Ziyi Wang¹, Xiaoyan Zhao^1,*, Hongjun Rong¹, Ying Tong¹, Jingang Shi²

Journal of New Media, Vol.4, No.3, pp. 145-153, 2022, DOI:10.32604/jnm.2022.030178 - 13 June 2022

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… More >

R. Adithya Pillai¹, S. Sakthivel Murugan^2,*, Guruprasad Gupta¹

Sound & Vibration, Vol.56, No.1, pp. 51-64, 2022, DOI:10.32604/sv.2022.012085 - 10 January 2022

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 More >

Xiaoyan Zhao^1,*, 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 - 26 July 2021

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… More >

Xiaoyan Zhao^{1, *}, Shuwen Chen², Lin Zhou³, Ying Chen^{3, 4}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 253-271, 2020, DOI:10.32604/cmc.2020.09848 - 20 May 2020

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 More >

Guangzheng Yu^1,*, Yu Liu^1,2, 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 More >

Lin Zhou^1,*, Kangyu Ma¹, Lijie Wang¹, Ying Chen^1,2, 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 More >