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A study on user defined spoken wake-up word recognition system using deep neural network-hidden Markov model hybrid model 基于深度神经网络隐马尔可夫模型混合模型的用户定义语音唤醒词识别系统研究
IF 0.4 Q4 ACOUSTICS Pub Date : 2020-03-01 DOI: 10.7776/ASK.2020.39.2.131
Ki-mu Yoon and Wooil Kim
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引用次数: 0
Speaker verification system combining attention-long short term memory based speaker embedding and I-vector in far-field and noisy environments 基于注意-长短时记忆的说话人嵌入与i向量相结合的远场噪声环境下的说话人验证系统
IF 0.4 Q4 ACOUSTICS Pub Date : 2020-03-01 DOI: 10.7776/ASK.2020.39.2.137
Ara Bae, Wooil Kim
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引用次数: 0
A study on the waveform-based end-to-end deep convolutional neural network for weakly supervised sound event detection 基于波形的端到端深度卷积神经网络弱监督声事件检测研究
IF 0.4 Q4 ACOUSTICS Pub Date : 2020-01-01 DOI: 10.7776/ASK.2020.39.1.024
Seokjin Lee, Minhan Kim, Youngho Jeong
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引用次数: 1
Changes in binaural beat strength to the difference of right and left hearing ability 双耳搏动强度随左右听力差异的变化
IF 0.4 Q4 ACOUSTICS Pub Date : 2020-01-01 DOI: 10.7776/ASK.2020.39.1.057
S. Kim
: The binaural beat is a subjective beating phenomenon due to the frequency difference of sounds heard in both ears, sensed by the human brain. The beating magnitude physically depends on the amplitudes of the two signals with slight different frequencies. Therefore, the binaural beat strength is expected to be affected by the difference in left and right hearing ability. In this study, 34 healthy subjects without hearing loss were chosen. They hear a pure tone sound (450 Hz) at 10 different Sound Pressure Levels (SPLs) (from 50 dB to 27.4 dB) through the one side of ears, while they hear the reference sound (440 Hz, 50 dB) through the other side of ears. Their subjective assessment using a semantic differential method reveals that the binaural beat strength decreases as SPL differences between the two sides of ears increases, if the difference is greater than 2.2 dB. The result suggests that the hearing loss difference between the two sides of ears should be less than 2.2 dB to maximize binaural
双耳节拍是一种主观的跳动现象,这是由于两只耳朵听到的声音的频率不同而被大脑感知到的。跳动幅度在物理上取决于两个频率略有不同的信号的幅度。因此,双耳节拍强度预计会受到左右听力能力差异的影响。本研究选择34名无听力损失的健康受试者。他们通过一侧耳朵听到10个不同声压级(从50分贝到27.4分贝)的纯音(450赫兹),而通过另一侧耳朵听到参考声音(440赫兹,50分贝)。他们使用语义差分方法进行主观评估,发现当双耳声压级差异大于2.2 dB时,双耳节拍强度随着双耳声压级差异的增大而减小。结果表明,双耳听力损失差应小于2.2 dB,以最大限度地提高双耳跳动效果。
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引用次数: 0
High-intensity focused ultrasound beam path visualization using ultrasound imaging 利用超声成像技术可视化高强度聚焦超声波束路径
IF 0.4 Q4 ACOUSTICS Pub Date : 2020-01-01 DOI: 10.7776/ASK.2020.39.1.016
J. Song, J. Chang, Y. Yoo
In High-Intensity Focused Ultrasound (HIFU) treatment, effective localization of HIFU focus is important for developing a safe treatment plan. While Magnetic Resonance Imaging guided HIFU (MRIgHIFU) can visualize the ultrasound path during the treatment for localizing HIFU focus, it is challenging in ultrasound imaging guided HIFU (USIgHIFU). In the present study, a real-time ultrasound beam visualization technique capable of localizing HIFU focus is presented for USIgHIFU. In the proposed method, a short pulse, with the same center frequency of an imaging ultrasound transducer below the regulated acoustic intensity (i.e., Ispta < 720 mW/cm(2)), was transmitted through a HIFU transducer whereupon backscattered signals were received by the imaging transducer. To visualize the HIFU beam path, the backscattered signals underwent dynamic receive focusing and subsequent echo processing. From in vitro experiments with bovine serum albumin gel phantoms, the HIFU beam path was clearly depicted with low acoustic intensity (i.e., Ispta of 94.8 mW/cm(2)) and the HIFU focus was successfully localized before any damages were produced. This result indicates that the proposed ultrasound beam path visualization method can be used for localizing the HIFU focus in real time while minimizing unwanted tissue damage in USIgHIFU treatment.
