The methods based on Discrete Fourier Transform (DFT) are the mainstream approaches for frequency estimation of signals in power systems. However, they exhibit unfavorable long response times when confronted with signals experiencing abrupt transients, such as amplitude or phase step changes. To surmount this challenge, a novel methodology leveraging the DFT has been designed to estimate power system signals with accuracy and responsiveness under abrupt transient conditions. The method first constructs the correlation between DFT bins and each parameter. The relationship is then harnessed to derive an unbiased estimator for sine-wave with a known step position. Afterward, we introduce a step position estimation procedure that guarantees the robustness of the estimator when dealing with abrupt transients. As a result, the proposed method achieves zero response time when confronted with arbitrary abrupt transients without loss of accuracy. The effectiveness and responsiveness of our method are evaluated through simulations that adhere to the stringent requirements of P-class phasor measurement units.

Convolutional neural network (CNN) is widely used in acoustic scene classification (ASC) tasks. In most cases, local convolution is utilized to gather time-frequency information between spectrum nodes. It is challenging to adequately express the non-local link between frequency domains in a finite convolution region. In this paper, we propose a dual-path convolutional neural network based on band interaction block (DCNN-bi) for ASC, with mel-spectrogram as the model’s input. We build two parallel CNN paths to learn the high-frequency and low-frequency components of the input feature. Additionally, we have created three band interaction blocks (bi-blocks) to explore the pertinent nodes between various frequency bands, which are connected between two paths. Combining the time-frequency information from two paths, the bi-blocks with three distinct designs acquire non-local information and send it back to the respective paths. The experimental results indicate that the utilization of the bi-block has the potential to improve the initial performance of the CNN substantially. Specifically, when applied to the DCASE 2018 and DCASE 2020 datasets, the CNN exhibited performance improvements of 1.79% and 3.06%, respectively. © 2024 The Institute of Electronics, Information and Communication Engineers.

Purpose: The purpose of this study was to determine the speech recognition equivalence of Mandarin Bamford-Kowal-Bench (BKB) sentence lists with adults and children with normal hearing. Method: A total of 32 lists, each of nine sentences, were compiled from a corpus of BKB-like sentences with paired babble in Mandarin. Interlist equivalence, critical differences, and sensitivity of performance to signal-to-noise ratio (SNR) were examined. Experiment 1 included 64 native Mandarin-speaking adults with normal hearing. Experiment 2 included 54 native Mandarin-speaking children with normal hearing aged 4-6 years. Results: Among the 32 sentence lists, 28 lists were confirmed to be equivalent in adults, with a mean SNR required for 50% correct (SNR50) of -5.9 +/- 0.1 dB, a mean slope of 22.3%/dB +/- 1.5%/dB, and a grand 95% critical difference subsequently calculated as 27.2% for score. From the 28 equivalent lists, 27 lists were selected and observed to be equivalent in children, with a mean SNR50 threshold of -2.0 +/- 0.2 dB, a mean slope of 15.8%/dB +/- 1.1%/dB, and a grand 95% critical difference of 24.6% for score. Conclusions: The Mandarin BKB sentences in babble noise test offers an opportunity for clinicians and researchers to assess speech understanding in adults and preschool children in an efficient manner. For comparisons of performance in different test conditions, 28 equivalent lists are available for adults and 27 equivalent lists for preschool children. The 95% critical difference values can be used for total percentage correct or SNR for 50% performance. Future work will examine the clinical utility for school-age children and children who are deaf and hard of hearing.

研发并推广普适、普惠、普及且合用的助听器，是发展中国家助听器及其服务指南(第二版)的要求，也是解决我国老年性听力损失干预困局的利器。本课题为评估课题4所开发的国产高性能、免验配助听器产品：完善了中文言语测试材料与工具，研发了汉语普通话版开放式CMnBio语句测听材料及闭合式听音识图”类辅音识别材料；开发了适用于中老年人听力自评估的(PC端&移动设备端)言语测听系统并获得软件著作权；建立便捷的中文语境下助听临床评估框架；开展临床对照研究，完成了157例国产高性能助听器与国外同档次助听器的临床对比研究及71例传统验配模式与自主验配模式前瞻性随机对照单盲研究；此外，根据以上研究结果，撰写了国产高性能、免验配助听器的应用示范总体方案与实施细则。WHO(2004)announced the guidelines containing requirements and recommendation for developing countries in which hearing aids and services shall be appropriate,acceptable,affordable and available.It shall also be the approach to resolve the dilemma related with the low prevalence of hearing aid acquisition in Chinese older adults.To evaluate the high-performance,self-fitting hearing aid which were designed and product by Study Ⅳ,we improved Mandarin speech test materials,including a Mandarin Chinese open-set sentence material,CMnBio,and a closed-set“WIPI”(the world intelligibility by picture identification)consonant recognition material.Meanwhile,we developed the speech audiometry system(PC software&App)for elderly listening self-evaluation,whose copyright is obtained.Then,a comparative study on the performance of the high-performance,self-fitting hearing aid made in China and abroad(157 clinical trials),and a prospective-randomized study on the effect between routine-fitting and self-fitting hearing aids(71 clinical trials)are carried out.Based on the study conclusion,we drew out the program of demonstration and implementation of high-performance,self-fitting hearing aids application in China.

