Pruning-aware Loss Functions for STOI-Optimized Pruned Recurrent Autoencoders for the Compression of the Stimulation Patterns of Cochlear Implants at Zero Delay
Cochlear implants (CIs) are surgically implanted hearing devices, which allow to restore a sense of hearing in people suffering from profound hearing loss. Wireless streaming of audio from external devices to CI signal processors has become common place. Specialized compression based on the stimulation patterns of a CI by deep recurrent autoencoders can decrease the power consumption in such a wireless streaming application through bit-rate reduction at zero latency.
While previous research achieved considerable bit-rate reductions, model sizes were ignored, which can be of crucial importance in hearing-aids due to their limited computational resources. This work investigates maximizing objective speech intelligibility of the coded stimulation patterns of deep recurrent autoencoders while minimizing model size. For this purpose, a pruning-aware loss is proposed, which captures the impact of pruning during training. This training with a pruning-aware loss is compared to conventional magnitude-informed pruning and is found to yield considerable improvements in objective intelligibility, especially at higher pruning rates. After fine-tuning, little to no degradation of objective intelligibility is observed up to a pruning rate of about 55\,\%. The proposed pruning-aware loss yields substantial gains in objective speech intelligibility scores after pruning compared to the magnitude-informed baseline for pruning rates above 45\,\%.
Enhancing spatial hearing with cochlear implants: exploring the role of AI, multimodal interaction and perceptual training
Acoustics Research Institute, Austrian Academy of Sciences（奥地利科学院声学研究所）；Centre de Recherche en Neurosciences de Lyon Inserm（里昂神经科学研究中心（Inserm））；Department of Neural Dynamics and Magnetoencephalography, Hertie Institute for Clinical Brain Research, University of Tübingen（图宾根大学神经动力学与脑磁图部门）；Centre for Integrative Neuroscience, University of Tübingen（图宾根大学整合神经科学中心）；NEMO Labs Nonprofit Kft., Budapest（布达佩斯NEMO实验室（非营利公司））
DeepSpeech models show Human-like Performance and Processing of Cochlear Implant Inputs
Center for Theoretical Neuroscience（理论神经科学中心）；Zuckerman Mind Brain Behavior Institute（扎克曼脑与行为研究所）；Columbia University（哥伦比亚大学）；Google DeepMind（谷歌DeepMind）
A Study of Joint Effect on Denoising Techniques and Visual Cues to Improve Speech Intelligibility in Cochlear Implant Simulation
Research Center for Information Technology Innovation, Academia Sinica（中央研究院资讯科技创新研究中心）；National Taiwan University（台湾大学）；Institute of Linguistics, Academia Sinica（中央研究院语言学研究所）
End-to-end audio-visual learning for cochlear implant sound coding simulations in noisy environments
Graduate Institute of Electronics Engineering（电子工程研究所）；the Department of Electrical Engineering, National Taiwan University, Taipei 106319, Taiwan（国立台湾大学电子工程系）；Research Center for Information Technology Innovation Technology, Academia Sinica, Taipei 115201, Taiwan（中科院资讯科技创新研究中心）；Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan 320314, Taiwan（Chung Yuan Christian University 电子工程系）
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）
Head shadow enhancement with low-frequency beamforming improves sound localization and speech perception for simulated bimodal listeners
KU Leuven – University of Leuven（鲁汶大学）
由于双耳线索的可用性差，许多听力受损的听众难以定位声音。带有人工耳蜗和对侧助听器的听众--所谓的双峰听众--是表现最差的，因为两耳间的时间和水平差都很难传递。提出了一种新的低频头部阴影增强方法。头部阴影增强是通过在每只耳朵中使用对侧衰减的固定波束形成器来实现的。该方法导致耳间水平差随角度单调变化。在语音和噪声空间分离的情况下，它还提高了低频信噪比。我们验证了该方法在两个实验中的声学模拟双峰听。在定位实验中，与标准全向麦克风相比，性能从50.5°提高到26.8°均方根误差。在噪声中的语音实验中，语音从正面方向呈现。当噪声来自人工耳蜗侧时，语音接收阈值提高了15.7 dB SNR，当噪声来自助听器侧时，语音接收阈值提高了7.6 dB SNR，当噪声来自各个方向时，语音接收阈值不受影响。除了双模态听众，该方法也可能是有前途的双侧人工耳蜗或助听器用户。其低计算复杂度使得该方法适合于在当前临床设备中的应用。保留字：头影增强、耳间水平差增强、声音定位、定向听力、噪声中言语、言语清晰度PACS：43.60.Fg、43.66.Pn、43.66.Qp、43.66.Rq、43.66.Ts、43.71.- k，43.71.Es，43.71.Ky
