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  • Open Access

    ARTICLE

    Microphone Array-Based Sound Source Localization Using Convolutional Residual Network

    Ziyi Wang1, Xiaoyan Zhao1,*, Hongjun Rong1, Ying Tong1, Jingang Shi2

    Journal of New Media, Vol.4, No.3, pp. 145-153, 2022, DOI:10.32604/jnm.2022.030178

    Abstract Microphone array-based sound source localization (SSL) is widely used in a variety of occasions such as video conferencing, robotic hearing, speech enhancement, speech recognition and so on. The traditional SSL methods cannot achieve satisfactory performance in adverse noisy and reverberant environments. In order to improve localization performance, a novel SSL algorithm using convolutional residual network (CRN) is proposed in this paper. The spatial features including time difference of arrivals (TDOAs) between microphone pairs and steered response power-phase transform (SRP-PHAT) spatial spectrum are extracted in each Gammatone sub-band. The spatial features of different sub-bands with a frame are combine into a… More >

  • Open Access

    ARTICLE

    A Complete Analysis of Clarity (C50) Using I-SIMPA to Maintain Ideal Conditions in an Acoustic Chamber

    R. Adithya Pillai1, S. Sakthivel Murugan2,*, Guruprasad Gupta1

    Sound & Vibration, Vol.56, No.1, pp. 51-64, 2022, DOI:10.32604/sv.2022.012085

    Abstract In any closed environment considered, it can be seen that the acoustic parameters are inherently not constant over the entire area considered. In a closed environment, it is ideally preferred to maintain the acoustic parameters as constant so that there exists better quality of sound leading to better auditory perception with respect to the audience. Practically, some of the acoustic parameters like reverberation time and clarity do not strictly pertain to the pattern obtained theoretically. In this paper, simulations are carried out using I-SIMPA under different values of Sound Transmission Class (STC), source position, distribution and the chamber dimensions and… More >

  • Open Access

    ARTICLE

    Robust Sound Source Localization Using Convolutional Neural Network Based on Microphone Array

    Xiaoyan Zhao1,*, Lin Zhou2, Ying Tong1, Yuxiao Qi1, Jingang Shi3

    Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 361-371, 2021, DOI:10.32604/iasc.2021.018823

    Abstract In order to improve the performance of microphone array-based sound source localization (SSL), a robust SSL algorithm using convolutional neural network (CNN) is proposed in this paper. The Gammatone sub-band steered response power-phase transform (SRP-PHAT) spatial spectrum is adopted as the localization cue due to its feature correlation of consecutive sub-bands. Since CNN has the “weight sharing” characteristics and the advantage of processing tensor data, it is adopted to extract spatial location information from the localization cues. The Gammatone sub-band SRP-PHAT spatial spectrum are calculated through the microphone signals decomposed in frequency domain by Gammatone filters bank. The proposed algorithm… More >

  • Open Access

    ARTICLE

    Sound Source Localization Based on SRP-PHAT Spatial Spectrum and Deep Neural Network

    Xiaoyan Zhao1, *, Shuwen Chen2, Lin Zhou3, Ying Chen3, 4

    CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 253-271, 2020, DOI:10.32604/cmc.2020.09848

    Abstract Microphone array-based sound source localization (SSL) is a challenging task in adverse acoustic scenarios. To address this, a novel SSL algorithm based on deep neural network (DNN) using steered response power-phase transform (SRP-PHAT) spatial spectrum as input feature is presented in this paper. Since the SRP-PHAT spatial power spectrum contains spatial location information, it is adopted as the input feature for sound source localization. DNN is exploited to extract the efficient location information from SRP-PHAT spatial power spectrum due to its advantage on extracting high-level features. SRP-PHAT at each steering position within a frame is arranged into a vector, which… More >

  • Open Access

    ARTICLE

    Multiple Scattering Between Adjacent Sound Sources in Head-Related Transfer Function Measurement System

    Guangzheng Yu1,*, Yu Liu1,2, Bosun Xie1, Huali Zhou1

    Sound & Vibration, Vol.53, No.4, pp. 151-159, 2019, DOI:10.32604/sv.2019.04644

    Abstract To accelerate head-related transfer functions (HRTFs) measurement, two or more independent sound sources are usually employed in the measurement system. However, the multiple scattering between adjacent sound sources may influence the accuracy of measurement. On the other hand, the directivity of sound source could induce measurement error. Therefore, a model consisting of two spherical sound sources with approximate omni-directivity and a rigid-spherical head is proposed to evaluate the errors in HRTF measurement caused by multiple scattering between sources. An example of analysis using multipole re-expansion indicates that the error of ipsilateral HRTFs are within the bound of ± 1.0 dB… More >

  • Open Access

    ARTICLE

    Binaural Sound Source Localization Based on Convolutional Neural Network

    Lin Zhou1,*, Kangyu Ma1, Lijie Wang1, Ying Chen1,2, Yibin Tang3

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 545-557, 2019, DOI:10.32604/cmc.2019.05969

    Abstract Binaural sound source localization (BSSL) in low signal-to-noise ratio (SNR) and high reverberation environment is still a challenging task. In this paper, a novel BSSL algorithm is proposed by introducing convolutional neural network (CNN). The proposed algorithm first extracts the spatial feature of each sub-band from binaural sound signal, and then combines the features of all sub-bands within one frame to assemble a two-dimensional feature matrix as a grey image. To fully exploit the advantage of the CNN in extracting high-level features from the grey image, the spatial feature matrix of each frame is used as input to train the… More >

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