A filter algorithm based on cochlear mechanics and neuron filter mechanism is proposed from the view point of vibration.It helps to solve the problem that the non-linear amplification is rarely considered in studying ...A filter algorithm based on cochlear mechanics and neuron filter mechanism is proposed from the view point of vibration.It helps to solve the problem that the non-linear amplification is rarely considered in studying the auditory filters.A cochlear mechanical transduction model is built to illustrate the audio signals processing procedure in cochlea,and then the neuron filter mechanism is modeled to indirectly obtain the outputs with the cochlear properties of frequency tuning and non-linear amplification.The mathematic description of the proposed algorithm is derived by the two models.The parameter space,the parameter selection rules and the error correction of the proposed algorithm are discussed.The unit impulse responses in the time domain and the frequency domain are simulated and compared to probe into the characteristics of the proposed algorithm.Then a 24-channel filter bank is built based on the proposed algorithm and applied to the enhancements of the audio signals.The experiments and comparisons verify that,the proposed algorithm can effectively divide the audio signals into different frequencies,significantly enhance the high frequency parts,and provide positive impacts on the performance of speech enhancement in different noise environments,especially for the babble noise and the volvo noise.展开更多
A Hi Fi audio coding technology for ISDN and Internet is introduced. It is the ISO/MPEG Audio Layer III digital audio compression scheme coding at 64 kbit/s. First, the paper implements C language simulation accordin...A Hi Fi audio coding technology for ISDN and Internet is introduced. It is the ISO/MPEG Audio Layer III digital audio compression scheme coding at 64 kbit/s. First, the paper implements C language simulation according to the algorithm and gets satisfactory quality of the reconstructed music signal. The estimation of operation steps and simulation of decoder finished by a TMS 320C548 simulator are presented. The result is the same as that of the C language simulation.展开更多
Audio‐visual wake word spotting is a challenging multi‐modal task that exploits visual information of lip motion patterns to supplement acoustic speech to improve overall detection performance.However,most audio‐vi...Audio‐visual wake word spotting is a challenging multi‐modal task that exploits visual information of lip motion patterns to supplement acoustic speech to improve overall detection performance.However,most audio‐visual wake word spotting models are only suitable for simple single‐speaker scenarios and require high computational complexity.Further development is hindered by complex multi‐person scenarios and computational limitations in mobile environments.In this paper,a novel audio‐visual model is proposed for on‐device multi‐person wake word spotting.Firstly,an attention‐based audio‐visual voice activity detection module is presented,which generates an attention score matrix of audio and visual representations to derive active speaker representation.Secondly,the knowledge distillation method is introduced to transfer knowledge from the large model to the on‐device model to control the size of our model.Moreover,a new audio‐visual dataset,PKU‐KWS,is collected for sentence‐level multi‐person wake word spotting.Experimental results on the PKU‐KWS dataset show that this approach outperforms the previous state‐of‐the‐art methods.展开更多
Depression is a common mental health disorder.With current depression detection methods,specialized physicians often engage in conversations and physiological examinations based on standardized scales as auxiliary mea...Depression is a common mental health disorder.With current depression detection methods,specialized physicians often engage in conversations and physiological examinations based on standardized scales as auxiliary measures for depression assessment.Non-biological markers-typically classified as verbal or non-verbal and deemed crucial evaluation criteria for depression-have not been effectively utilized.Specialized physicians usually require extensive training and experience to capture changes in these features.Advancements in deep learning technology have provided technical support for capturing non-biological markers.Several researchers have proposed automatic depression estimation(ADE)systems based on sounds and videos to assist physicians in capturing these features and conducting depression screening.This article summarizes commonly used public datasets and recent research on audio-and video-based ADE based on three perspectives:Datasets,deficiencies in existing research,and future development directions.展开更多
随着广播电视行业的快速发展,音频信号的质量成为提升视听体验的关键因素。传统音频处理方法已无法满足现代广播电视系统对音频清晰度、动态范围及噪声控制的高要求,数字信号处理(Digital Signal Processing,DSP)技术以其强大的计算能...随着广播电视行业的快速发展,音频信号的质量成为提升视听体验的关键因素。传统音频处理方法已无法满足现代广播电视系统对音频清晰度、动态范围及噪声控制的高要求,数字信号处理(Digital Signal Processing,DSP)技术以其强大的计算能力和灵活的处理方式成为解决此问题的有效手段。重点研究DSP技术在广播电视音频信号处理中的优化措施,探讨优化噪声抑制算法、动态范围压缩、增强音频均衡处理以及集成回声消除算法等技术的融合应用。这些技术的有效结合能够显著减少噪声对音频质量的干扰,精确检测音频信号的动态变化,确保音频信号的均衡,并有效消除音频信号中的回声。展开更多
