This study describes a binaural machine hearing system that is capable of performing auditory stream segregation in scenarios where multiple sound sources are present. The process of stream segregation refers to the capability of human listeners to group acoustic signals into sets of distinct auditory streams, corresponding to individual sound sources. The proposed computational framework mimics this ability via a probabilistic clustering scheme for joint localization and segregation. This scheme is based on mixtures of von Mises distributions to model the angular positions of the sound sources surrounding the listener. The distribution parameters are estimated using block-wise processing of auditory cues extracted from binaural signals. Additionally, the proposed system can conduct rotational head movements to improve localization and stream segregation performance. Evaluation of the system is conducted in scenarios containing multiple simultaneously active speech and non-speech sounds placed at different positions relative to the listener.
Detection of Auditory Brainstem Response Peaks Using Image Processing Techniques in Infants with Normal Hearing Sensitivity
Shahid Beheshti University of Medical Sciences（沙希德·贝赫什提医科大学）；Presidency University（总统大学）；Al-Karkh University of Science（阿尔卡尔赫科学大学）；University of Raparin（拉帕林大学）；University of Kurdistan Hewlêr（库尔德斯坦赫韦勒大学）；Arak University of Medical Sciences（阿拉克医科大学）
Sound Masking Strategies for Interference with Mosquito Hearing
Department of Physics \& Astronomy, University of California, Los Angeles, California, USA；University College London Ear Institute: London, UK；Cluster of Excellence Hearing4all, Sensory Physiology \& Behaviour Group, Department for Neuroscience, School of Medicine；California NanoSystems Institute, University of California, Los Angeles, California, USA
BiEAR: A Human Auditory-Inspired Adaptive Binaural Front-end for Multi-Speaker Localisation and Distance Estimation
The University of New South Wales（新南威尔士大学）；Tongyi Speech Lab, Alibaba Group（通义语音实验室，阿里巴巴集团）；School of Artificial Intelligence, The Chinese University of Hong Kong, Shenzhen（人工智能学院，香港中文大学（深圳））
From Spikes to Speech: NeuroVoc -- A Biologically Plausible Vocoder Framework for Auditory Perception and Cochlear Implant Simulation
Leiden Institute of Advanced Computer Science（莱顿高级计算机科学研究所）；Department of Otorhinolaryngology（耳鼻喉科部门）；Leiden Institute for Brain and Cognition（莱顿脑认知研究所）；Bioelectronics group, EEMCS（生物电子组，EEMCS）
Predicting EEG Responses to Attended Speech via Deep Neural Networks for Speech
Eriksholm Research Centre（埃里克肖尔姆研究中心）；Linköping University（林雪平大学）；University of Stuttgart（斯图加特大学）；Technical University of Denmark（丹麦技术大学）；Oticon A/S（奥迪康公司）
AADNet: Exploring EEG Spatiotemporal Information for Fast and Accurate Orientation and Timbre Detection of Auditory Attention Based on A Cue-Masked Paradigm
West China Hospital, Sichuan University（四川大学华西医院）；Institute of Electronic Engineering, China Academy of Engineering Physics（中国工程物理研究院电子工程研究所）
Modeling the Repetition-based Recovering of Acoustic and Visual Sources with Dendritic Neurons
Okinawa Institute of Science and Technology（冲绳科学技术大学院大学）；Institute of Neuroinformatics（神经信息学研究所）；University of Zurich（苏黎世大学）；ETH Zurich（苏黎世联邦理工学院）；Children’s Hospital（儿童医院）；Harvard Medical School（哈佛医学院）
Statistical validation and full-sphere extension of a Bayesian model for human static sound localisation
Dyson School of Design Engineering, Imperial College London（帝国理工学院戴森设计工程学院）；Audio Communication Group, Technische Universität Berlin（柏林工业大学音频通信组）；Department of Industrial Systems Technology and Management, University of Padova（帕多瓦大学工业系统技术与管理系）
