用低频波束形成增强头部阴影改善声音 模拟双峰听者的定位与语音感知

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摘要翻译：
许多听力受损的听众由于缺乏双耳线索而难以定位声音。植入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异都很难传递。提出了一种新的低频增强头部阴影的方法。头部阴影增强是用固定的波束形成器实现的，每个耳朵都有对侧衰减。该方法产生的耳间水平差异随角度的变化而单调变化。在语音和噪声空间分离的情况下，它还提高了低频信噪比。我们在两个双峰听力声学模拟实验中验证了该方法。在定位实验中，与标准的全向传声器相比，性能从50.5{\deg}提高到26.8{\deg}。在噪声中的语音实验中，语音是从正面方向呈现的。当噪声来自人工耳蜗侧时，语音接收阈值提高了15.7dB信噪比，当噪声来自助听器侧时，语音接收阈值提高了7.6dB信噪比，当噪声来自各个方向时，语音接收阈值不受影响。除了双峰听者，这种方法也可能对双侧耳蜗植入或助听器使用者有希望。其低的计算复杂度使该方法适合于当前临床设备的应用。关键词：头影增强、耳间水平差异增强、声音定位、定向听力、噪声中的语音、语音清晰度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
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英文标题：
《Head shadow enhancement with low-frequency beamforming improves sound
  localization and speech perception for simulated bimodal listeners》
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作者：
Benjamin Dieudonn\'e, Tom Francart
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最新提交年份：
2018
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Audio and Speech Processing        音频和语音处理
分类描述：Theory and methods for processing signals representing audio, speech, and language, and their applications. This includes analysis, synthesis, enhancement, transformation, classification and interpretation of such signals as well as the design, development, and evaluation of associated signal processing systems. Machine learning and pattern analysis applied to any of the above areas is also welcome.  Specific topics of interest include: auditory modeling and hearing aids; acoustic beamforming and source localization; classification of acoustic scenes; speaker separation; active noise control and echo cancellation; enhancement; de-reverberation; bioacoustics; music signals analysis, synthesis and modification; music information retrieval;  audio for multimedia and joint audio-video processing; spoken and written language modeling, segmentation, tagging, parsing, understanding, and translation; text mining; speech production, perception, and psychoacoustics; speech analysis, synthesis, and perceptual modeling and coding; robust speech recognition; speaker recognition and characterization; deep learning, online learning, and graphical models applied to speech, audio, and language signals; and implementation aspects ranging from system architecture to fast algorithms.
处理代表音频、语音和语言的信号的理论和方法及其应用。这包括分析、合成、增强、转换、分类和解释这些信号，以及相关信号处理系统的设计、开发和评估。机器学习和模式分析应用于上述任何领域也是受欢迎的。感兴趣的具体主题包括：听觉建模和助听器；声波束形成与声源定位；声场景分类；说话人分离；有源噪声控制和回声消除；增强；去混响；生物声学；音乐信号的分析、合成与修饰；音乐信息检索；多媒体音频和联合音视频处理；口语和书面语建模、切分、标注、句法分析、理解和翻译；文本挖掘；言语产生、感知和心理声学；语音分析、合成、感知建模和编码；鲁棒语音识别；说话人识别与特征描述；应用于语音、音频和语言信号的深度学习、在线学习和图形模型；以及从系统架构到快速算法的实现方面。
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一级分类：Computer Science        计算机科学
二级分类：Sound        声音
分类描述：Covers all aspects of computing with sound, and sound as an information channel. Includes models of sound, analysis and synthesis, audio user interfaces, sonification of data, computer music, and sound signal processing. Includes ACM Subject Class H.5.5, and intersects with H.1.2, H.5.1, H.5.2, I.2.7, I.5.4, I.6.3, J.5, K.4.2.
涵盖了声音计算的各个方面，以及声音作为一种信息通道。包括声音模型、分析和合成、音频用户界面、数据的可听化、计算机音乐和声音信号处理。包括ACM学科类H.5.5，并与H.1.2、H.5.1、H.5.2、I.2.7、I.5.4、I.6.3、J.5、K.4.2交叉。
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英文摘要：
  Many hearing-impaired listeners struggle to localize sounds due to poor availability of binaural cues. Listeners with a cochlear implant and a contralateral hearing aid -- so-called bimodal listeners -- are amongst the worst performers, as both interaural time and level differences are poorly transmitted. We present a new method to enhance head shadow in the low frequencies. Head shadow enhancement is achieved with a fixed beamformer with contralateral attenuation in each ear. The method results in interaural level differences which vary monotonically with angle. It also improves low-frequency signal-to-noise ratios in conditions with spatially separated speech and noise. We validated the method in two experiments with acoustic simulations of bimodal listening. In the localization experiment, performance improved from 50.5{\deg} to 26.8{\deg} root-mean-square error compared with standard omni-directional microphones. In the speech-in-noise experiment, speech was presented from the frontal direction. Speech reception thresholds improved by 15.7 dB SNR when the noise was presented from the cochlear implant side, improved by 7.6 dB SNR when the noise was presented from the hearing aid side, and was not affected when noise was presented from all directions. Apart from bimodal listeners, the method might also be promising for bilateral cochlear implant or hearing aid users. Its low computational complexity makes the method suitable for application in current clinical devices.   Keywords: head shadow enhancement, enhancement of interaural level differences, sound localization, directional hearing, speech in noise, speech intelligibility   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
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PDF链接：
https://arxiv.org/pdf/1710.01904

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关键词：localization Availability Architecture cancellation Segmentation 阈值 enhancement deg