针对经典助听器听力补偿算法在噪声和干扰声等场景中性能下降的问题，本课题研究基于现代音频信号处理和人工智能技术的新型助听器语音处理算法。在通道自适应的宽动态范围压缩方面，提出了增益平稳调节的动态范围控制算法和自适应滤波器的助听器宽动态范围压缩算法；在基于人工智能技术的算法参数优化方面，提出了基于深度域自适应网络的迁移学习模型，融合时序卷积网络和残差块；在助听器自适应语音方向性合成技术方面，提出融合广义旁瓣对消和自适应陷波滤波器的助听器指向性算法、基于信噪比的数字助听器自适应指向性算法、基于回归器和密集连接卷积网络的声方位估计算法；在基于自适应环境识别的多类噪声抑制及反馈消除算法研究方面，提出了非线性回声抑制方法、基于互相关检测与时频掩蔽的助听器风噪声抑制算法、面向瞬态噪声抑制的语音增强方法，在深度神经网络方面，提出了基于混合空洞卷积网络和残差密集网络、面向麦克风阵列的通道注意力加权、基于特征维度自注意力的语音增强方法。本课题共发表了论文13篇，其中SCI收录9篇，申请专利13项，其中授权8项，研究成果降低了各种环境干扰对助听器使用的影响，实现了助听器感知语音质量的提升，提高了患者的言语交流能力和助听器使用舒适度，获得更好的助听效果，同时系统计算量小，实时性好，满足了数字助听器的低功耗高实时性设备的要求，提升国产数字化助听器等听力康复设备的技术水平。Aiming at the problem of performance degradation of classical hearing aid hearing compensation algorithms in scenarios such as background noise and interference signals,this project investigates new hearing aid speech processing algorithms based on modern speech signal processing and artificial intelligence technology.In terms of channel adaptive wide dynamic compression,a dynamic range control algorithm with smooth gain adjustment and an adaptive filter wide dynamic range compression algorithm for hearing aids are proposed;in terms of algorithmic parameter optimization based on artificial intelligence technology,a transfer learning model based on a deep domain adaptive networks fusing temporal convolutional networks and residual blocks is proposed;in terms of adaptive speech directionality synthesis for hearing aids,directionality algorithm integrating generalized sidelobe canceller and adaptive notch filter,a digital hearing aid adaptive directionality algorithm based on signal-to-noise ratio,and an sound source localization algorithm based on regressor and densely connected convolutional network are proposed;In terms of multi-class noise suppression and feedback cancellation algorithms based on adaptive environment recognition,nonlinear echo suppression methods,wind noise suppression algorithms for hearing aids based on cross correlation detection and time-frequency masking are proposed.Also,for deep neural network-based speech enhancement,speech enhancement methods based on hybrid dilated convolution networks and residual dense networks,microphone array-based channel attention weighting,and feature dimension self-attention are proposed.A total of 13 papers have been published,of which 9 are SCI-indexed,and 13 patents have been applied for,of which 8 are authorized.The research reduces the impact of various environmental interference on the use of hearing aids,achieve the improvement of the perceived speech quality of hearing aids,improve the patient's speech communication ability and the comfort of using hearing aids,and obtain better hearing aid effects.Also,the system has low computation complexity,which meets the requirements of low-power and high real-time equipment for digital hearing aids.This research improves the technical level of domestic digital hearing aids and other hearing rehabilitation equipment.