基金Project(17KJB510029)supported by the Natural Science Foundation of the Jiangsu Higher Education Institutions,ChinaProject(GXL2017004)supported by the Scientific Research Foundation of Nanjing Forestry University,China+3 种基金Project(202102210132)supported by the Important Project of Science and Technology of Henan Province,ChinaProject(B2019-51)supported by the Scientific Research Foundation of Henan Polytechnic University,ChinaProject(51521003)supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of ChinaProject(KQTD2016112515134654)supported by Shenzhen Science and Technology Program,China。
文摘A filter algorithm based on cochlear mechanics and neuron filter mechanism is proposed from the view point of vibration.It helps to solve the problem that the non-linear amplification is rarely considered in studying the auditory filters.A cochlear mechanical transduction model is built to illustrate the audio signals processing procedure in cochlea,and then the neuron filter mechanism is modeled to indirectly obtain the outputs with the cochlear properties of frequency tuning and non-linear amplification.The mathematic description of the proposed algorithm is derived by the two models.The parameter space,the parameter selection rules and the error correction of the proposed algorithm are discussed.The unit impulse responses in the time domain and the frequency domain are simulated and compared to probe into the characteristics of the proposed algorithm.Then a 24-channel filter bank is built based on the proposed algorithm and applied to the enhancements of the audio signals.The experiments and comparisons verify that,the proposed algorithm can effectively divide the audio signals into different frequencies,significantly enhance the high frequency parts,and provide positive impacts on the performance of speech enhancement in different noise environments,especially for the babble noise and the volvo noise.
文摘A Hi Fi audio coding technology for ISDN and Internet is introduced. It is the ISO/MPEG Audio Layer III digital audio compression scheme coding at 64 kbit/s. First, the paper implements C language simulation according to the algorithm and gets satisfactory quality of the reconstructed music signal. The estimation of operation steps and simulation of decoder finished by a TMS 320C548 simulator are presented. The result is the same as that of the C language simulation.
基金supported by the National Key R&D Program of China(No.2020AAA0108904)the Science and Technology Plan of Shenzhen(No.JCYJ20200109140410340).
文摘Audio‐visual wake word spotting is a challenging multi‐modal task that exploits visual information of lip motion patterns to supplement acoustic speech to improve overall detection performance.However,most audio‐visual wake word spotting models are only suitable for simple single‐speaker scenarios and require high computational complexity.Further development is hindered by complex multi‐person scenarios and computational limitations in mobile environments.In this paper,a novel audio‐visual model is proposed for on‐device multi‐person wake word spotting.Firstly,an attention‐based audio‐visual voice activity detection module is presented,which generates an attention score matrix of audio and visual representations to derive active speaker representation.Secondly,the knowledge distillation method is introduced to transfer knowledge from the large model to the on‐device model to control the size of our model.Moreover,a new audio‐visual dataset,PKU‐KWS,is collected for sentence‐level multi‐person wake word spotting.Experimental results on the PKU‐KWS dataset show that this approach outperforms the previous state‐of‐the‐art methods.
基金Supported by Shandong Province Key R and D Program,No.2021SFGC0504Shandong Provincial Natural Science Foundation,No.ZR2021MF079Science and Technology Development Plan of Jinan(Clinical Medicine Science and Technology Innovation Plan),No.202225054.
文摘Depression is a common mental health disorder.With current depression detection methods,specialized physicians often engage in conversations and physiological examinations based on standardized scales as auxiliary measures for depression assessment.Non-biological markers-typically classified as verbal or non-verbal and deemed crucial evaluation criteria for depression-have not been effectively utilized.Specialized physicians usually require extensive training and experience to capture changes in these features.Advancements in deep learning technology have provided technical support for capturing non-biological markers.Several researchers have proposed automatic depression estimation(ADE)systems based on sounds and videos to assist physicians in capturing these features and conducting depression screening.This article summarizes commonly used public datasets and recent research on audio-and video-based ADE based on three perspectives:Datasets,deficiencies in existing research,and future development directions.
文摘随着广播电视行业的快速发展,音频信号的质量成为提升视听体验的关键因素。传统音频处理方法已无法满足现代广播电视系统对音频清晰度、动态范围及噪声控制的高要求,数字信号处理(Digital Signal Processing,DSP)技术以其强大的计算能力和灵活的处理方式成为解决此问题的有效手段。重点研究DSP技术在广播电视音频信号处理中的优化措施,探讨优化噪声抑制算法、动态范围压缩、增强音频均衡处理以及集成回声消除算法等技术的融合应用。这些技术的有效结合能够显著减少噪声对音频质量的干扰,精确检测音频信号的动态变化,确保音频信号的均衡,并有效消除音频信号中的回声。