在高强度聚焦超声(HIFU)治疗中,HIFU病灶的有效定位对于制定安全的治疗方案至关重要。虽然磁共振成像引导下的HIFU (MRIgHIFU)可以在治疗过程中可视化超声路径以定位HIFU病灶,但超声成像引导下的HIFU (USIgHIFU)具有挑战性。在本研究中,提出了一种用于USIgHIFU的能够定位HIFU焦点的实时超声束可视化技术。在所提出的方法中,通过HIFU换能器传输具有与成像超声换能器相同中心频率的短脉冲,该脉冲低于调节声强(即Ispta < 720 mW/cm(2))),然后成像换能器接收背散射信号。为了可视化HIFU波束路径,后向散射信号进行了动态接收聚焦和随后的回波处理。通过牛血清白蛋白凝胶模型的体外实验,可以清楚地描绘出低声强(即Ispta为94.8 mW/cm(2))下的HIFU光束路径,并且在产生任何损伤之前成功定位了HIFU焦点。该结果表明,所提出的超声波束路径可视化方法可以用于实时定位HIFU焦点,同时最大限度地减少USIgHIFU治疗中不必要的组织损伤。
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引用次数: 1
Comparison of the sound source localization methods appropriate for a compact microphone array 适用于紧凑型麦克风阵列的声源定位方法的比较
IF 0.4 Q4 ACOUSTICS Pub Date : 2020-01-01 DOI: 10.7776/ASK.2020.39.1.047
In-Jee Jung, J. Ih
: The sound source localization technique has various application fields in the era of internet-of-things, for which the probe size becomes critical. The localization methods using the acoustic intensity vector has an advantage of downsizing the layout of the array owing to a small finite-difference error for the short distance between adjacent microphones. In this paper, the acoustic intensity vector and the Time Difference of Arrival (TDoA) method are compared in the viewpoint of the localization error in the far-field. The comparison is made according to the change of spacing between adjacent microphones of the three-dimensional microphone array arranged in a tetrahedral shape. An additional test is conducted in the reverberant field by varying the reverberation time to verify the effectiveness of the methods applied to the actual environments. For estimating the TDoA, the Generalized Cross Correlation-Phase transform (GCC-PHAT) algorithm is adopted in the computation. It is found that the mean localization error of the acoustic intensimetry is 2.9° and that of the GCC-PHAT is 7.3° for T 60 = 0.4 s, while the error increases as 9.9°, 13.0° for T 60 = 1.0 s, respectively. The data supports that a compact array employing the acoustic intensimetry can localize of the sound source in the actual environment with the moderate reflection conditions.
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引用次数: 1
Numerical investigation of blade tip vortex cavitation noise using Reynolds-averaged Navier-Stokes simulation and bubble dynamics model 基于reynolds -average Navier-Stokes模拟和气泡动力学模型的叶片尖涡空化噪声数值研究
IF 0.4 Q4 ACOUSTICS Pub Date : 2020-01-01 DOI: 10.7776/ASK.2020.39.2.077
Ga-ram Ku, C. Cheong, Hanshin Seol
In this study, the Eulerian/Lagrangian one-way coupling method is proposed to predict flow noise due to Blade-Tip Vortex Cavitation (BTVC). The proposed method consists of four sequential steps: flow field simulation using Computational Fluid Dynamics (CFD) techniques, reconstruction of wing-tip vortex using vortex model, generation of BTVC using bubble dynamics model and acoustic wave prediction using the acoustic analogy. Because the CFD prediction of tip vortex structure generally suffers from severe under-prediction of its strength along the steamwise direction due to the intrinsic numerical damping of CFD schemes and excessive turbulence intensity, the wing-tip vortex along the freestream direction is regenerated by using the vortex modeling. Then, the bubble dynamics model based on the Rayleigh-Plesset equation was employed to simulate the generation and variation of BTVC. Finally, the flow noise due to BTVC is predicted by modeling each of spherical bubbles as a monople source whose strength is proportional to the rate of time-variation of bubble volume. The validity of the proposed numerical methods is confirmed by comparing the predicted results with the measured data.
