커 시스템으로 재생하여 들려주고 리스닝 테스트를 하여 그들이 3D 사운드를 듣는 특성과 선호도에 대해 파악하였다. 반원구 형태의 모든 곳에서 소리가 나오는 것에 대한 테스트이며 물리적으로 어떻게 들리는지 알아보았다. 설문 테스트 결과 음악전공자와 사운드엔지니어 간에 3D 사운드 특성에 대한 인지 능력이 다르거나 부족한 부분이 있는 것을 알 수 있었고 이를 통해 3D 사운드에서 소리방향의 인지를 위한 청음훈련이 필요하다는 결론을 낼 수 있었다.

This study is about the need for listening training to produce 3D audio of music, which is currently in increasing demand. In addition to stereo and surroundings of music, 3D audio production requires listening skills and knowledge, but the problem is that individuals have diverse tendency about listening music and music sound . Moreover, the 3D sound that has not been encountered so far is not easy for the producer to interpret or give meaning to the sound from the direction not heard in the existing audio format. Under these circumstances, it is not easy to hear and discriminate three-dimensional sounds through speakers. In this study, music majors (composition, performance) and sound engineers were asked to listen to 3D audio-formatted orchestra music with a 3D speaker system and listen test to understand the characteristics and preferences of listening to 3D sound. It is a test of sound coming from everywhere in the semi-circular form and we looked at how it sounds physically. Tests showed that there was a difference or lack of cognitive skills in 3D sound between music majors and sound engineers, which led to the conclusion that listening training for 3D sound was necessary.

This paper suggests an algorithm that can estimate the direction of the sound source in realtime. Our intelligent service robot, WEVER, is used to implement the proposed method at the home environment. The algorithm uses the time difference and sound intensity information among the recorded sound source by four microphones. Also, to deal with noise of robot itself, the kalman filter is implemented. The proposed method takes shorter execution time than that of an existing algorithm to fit the real-time service robot. The result shows relatively small error within the range of ${\pm}$ 7 degree.

Purpose: Sound is localized by two ears. People with bilaterally severe-to-profound hearing loss may struggle to identify the direction of a sound if their hearing device delivers sound only one ear due to the loss of binaural advantage. The purpose of this study was to systematically investigate the sound localization performance of people with unilateral cochlear implant users. Methods: Ten unilateral cochlear implant users and 10 normal hearing adults participated in this study. Sound localization tests were conducted using five stimuli (speech, speech with noise, 500 Hz warble tone, 1 kHz warble tone, and 4 kHz warble tone) presented from eight loud-speakers. Correct responses and rootmean- square errors were obtained to investigate the localization performances and error patterns. Additional factors including the Korean-Speech Spatial and Qualities of Hearing Questionnaire were also analyzed. Results: Localization performance was significantly poor in the unilateral cochlear implant group showing polar patterns toward their hearing side. While the normal hearing group showed better localization for speech in quiet conditions compared to 500 Hz warble tone, the cochlear implant group did not show any statistical difference in performance across the stimuli due to their very poor performance. The Korean-Speech Spatial and Qualities of Hearing Questionnaire was associated with localization performance in limited conditions. Conclusion: The present study revealed that unilateral cochlear implant users correctly localize a sound at nearly chance levels. The Korean-Speech Spatial and Qualities of Hearing Questionnaire predict localization performance for unilateral cochlear implant users only for particular conditions.

Purpose: The present study examined sound localization in terms of varying hearing threshold levels as well as age and sex. Methods: Fifteen healthy volunteers participated with varying mean pure tone averages (mean PTA). Using speaker systems evenly separated by 15˚ from 0˚ to 75˚ to the left and right sides (11 speakers), sound localization error was calculated. Correlation was computed between localization error and various methods of averaging PTA. Three averages were compared: full test frequency range averaging, 6 frequency weighted average used for diagnosing hearing loss and 6 frequency average for Enforcement Decree of Industrial Accident Compensation Insurance Act. Results: First of all, sound localization error positively correlated with age and hearing threshold. The positive correlation was preserved with three averaging methods, with strongest significance with the full range averaging. Conclusion: The present results imply that various averaging methods equally provide significant correlation by the function of localization error.

