Pub Date : 1900-01-01DOI: 10.1109/ASPAA.1991.634116
P. Chu
The constraints for audio compression and echo cancellation in low bit rate videoteleconferencing (56 to 128 thousand bits per second) difeer in many important respects from audio-only teleconferencing. Algorithms which have been optimized for audio-only communications may be improved significantly or require significant improvement. In this talk, audio requirements will be presented, and we shall demonstrate with a tape how PictureTel has addressed these problems in their latest commercial product. A summary of the talk follows.
{"title":"Audio Compression and Echo Cancellation for Low Bit Rate VideoTeleconferencing","authors":"P. Chu","doi":"10.1109/ASPAA.1991.634116","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634116","url":null,"abstract":"The constraints for audio compression and echo cancellation in low bit rate videoteleconferencing (56 to 128 thousand bits per second) difeer in many important respects from audio-only teleconferencing. Algorithms which have been optimized for audio-only communications may be improved significantly or require significant improvement. In this talk, audio requirements will be presented, and we shall demonstrate with a tape how PictureTel has addressed these problems in their latest commercial product. A summary of the talk follows.","PeriodicalId":146017,"journal":{"name":"Final Program and Paper Summaries 1991 IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132870010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ASPAA.1991.634107
C. Chui, A. Chan
Splines and Spline-Wavelets of order m differ from any other functions in that they are uniquely determined by their (mlist order derivatives that are staircase waveforms (piecewise constants) of finite length. Through this important observation, we are able to build a general purpose spline/wavelet signal analyzer. A patent application which includes this class of analyzers hais been filed with the U.S. government recently [ 11. Since the mth order 13-spline and splinew,avelet (B-wavelet) have compact supports (i.e., finite duration) andthe B--wavelets are symmetric or antisymmetric depending on m being even or odd [2,3], our signal analyzer is essentially distortion free. An input analog signal is digitized and mapped into a spline: signal space (a subspace of L2 in which signals are represented by spline functions) of specific order and sulfficiently fine grid. This mapping is done by using an FIR filter based on a local cardinal interpolation method developed in [4,5]. Accordingly, the wavelet decomposition and reconstruction algorithms [2,3,6] can be applied in parallel to separate the signal into different filequency bands for different processing purposes. The result is similar to one obtained by the multi-channel filter bank method.
{"title":"A real-time Spline/Wavelet Signal Analyzer","authors":"C. Chui, A. Chan","doi":"10.1109/ASPAA.1991.634107","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634107","url":null,"abstract":"Splines and Spline-Wavelets of order m differ from any other functions in that they are uniquely determined by their (mlist order derivatives that are staircase waveforms (piecewise constants) of finite length. Through this important observation, we are able to build a general purpose spline/wavelet signal analyzer. A patent application which includes this class of analyzers hais been filed with the U.S. government recently [ 11. Since the mth order 13-spline and splinew,avelet (B-wavelet) have compact supports (i.e., finite duration) andthe B--wavelets are symmetric or antisymmetric depending on m being even or odd [2,3], our signal analyzer is essentially distortion free. An input analog signal is digitized and mapped into a spline: signal