本文提出了欧拉/拉格朗日单向耦合方法来预测叶尖涡空化(BTVC)引起的流动噪声。该方法由四个步骤组成:利用计算流体动力学技术进行流场模拟,利用涡模型重建翼尖涡,利用气泡动力学模型生成BTVC,利用声学类比进行声波预测。由于CFD方案固有的数值阻尼和湍流强度过大,导致翼尖涡结构的CFD预测在沿蒸汽方向上存在严重的强度低估问题,因此利用涡模型再生了沿自由流方向的翼尖涡。然后,采用基于Rayleigh-Plesset方程的气泡动力学模型,模拟了BTVC的产生和变化。最后,将每个球形气泡建模为单个源,其强度与气泡体积的时变速率成正比,从而预测了由BTVC引起的流动噪声。通过将预测结果与实测数据进行比较,验证了所提数值方法的有效性。
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引用次数: 1
An effective method to reduce the contraction and expansion noise of air conditioner 一种降低空调缩胀噪声的有效方法
IF 0.4 Q4 ACOUSTICS Pub Date : 2020-01-01 DOI: 10.7776/ASK.2020.39.2.098
Kangtae Kim, Won-Jin Kim
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引用次数: 0
Acoustic insertion loss by a bubble layer for the application to air bubble curtain and air masker 一种用于气泡幕和空气掩蔽器的气泡层的声插入损耗
IF 0.4 Q4 ACOUSTICS Pub Date : 2020-01-01 DOI: 10.7776/ASK.2020.39.4.227
Cheol-Soo Park, S. Jeong, Gun-Do Kim, I. Moon, G. Yim
This paper derives the insertion loss for the bubble layer of an air bubble curtain and an air masker which are used to reduce ocean anthropogenic noise such as the piling noise and the ship noise. The air bubble curtain is considered as a ‘fluid-air bubble layer-fluid’ model and the environment for the air masker is simplified as an ‘vacuum-thin plate-fluid-air bubble layer-fluid’ model. The air bubble layer in each model is assumed as the effective medium which has the complex wavenumber and the complex impedance corresponding to the bubble population distribution. The numerical simulations are performed to examine the insertion loss depending on the bubble population, the void fraction, and the thickness of the layer.
本文推导了用于降低海洋人为噪声(如桩噪声和船舶噪声)的气泡幕和空气罩的气泡层的插入损耗。将气泡幕视为“流体-气泡层-流体”模型,将空气罩的环境简化为“真空-薄板-流体-气泡层-流体”模型。假设各模型中的气泡层为有效介质,具有复波数和复阻抗,与气泡种群分布相对应。数值模拟研究了气泡填充、空隙率和层厚对插入损失的影响。
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引用次数: 2
LOFAR/DEMON grams compression method for passive sonars 无源声纳LOFAR/DEMON图压缩方法
IF 0.4 Q4 ACOUSTICS Pub Date : 2020-01-01 DOI: 10.7776/ASK.2020.39.1.038
J. Ahn, Hyeon‑Deok Cho, Donghoon Shin, Taek-ik Kwon, Gwangtae Kim
LOw Frequency Analysis Recording (LOFAR) and Demodulation of Envelop Modulation On Noise (DEMON) grams are bearing-time-frequency plots of underwater acoustic signals, to visualize features for passive sonar. Those grams are characterized by tonal components, for which conventional data coding methods are not suitable. In this work, a novel LOFAR/DEMON gram compression algorithm based on binary map and prediction methods is proposed. We first generate a binary map, from which prediction for each frequency bin is determined, and then divide a frame into several macro blocks. For each macro block, we apply intra and inter prediction modes and compute residuals. Then, we perform the prediction of available bins in the binary map and quantize residuals for entropy coding. By transmitting the binary map and prediction modes, the decoder can reconstructs grams using the same process. Simulation results show that the proposed algorithm provides significantly better compression performance on LOFAR and DEMON grams than conventional data coding methods.
低频分析记录(LOFAR)和噪声包络调制解调(DEMON)图是水声信号的承载时频图,用于可视化被动声呐的特征。这些克具有音调成分的特征,传统的数据编码方法不适合这种特征。本文提出了一种基于二值映射和预测方法的LOFAR/DEMON图像压缩算法。我们首先生成一个二值映射,从中确定每个频率bin的预测,然后将帧划分为几个宏块。对于每个宏块,我们采用内部和内部预测模式并计算残差。然后,我们对二值映射中的可用bin进行预测,并对残差进行量化以进行熵编码。通过传输二进制映射和预测模式,解码器可以使用相同的过程重建图。仿真结果表明,该算法对LOFAR图和DEMON图的压缩性能明显优于传统的数据编码方法。
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Journal of the Acoustical Society of Korea
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