Heart sounds are the main obstacle in lung sound analysis. To tackle this obstacle, we propose a diagnosis algorithm that uses singular spectrum analysis (SSA) and frequency features of heart and lung sounds. In particular, we introduce a frequency coefficient that shows the frequency difference between heart and lung sounds. The proposed algorithm is applied to a synthetic mixture of heart and lung sounds. The results show that heart sounds can be extracted successfully and localizations for the first and second heart sounds are remarkably performed. An error analysis of the localization results shows that the proposed algorithm has fewer errors compared to the SSA method, which is one of the most powerful methods in the localization of heart sounds. The presented algorithm is also applied in the cases of recorded respiratory sounds from the chest walls of five healthy subjects. The efficiency of the algorithm in extracting heart sounds from the recorded breathing sounds is verified with power spectral density evaluations and listening. Most studies have used only normal respiratory sounds, whereas we additionally use abnormal breathing sounds to validate the strength of our achievements.

In this paper, we present the design and implementation of real-time sound localization based on $0.13{\mu}m$ CMOS process. Time delay of arrival (TDOA) estimation was used to obtain the direction of the sound signal. The sound localization chip consists of four modules: data buffering, short-term energy calculation, cross correlation, and azimuth calculation. Our chip achieved real-time processing speed with full range ($360^{\circ}$) using three microphones. Additionally, we developed a dedicated sound localization circuit (DSLC) system for measuring the accuracy of the sound localization chip. The DSLC system revealed that our chip gave reasonably accurate results in an experiment that was carried out in a noisy and reverberant environment. In addition, the performance of our chip was compared with those of other chip designs.

This paper describes real time implementation of subband sound localization system on a floating-point DSP TI TMS320C31. The system determines two dimensional location of an active speaker in a closed room environment with real noise presents. The system consists of an two microphone array connected to TI DSP hosted by PC. The implemented sound localization algorithm is Subband CPSP which is an improved version of traditional CPSP (Cross-Power Spectrum Phase) method. The algorithm first split the input speech signal into arbitrary number of subband using subband filter banks and calculate the CPSP in each subband. It then averages out the CPSP results on each subband and compute a source location estimate. The proposed algorithm has an advantage over CPSP such that it minimize the overall estimation error in source location by limiting the specific band dominant noise to that subband. As a result, it makes possible to set up a robust real time sound localization system. For real time simulation, the input speech is captured using two microphone and digitized by the DSP at sampling rate 8192 hz, 16 bit/sample. The source location is then estimated at once per second to satisfy real-time computational constraints. The performance of the proposed system is confirmed by several real time simulation of the speech at a distance of 1m, 2m, 3m with various speech source locations and it shows over 5% accuracy improvement for the source location estimation.

This paper reviews several multi-source localization methods which estimate ITDs based on zero crossings (ZCs). Employing signal-to-noise ratio (SNR) estimation from ITD variances, these ZC-based source localization methods are more robust to diffuse noise than the cross-correlation (CC)-based one with less computational complexity. In order to take reverberant environments into account, two approaches detect intervals which dominantly contain direct-path components from sources to sensors because they may effectively provide reliable ITDDs corresponding to source directions. One accomplishes the detection by comparing the original and cepstral-prefiltering-processed envelopes, and the other searches sudden increase of acoustic energy by considering typical characteristics of acoustic reverberation. Experiments for comparison of these methods demonstrate that the approach with energy-based detection efficiently achieves multi-source localization in reverberant environments.

The problem of sound source localization is to determine the position of sound sources using the measurement of the acoustic signals received by microphones. To develop a good sound source localization system which is applicable to a mobile platform such as robots, a time delay estimator with low computational complexity and robustness to background noise or reverberations is necessary. In this paper, an explicit adaptive time delay estimation method for a sound source localization system is proposed. Proposed explicit adaptive time estimation algorithm employs direct adaptation of the delay parameter using a transform-based optimization technique, rather than...