space (a subspace of L2 in which signals are represented by spline functions) of specific order and sulfficiently fine grid. This mapping is done by using an FIR filter based on a local cardinal interpolation method developed in [4,5]. Accordingly, the wavelet decomposition and reconstruction algorithms [2,3,6] can be applied in parallel to separate the signal into different filequency bands for different processing purposes. The result is similar to one obtained by the multi-channel filter bank method.","PeriodicalId":146017,"journal":{"name":"Final Program and Paper Summaries 1991 IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125506089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ASPAA.1991.634121
J. Greenberg, P. Zurek
Introduction. Recent applications of adaptive filtering to hearing aids [4-81 have shown that very simple two-microphone systems can provide large improvements in target-to-jammer ratio under anechoic conditions. Some of these studies also considered non-anechoic conditions and showed that the presence of reverberation has a strong effect on performance. Because of differences among the acoustic and signal-processing conditions of these studies, a more detailed summary cannot be given. The present study illustrates , for a particular adaptive beamformer, the effects of reverberation on performance and the interactions among reverberation, target-to-jammer ratio (TJR) and filter length (L). System Description and Methods. The system used here (Figure 1) is a modified, two-microphone version of the Griffiths-Jim (21 constnained adaptive beamformer. The modifications were developed to deal with the problems of misadjustnient and misalignment at high TJRs and do so by exploiting the fluctuations in speech to allow adaptation during intervals of low TJR [l]. The first method employs the input correlation p between bandpass-filtered microphone signals as a measure of TJR and inhibits adaptation when p exceeds a threshold. The second method includes output power in the normalization of the weight update: Aw&z + 1) = 2ay[n]d[n-k]/{L(P,,[n] + Pd[n])}, where Py and P d are running estimates of power in the system output and the adaptive filter' The study employed computer simulations of this beamformer with 7-cm spacing between microphones in free-space. Input signals were generated by convolving single-talker target and babble jammer sources with synthetic source-to-microphone impulse responses [3]. For all conditions, the target was located at 0", broadside to the array, the jammer was at 45", and both sources were 0.9 m from the center of the array. Output target and jammer were measured separately through use of a master and two slave processors. The master processed target and jammer summed together, while the slave systems processed the target and jammer separately using adaptive filter weights copied from the master. The performance metric, GI, is a spectrally-weighted gain in target-to-jammer ratio from input to output, measured in the steady-state [6]. Results. A sampling of rooms and source/array geometries was simulated to study the joint effects of TJR, degree of reverberation, and filter length. Condition A employed a room with dimensions 5.2 x 3.4 x 2.8 mtders and a uniform absorption coefficient of 1.0 (anechoic), 0.6, or 0.2, resulting in direct-to-reverberant energy ratios at the array of 00, 5.7,oI-2.4 dB, respectively. The …