针对传统助听器在存在的问题，本课题主要研究高性能及免验配助听器的系统电路设计、算法优化与实现、通用声学结构设计等关键技术，攻克高性能助听器音频处理算法与芯片算力与功耗的矛盾，突破基于模式切换的免验配助听器个性化补偿效果不佳的问题，完成性能指标达到国际领先水平的高性能助听器及适用于广大听障人群自调佩戴的免验配助听器产品。_x000D_课题从关键元件选型、电路设计、声结构设计、算法移植、验配软件研发等方面开展研究完成了高性能全数字助听器和免验配全数字助听器的样机研发。_x000D_课题基于数字助听器专用信号处理平台进行了高性能全数字助听器和免验配全数字助听器的算法实现、样机研发以及验配软件开发。课题组对信号处理平台的特点、体系架构、固件库、指令集及各种资源进行了充分学习和调研，在此基础上开展相关工作。_x000D_根据高性能与免验配数字助听器的要求选择了能满足需求的传声器和受话器元件，对高性能数字助听器，特别选择了预匹配的全向传声器。综合考虑助听器芯片、助听器声腔结构等因素设计了助听器柔性电路板。针对助听器啸叫引起佩戴者极大不适的问题，设计了一种抑制数字助听器产生啸叫的声结构。针对高性能和免验配助听器，研制了PC端验配软件和验配软件手机APP,可通过HIPRO专用设备或者蓝牙调节助听器的音量、程序、增益、通道、附加功能等等，为用户提供远程验配，听力测试以及对应听力图的自主验配等。In response to the problems existing in traditional hearing aids,this project mainly focuses on key technologies such as system circuit design,algorithm optimization and implementation,and universal acoustic structure design for high-performance and exempt hearing aids.It aims to overcome the challenges of audio processing algorithms and chip computing power and power consumption in high-performance hearing aids,and break through the problem of poor personalized compensation effect of exempt hearing aids based on mode switching,High performance hearing aids that achieve internationally leading performance indicators and are suitable for self adjusting and wearing by a large number of hearing impaired individuals._x000D_The project has conducted research and completed the prototype development of high-performance all digital hearing aids and test free all digital hearing aids from the aspects of key component selection,circuit design,sound structure design,algorithm transplantation,and testing software development._x000D_The project is based on a dedicated signal processing platform for digital hearing aids,and the algorithm implementation,prototype development,and fitting software development of high-performance all digital hearing aids and non matching all digital hearing aids have been carried out.The research team has thoroughly studied and researched the characteristics,architecture,firmware library,instruction set,and various resources of the signal processing platform,and carried out relevant work on this basis._x000D_We have selected microphone and receiver components that can meet the requirements of high-performance and test free digital hearing aids.For high-performance digital hearing aids,we have particularly selected pre matched omnidirectional microphones.A flexible circuit board for hearing aids was designed taking into account factors such as the hearing aid chip and the structure of the hearing aid cavity.A sound structure is designed to suppress the squealing of digital hearing aids,which can cause great discomfort to the wearer.We have developed a PC based matching software and matching software mobile app for high-performance and OTC hearing aids.The software and app can adjust the volume,program,gain,channel,and additional functions of the hearing aid through HIPRO dedicated devices or Bluetooth,providing users with remote matching,hearing testing,and independent matching of corresponding hearing maps.

The performance of the speech enhancement (SE) algorithm will decrease rapidly in the presence of interference, especially competing or interfering speech. In this article, an improved real-time implementation of the transfer function generalized sidelobe canceller(TF-GSC) method based on distributed dual-microphone is proposed for interference suppression in the specific direction. In our method, we first derive an improved TF-GSC method based on a primary microphone and a secondary microphone which is abbreviated as GSC-PS in the following. GSC-PS estimates the desired signal by the dual-microphone structure based on estimation of time delay of arrival and calculation of the transfer functions. After that, we propose a new adaptive interference canceller based on the multichannel speech presence probability (MC-SPP) and the output gate unit. The calculated MC-SPP is applied to the step size adjustment and cost function modification of the adaptive interference canceller, while the output gate is designed based on the normalized posterior signal-to-interference ratio difference, which is sensitive to the direction of signal sources. The simulation results show that the proposed GSC-PS algorithm outperforms the current mainstream single-channel and multi-channel SE algorithms in suppressing interference and causes less damage to the quality of the target speech. In addition, experimental results confirm the usability of the proposed algorithm in real world acoustic environment with multiple sources of noises.

Proteomics technology reveals the marker proteins, potential pathogenesis, and intervention targets after noise-induced hearing loss. To study the differences in cochlea protein expression before and after noise exposure using proteomics to reveal the pathological mechanism of noise-induced hearing loss (NIHL). A guinea pig NIHL model was established to test the ABR thresholds before and after noise exposure. The proteomics technology was used to study the mechanism of differential protein expression in the cochlea by noise stimulation. The average hearing threshold of guinea pigs on the first day after noise exposure was 57.00 ± 6.78 dB Sound pressure level (SPL); the average hearing threshold on the seventh day after noise exposure was 45.83 ± 6.07 dB SPL. The proteomics technology identified 3122 different inner ear proteins, of which six proteins related to the hearing were down-regulation: Tenascin C, Collagen Type XI alpha two chains, Collagen Type II alpha one chain, Thrombospondin 2, Collagen Type XI alpha one chain and Ribosomal protein L38, and are enriched in protein absorption, focal adhesion, and extracellular matrix receptor pathways. Impulse noise can affect the expression of differential proteins through focal adhesion pathways. This data can provide an experimental basis for the research on the prevention and treatment of NIHL. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Hearing loss is one of the most prevalent chronic health problems worldwide and a common intervention is the wearing of hearing aids. However, the tedious fitting procedures and limited hearing experts pose restrictions for the popularity of hearing aids. This paper introduced a hearing loss classification method based on the insertion gain of hearing aids, which aims to simplify the fitting procedure and achieve a fitting-free effect of the hearing aid, in line with current research trends in key algorithms for fitting-free hearing aids. The proposed method innovatively combines the insertion gain of hearing aids with the covariates of patient’s gender, age, wearing history to form a new set of hearing loss vectors, and then classifies the hearing loss into six categories by unsupervised cluster analysis method. Each category of representative parameters characterizes a typical type of hearing loss, which can be used as the initial parameter to improve the efficiency of hearing aid fitting. Compared with the traditional audiogram classification method AMCLASS (Automated Audiogram Classification System), the proposed classification method reflect the actual hearing loss of hearing impaired patients better. Moreover, the effectiveness of the new classification method was verified by the comparison between the obtained six sets of representative insertion gains and the inferred hearing personalization information. © 2023, The Author(s).