Xiaoyan Zhao^1,*, Lin Zhou², Yue Xie¹, Ying Tong¹, Jingang Shi³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3087-3100, 2023, DOI:10.32604/iasc.2023.030180

Abstract Speech separation is an active research topic that plays an important role in numerous applications, such as speaker recognition, hearing prosthesis, and autonomous robots. Many algorithms have been put forward to improve separation performance. However, speech separation in reverberant noisy environment is still a challenging task. To address this, a novel speech separation algorithm using gate recurrent unit (GRU) network based on microphone array has been proposed in this paper. The main aim of the proposed algorithm is to improve the separation performance and reduce the computational cost. The proposed algorithm extracts the sub-band steered response power-phase transform (SRP-PHAT) weighted… 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

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 >