介绍。最近自适应滤波在助听器中的应用[4-81]表明，在消声条件下，非常简单的双麦克风系统可以大大提高目标与干扰器的比例。其中一些研究还考虑了非消声条件，并表明混响的存在对性能有很强的影响。由于这些研究的声学和信号处理条件存在差异，因此无法给出更详细的总结。本研究说明了一个特定的自适应波束形成器，混响对性能的影响，以及混响、目标干扰比(TJR)和滤波器长度(L)之间的相互作用。这里使用的系统(图1)是一个改进的双麦克风版本的格里菲斯-吉姆(21)包含自适应波束形成器。这些修改是为了处理高TJR时的失调和不对准问题，并通过利用语音的波动来允许在低TJR间隔期间进行适应[1]。第一种方法采用带通滤波麦克风信号之间的输入相关性p作为TJR的度量，并在p超过阈值时抑制自适应。第二种方法包括权值更新归一化中的输出功率:Aw&z + 1) = 2ay[n]d[n-k]/{L(P，，[n] + Pd[n])}，其中Py和Pd为系统输出和自适应滤波器中功率的运行估计。研究采用自由空间中麦克风间距为7 cm的波束形成器的计算机模拟。输入信号由具有合成源-传声器脉冲响应的单话音目标和杂波干扰源进行卷积产生[3]。在所有条件下，目标位于0”，阵列侧，干扰机位于45”，两个源距离阵列中心0.9 m。通过使用一个主处理器和两个从处理器分别测量输出目标和干扰器。主系统对目标和干扰机进行综合处理，从系统使用从主系统复制的自适应滤波权值分别对目标和干扰机进行处理。性能指标GI是从输入到输出的目标与干扰器之比的频谱加权增益，在稳态下测量[6]。结果。模拟了房间和源/阵列几何形状的采样，以研究TJR、混响程度和滤波器长度的联合影响。条件A使用一个尺寸为5.2 x 3.4 x 2.8 m的房间，均匀吸收系数为1.0(消声)，0.6或0.2，导致阵列的直接-混响能量比分别为00,5.7,0 -2.4 dB。…
{"title":"Adaptive Beamformer Performance In Reverberation","authors":"J. Greenberg, P. Zurek","doi":"10.1109/ASPAA.1991.634121","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634121","url":null,"abstract":"Introduction. Recent applications of adaptive filtering to hearing aids [4-81 have shown that very simple two-microphone systems can provide large improvements in target-to-jammer ratio under anechoic conditions. Some of these studies also considered non-anechoic conditions and showed that the presence of reverberation has a strong effect on performance. Because of differences among the acoustic and signal-processing conditions of these studies, a more detailed summary cannot be given. The present study illustrates , for a particular adaptive beamformer, the effects of reverberation on performance and the interactions among reverberation, target-to-jammer ratio (TJR) and filter length (L). System Description and Methods. The system used here (Figure 1) is a modified, two-microphone version of the Griffiths-Jim (21 constnained adaptive beamformer. The modifications were developed to deal with the problems of misadjustnient and misalignment at high TJRs and do so by exploiting the fluctuations in speech to allow adaptation during intervals of low TJR [l]. The first method employs the input correlation p between bandpass-filtered microphone signals as a measure of TJR and inhibits adaptation when p exceeds a threshold. The second method includes output power in the normalization of the weight update: Aw&z + 1) = 2ay[n]d[n-k]/{L(P,,[n] + Pd[n])}, where Py and P d are running estimates of power in the system output and the adaptive filter' The study employed computer simulations of this beamformer with 7-cm spacing between microphones in free-space. Input signals were generated by convolving single-talker target and babble jammer sources with synthetic source-to-microphone impulse responses [3]. For all conditions, the target was located at 0\", broadside to the array, the jammer was at 45\", and both sources were 0.9 m from the center of the array. Output target and jammer were measured separately through use of a master and two slave processors. The master processed target and jammer summed together, while the slave systems processed the target and jammer separately using adaptive filter weights copied from the master. The performance metric, GI, is a spectrally-weighted gain in target-to-jammer ratio from input to output, measured in the steady-state [6]. Results. A sampling of rooms and source/array geometries was simulated to study the joint effects of TJR, degree of reverberation, and filter length. Condition A employed a room with dimensions 5.2 x 3.4 x 2.8 mtders and a uniform absorption coefficient of 1.0 (anechoic), 0.6, or 0.2, resulting in direct-to-reverberant energy ratios at the array of 00, 5.7,oI-2.4 dB, respectively. The …","PeriodicalId":146017,"journal":{"name":"Final Program and Paper Summaries 1991 IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125913282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ASPAA.1991.634147
J.C. Brown
q u a n t i t i e s of d a t a and a t t e m p t i n g t o d e t e r m i n e by c o m p u t a t i o n t h e q u a n t i t i e s which a p p e a r s o e a s i l y o b t a i n e d by human b e i n g s. One s u c h q u a n t i t y i s m u s i c a l meter.
{"title":"Determination of Musical Meter using the Method of Autocorrelation","authors":"J.C. Brown","doi":"10.1109/ASPAA.1991.634147","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634147","url":null,"abstract":"q u a n t i t i e s of d a t a and a t t e m p t i n g t o d e t e r m i n e by c o m p u t a t i o n t h e q u a n t i t i e s which a p p e a r s o e a s i l y o b t a i n e d by human b e i n g s. One s u c h q u a n t i t y i s m u s i c a l meter.","PeriodicalId":146017,"journal":{"name":"Final Program and Paper Summaries 1991 IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116633704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ASPAA.1991.634127
N. Dillier, H. Bogli, T. Frohlich, M. Kompis
SUMMARY Hearing sensations can be restored for profoundly deaf patients via artificial electrical stimulation of the auditory nerve. Present electrode technology and electrophysiological constraints however allow at best a very crude and limited approximation of the normal neural excitation pattern. Signal processing for cochlear implants therefore is confronted with the problem of a severely restricted channel capacity and the necessity to select and encode a subset of the information contained in the sound signal reaching the listeners ear. With single chip digital signal processors (DSPs) incorporated in personal computers different speech coding strategies can be evaluated in relatively short laboratory experiments. In addition to the well known strategies realized with filters, amplifiers and logic circuits a DSP approach allows the implementation of much more complex algorithms such as nonlinear multiband loudness correction, speech feature contrast enhancement, adaptive noise reduction. Although many aspects of speech encoding can be efficiently studied using a laboratory digital signal processor it would be desirable to allow subjects more time for adjustment to a new coding strategy. Several days or weeks of habituation are sometimes required until a new mapping can be fully exploited. Thus for scientific as well as practical purposes the miniaturization of wearable DSPs will be of great importance. A cochlear implant digital speech processor (CIDSP) for the Nucleus 22-channel cochlear prosthesis has been implemented using a single chip digital signal processor (TMS320C25, Texas Instruments). For laboratory experiments the CIDSP is incorporated in a general purpose computer (PDP11/73) which provides interactive parameter control, graphical display of input/output and intermediate buffers and offline speech file processing facilities. In addition to the generation of stimulus parameters for the cochlear implant an acoustic signal based on a perceptive model of auditory nerve stimulation is output simultaneously. For field studies and as a take-home device for patients a wearable battery-operated unit has been built. Advantages of a DSP-implementation of speech encoding algorithms as opposed to offline prepared tcst lists are increased flexibility, controlled, reproducible and fast modifications of processing parameters, use of running speech for training and familiarization. Disadvantages are the more complex programming and numerical problems with integer arithmetic.
{"title":"DSP-implementations of speech coding for multielectrode cochlear implants and multiband loudness correction for digital hearing aids","authors":"N. Dillier, H. Bogli, T. Frohlich, M. Kompis","doi":"10.1109/ASPAA.1991.634127","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634127","url":null,"abstract":"SUMMARY Hearing sensations can be restored for profoundly deaf patients via artificial electrical stimulation of the auditory nerve. Present electrode technology and electrophysiological constraints however allow at best a very crude and limited approximation of the normal neural excitation pattern. Signal processing for cochlear implants therefore is confronted with the problem of a severely restricted channel capacity and the necessity to select and encode a subset of the information contained in the sound signal reaching the listeners ear. With single chip digital signal processors (DSPs) incorporated in personal computers different speech coding strategies can be evaluated in relatively short laboratory experiments. In addition to the well known strategies realized with filters, amplifiers and logic circuits a DSP approach allows the implementation of much more complex algorithms such as nonlinear multiband loudness correction, speech feature contrast enhancement, adaptive noise reduction. Although many aspects of speech encoding can be efficiently studied using a laboratory digital signal processor it would be desirable to allow subjects more time for adjustment to a new coding strategy. Several days or weeks of habituation are sometimes required until a new mapping can be fully exploited. Thus for scientific as well as practical purposes the miniaturization of wearable DSPs will be of great importance. A cochlear implant digital speech processor (CIDSP) for the Nucleus 22-channel cochlear prosthesis has been implemented using a single chip digital signal processor (TMS320C25, Texas Instruments). For laboratory experiments the CIDSP is incorporated in a general purpose computer (PDP11/73) which provides interactive parameter control, graphical display of input/output and intermediate buffers and offline speech file processing facilities. In addition to the generation of stimulus parameters for the cochlear implant an acoustic signal based on a perceptive model of auditory nerve stimulation is output simultaneously. For field studies and as a take-home device for patients a wearable battery-operated unit has been built. Advantages of a DSP-implementation of speech encoding algorithms as opposed to offline prepared tcst lists are increased flexibility, controlled, reproducible and fast modifications of processing parameters, use of running speech for training and familiarization. Disadvantages are the more complex programming and numerical problems with integer arithmetic.","PeriodicalId":146017,"journal":{"name":"Final Program and Paper Summaries 1991 IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131384399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ASPAA.1991.634120
V. DeBrunner, A. Beex
Extended Summary We consider the design and performance of a restricted geometry, narrowband, adaptive 2-element (termed "small") acoustic array as used for directional hearing enhancement. An array is designed to be mobile and burden-free, so that the wearer is not encumbered by the harldware, while remaining usehl in noisy environments. The directionality of multi-element arrays, and thus the capability for interference rejection, is greatly superior to that possible with a single-element device. Enhanced directionality comes from the extra knowledge gained when acoustic signals are spatially sampled. Intuitively, we expect such a result since humans have 2 ears to hear with, and we do not have the "extra" one merely for redundancy. This increased knowledge comes at the expense of increased hardware requirements, as well as an increase in real-time computations and communications. We explore the balance between directionality improvlement and hardware requirements. Making the array adaptive is shown to enhance the array directionality above that achievable by a iixed array which we have examined previously. We examine the perf'ornnance of small, adaptive, nonlinear acoustic arrays for
{"title":"Narrowband Adaptive Acoustic Arrays For Directional Interference Nulling","authors":"V. DeBrunner, A. Beex","doi":"10.1109/ASPAA.1991.634120","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634120","url":null,"abstract":"Extended Summary We consider the design and performance of a restricted geometry, narrowband, adaptive 2-element (termed \"small\") acoustic array as used for directional hearing enhancement. An array is designed to be mobile and burden-free, so that the wearer is not encumbered by the harldware, while remaining usehl in noisy environments. The directionality of multi-element arrays, and thus the capability for interference rejection, is greatly superior to that possible with a single-element device. Enhanced directionality comes from the extra knowledge gained when acoustic signals are spatially sampled. Intuitively, we expect such a result since humans have 2 ears to hear with, and we do not have the \"extra\" one merely for redundancy. This increased knowledge comes at the expense of increased hardware requirements, as well as an increase in real-time computations and communications. We explore the balance between directionality improvlement and hardware requirements. Making the array adaptive is shown to enhance the array directionality above that achievable by a iixed array which we have examined previously. We examine the perf'ornnance of small, adaptive, nonlinear acoustic arrays for","PeriodicalId":146017,"journal":{"name":"Final Program and Paper Summaries 1991 IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115543435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ASPAA.1991.634145
A. Barbosa, S. Kuo
Abstract: This paper presents or stabiliry analysis of an active periodic noise control (APNC) system using an internally generated impulse train with the same fundamental frequency as the noise to be canceled as reference input. The stability analysis is made through the use of polar plots and shows how the compensation of the input to the LMS adaptation cfiltered-X) can improve stability of the APNC system. This polar plot also shows the relationship between the stability of the system and step size p andjilter order hr.
{"title":"Stability Analysis of an Active Periodic Noise Control System","authors":"A. Barbosa, S. Kuo","doi":"10.1109/ASPAA.1991.634145","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634145","url":null,"abstract":"Abstract: This paper presents or stabiliry analysis of an active periodic noise control (APNC) system using an internally generated impulse train with the same fundamental frequency as the noise to be canceled as reference input. The stability analysis is made through the use of polar plots and shows how the compensation of the input to the LMS adaptation cfiltered-X) can improve stability of the APNC system. This polar plot also shows the relationship between the stability of the system and step size p andjilter order hr.","PeriodicalId":146017,"journal":{"name":"Final Program and Paper Summaries 1991 IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123205902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ASPAA.1991.634124
Maynard Engebretson, Michael P. OConnell, Fengmin Gong
A method is described for adaptively equalizing the ubiquitous feedback path of a hearing aid in order to stabilize the system. The algorithm utilizes an LMS adaptive filter and is implemented in digital form. An additional 10 to 15 dB of stable gain margin has been demonstrated. INTRODUCTION System instability is a commonly cited problem with regard to highpower hearing aids, where it is desirable to achieve high acoustic gains, and with intheear devices, where acoustical and mechanical isolation between input and output is difficult to achieve. Instability is a result of feedback due to 1) acoustic leakage around the earmold and through the vent in the earmold and 2) mechanical coupling between receiver and microphone As is well known, when the open loop gain of a system with feedback is greater than unity and has a phase which is a multiple of 2n radians, the system will oscillate [l], thereby causing a serious degradation of signal quality. In addition, if the open loop gain is close to but less than unity, the system response will be highly underdamped and will exhibit a response sharply divergent from the desired frequency-gain characteristic prescribed for the hearing-impaired patient. Current methods for reducing hearing aid instability are limited to the use of tightly fitting m o l d s . However, this is difficult to achieve without causing discomfort for the patient. A number of methods of feedback suppression have been proposed. For example, Egolf and Larson [2] have studied two methods, one, a time delay notch filter system and, two, an active feedback cancellation system. They report improvements of between 6 and 8 dB in closed loop gain margin with both approaches and, if conditions are carefully controlled, up to 15 to 20 dJ3 [3]. The algorithm described herein, is similar to the active feedback cancellation system, and stabilizes the hearing aid by adaptively cancelling its feedback path. Since the algorithm is adaptive, it can accommodate to changes in the feedback characteristic of the hearing aid. Equalization is accomplished with a Widrow LMS adaptive filter [4]. The adaptive process is driven by an internally generated pseudorandom signal presented at threshold and subthreshold levels similar to that used by Schroeder [5]. The algorithm has been refined for implementation on small digital processing structures. THE FEEDBACK EQUALIZATION MODEL The equalized hearing aid model is shown in the figure where Hm and Hr represent the microphone and receiver characteristics, respectively, Hf represents the undesirable acoustic and mechanical feedback paths, H represents a filter function that when multiplied by Hm and Hr yields the prescribed acoustic fkequencygain function for the patient, and & represents the adaptive equalization filter. X, Y, and N represent the input sound pressure at the hearing aid microphone, the sound pressure in the ear canal, and the pseudorandom probe signal, respectively. The closed-loop transfer charact
本文描述了一种自适应均衡助听器无所不在反馈路径以稳定系统的方法。该算法采用LMS自适应滤波器，并以数字形式实现。另外10到15db的稳定增益裕量已被证实。系统不稳定性是高功率助听器的一个常见问题，在高功率助听器中需要获得高声学增益，而在耳内助听器中，输入和输出之间的声学和机械隔离很难实现。不稳定性是由于反馈造成的:1)耳模周围和通过耳模通风孔的声泄漏，2)接收器和麦克风之间的机械耦合。众所周知，当有反馈的系统的开环增益大于1且相位为2n弧度的倍数时，系统将产生振荡[1]，从而导致信号质量的严重下降。此外，如果开环增益接近但小于1，则系统响应将高度欠阻尼，并且将表现出与为听力受损患者规定的期望频率增益特性截然不同的响应。目前减少助听器不稳定性的方法仅限于使用紧密贴合的助听器。然而，这很难在不引起病人不适的情况下实现。人们提出了许多抑制反馈的方法。例如，Egolf和Larson[2]研究了两种方法，一种是延时陷波滤波系统，另一种是主动反馈抵消系统。他们报告说，两种方法的闭环增益裕度都有6到8 dB的改善，如果条件得到仔细控制，可以提高到15到20 dJ3[3]。本文所述的算法类似于有源反馈抵消系统，通过自适应抵消其反馈路径来稳定助听器。由于算法是自适应的，可以适应助听器反馈特性的变化。均衡是由Widrow LMS自适应滤波器[4]完成的。自适应过程是由内部产生的伪随机信号驱动的，该信号呈现在阈值和亚阈值水平，类似于施罗德[5]所使用的。该算法经过改进，可以在小型数字处理结构上实现。均衡助听器模型如图所示，其中Hm和Hr分别表示麦克风和接收器的特性，Hf表示不希望的声学和机械反馈路径，H表示滤波器函数，乘以Hm和Hr得到患者规定的声学频率增益函数，&表示自适应均衡滤波器。X、Y、N分别为助听器麦克风输入声压、耳道内声压和伪随机探头信号。图中系统的闭环传递特性可以表示为:分子中的项Hm H Hr是所要求的规定的频率增益函数。分母中的项H(Hm Hf Hr &)表示系统的开环增益。如果这个项大于1，并且相位是2x弧度的倍数，则系统将是不稳定的。如果方程1的分母项为零，即He = HmHfHr，则系统稳定，总体响应为规定响应。在理论上，它应该是有可能实现尽可能多的稳定的声学增益与期望的均衡。然而，在实践中，最大稳定增益受到I&和HmHfHr之间可以实现的抵消程度的限制。下面将讨论这些限制。自适应算法HmHfHr的消去是通过一种自适应算法来实现的，该算法调整&的系数，使误差函数E在最小均方意义上最小化，如图所示。误差是外部反馈路径与均衡滤波器之间的差的函数，可以表示为:E =Hm X + (Hm Hf Hr He) (N + Z)(2)如果变量N, Z和N不相关，很容易看出，只能通过调整均衡滤波器l和来最小化E m r。的系数(分接权重)的递归表达式可由式2导出，与Widrow自适应LMS滤波器[5]的递归表达式相同。递归表达式为:FIR滤波器可以抵消声反馈和机械反馈路径。Ck(n+l) = Cdn) + be (n) x(nk)(3)滤波器的失配可能是由于处理噪声和输入信号x在误差项中存在。
{"title":"An Adaptive Feedback Equalization Algorithm For Digital Hearing Aids","authors":"Maynard Engebretson, Michael P. OConnell, Fengmin Gong","doi":"10.1109/ASPAA.1991.634124","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634124","url":null,"abstract":"A method is described for adaptively equalizing the ubiquitous feedback path of a hearing aid in order to stabilize the system. The algorithm utilizes an LMS adaptive filter and is implemented in digital form. An additional 10 to 15 dB of stable gain margin has been demonstrated. INTRODUCTION System instability is a commonly cited problem with regard to highpower hearing aids, where it is desirable to achieve high acoustic gains, and with intheear devices, where acoustical and mechanical isolation between input and output is difficult to achieve. Instability is a result of feedback due to 1) acoustic leakage around the earmold and through the vent in the earmold and 2) mechanical coupling between receiver and microphone As is well known, when the open loop gain of a system with feedback is greater than unity and has a phase which is a multiple of 2n radians, the system will oscillate [l], thereby causing a serious degradation of signal quality. In addition, if the open loop gain is close to but less than unity, the system response will be highly underdamped and will exhibit a response sharply divergent from the desired frequency-gain characteristic prescribed for the hearing-impaired patient. Current methods for reducing hearing aid instability are limited to the use of tightly fitting m o l d s . However, this is difficult to achieve without causing discomfort for the patient. A number of methods of feedback suppression have been proposed. For example, Egolf and Larson [2] have studied two methods, one, a time delay notch filter system and, two, an active feedback cancellation system. They report improvements of between 6 and 8 dB in closed loop gain margin with both approaches and, if conditions are carefully controlled, up to 15 to 20 dJ3 [3]. The algorithm described herein, is similar to the active feedback cancellation system, and stabilizes the hearing aid by adaptively cancelling its feedback path. Since the algorithm is adaptive, it can accommodate to changes in the feedback characteristic of the hearing aid. Equalization is accomplished with a Widrow LMS adaptive filter [4]. The adaptive process is driven by an internally generated pseudorandom signal presented at threshold and subthreshold levels similar to that used by Schroeder [5]. The algorithm has been refined for implementation on small digital processing structures. THE FEEDBACK EQUALIZATION MODEL The equalized hearing aid model is shown in the figure where Hm and Hr represent the microphone and receiver characteristics, respectively, Hf represents the undesirable acoustic and mechanical feedback paths, H represents a filter function that when multiplied by Hm and Hr yields the prescribed acoustic fkequencygain function for the patient, and & represents the adaptive equalization filter. X, Y, and N represent the input sound pressure at the hearing aid microphone, the sound pressure in the ear canal, and the pseudorandom probe signal, respectively. The closed-loop transfer charact","PeriodicalId":146017,"journal":{"name":"Final Program and Paper Summaries 1991 IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123047254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ASPAA.1991.634095
U. Laine, M. Karjalainen, T. Altosaar
The human auditory system is known to utilize different temporal and frequency re,solutions in different contexts and analysis phases. In this paper we discuss some aspects of using time-frequency representations and multiple resolutions in auditory modeling from an information and signal theoretic point of view. The first question is how to allocate resolution optimally between frequency and time. For this purpose a new method called the FAM tranSform is described. The other question is how to utilize multiple parallel and redundant resolutions to avoid some problems that are faced when using single resolution approaches.
{"title":"Time-frequency And Multiple-resolution Representations In Auditory Modeling","authors":"U. Laine, M. Karjalainen, T. Altosaar","doi":"10.1109/ASPAA.1991.634095","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634095","url":null,"abstract":"The human auditory system is known to utilize different temporal and frequency re,solutions in different contexts and analysis phases. In this paper we discuss some aspects of using time-frequency representations and multiple resolutions in auditory modeling from an information and signal theoretic point of view. The first question is how to allocate resolution optimally between frequency and time. For this purpose a new method called the FAM tranSform is described. The other question is how to utilize multiple parallel and redundant resolutions to avoid some problems that are faced when using single resolution approaches.","PeriodicalId":146017,"journal":{"name":"Final Program and Paper Summaries 1991 IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130012203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ASPAA.1991.634113
B. Bhaskar
The technique of Adaptive Predictive Coding with Transform domain Quantization (APCTQ) has been studled for high quality coding of audio signals, at rates in the range 1.5 2.5 bit/sample. This technique is a combination of time domain predictive methods with transform domain quantization methods. Near transparent quality performance has been obtained at 5 kHz and 7.5 kHz bandwidths at rates of 24 kbit/s and 32 kbit/s respectively. In general, the APC-TQ technique is applicable over a wide range of signal bandwidths from 5 kHz to 20 kHz, for efficient transmission of high quality audio signals for applications such as direct audio broadcasing.
{"title":"Adaptive Prediction With Transform Domain Quantization For Low-rate Audio Coding","authors":"B. Bhaskar","doi":"10.1109/ASPAA.1991.634113","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634113","url":null,"abstract":"The technique of Adaptive Predictive Coding with Transform domain Quantization (APCTQ) has been studled for high quality coding of audio signals, at rates in the range 1.5 2.5 bit/sample. This technique is a combination of time domain predictive methods with transform domain quantization methods. Near transparent quality performance has been obtained at 5 kHz and 7.5 kHz bandwidths at rates of 24 kbit/s and 32 kbit/s respectively. In general, the APC-TQ technique is applicable over a wide range of signal bandwidths from 5 kHz to 20 kHz, for efficient transmission of high quality audio signals for applications such as direct audio broadcasing.","PeriodicalId":146017,"journal":{"name":"Final Program and Paper Summaries 1991 IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134229406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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