Pub Date : 1900-01-01DOI: 10.1109/ASPAA.1991.634087
J. Flanagan
Information signals are typically intended for human consumption. Human perception therefore contributes directly to fidelity criteria for digital representation. As computational capabilities increase and costs diminish, coding algorithms are able to iiicorporate more of the constraints that characterize perception. The incentive is still-greater economy for digital transmission and storage. Sight and sound are sensory modes favored by the human for information exchange. These modes are presently most central to humadmachine communications and multimedia systems. The intricacies of visual and auditory perception are therefore figuring more prominently in signal coding. For example, taking account of the eye's sensitivity to quantizing noise as a function of temporal and spatial frequencies leads to good-quality coding of color motion images at fractions of a bit per pixel. Similarly, the characteristics of auditory masking, in both time and frequency domains, provide leverage to identify signal components which are irrelevant to perception and which need not consume coding capacity. This discussion draws a perspective on recent coding advances and points up opportunities for increased sophistication in representing perceptual I y imp0 rtan t factors. It also indicates relations hips between economies gained by perceptual coding alone, and those where source coding can trade on signal-specific characteristics to achieve further reductions in bit rate. It COnChdeS with brief consideration of other sensory modalities, such as the tactile dimension, that might contribute to naturalness and ease of use in interactive multimedia information systems.
{"title":"Digital Representation of Perceptual Criteria","authors":"J. Flanagan","doi":"10.1109/ASPAA.1991.634087","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634087","url":null,"abstract":"Information signals are typically intended for human consumption. Human perception therefore contributes directly to fidelity criteria for digital representation. As computational capabilities increase and costs diminish, coding algorithms are able to iiicorporate more of the constraints that characterize perception. The incentive is still-greater economy for digital transmission and storage. Sight and sound are sensory modes favored by the human for information exchange. These modes are presently most central to humadmachine communications and multimedia systems. The intricacies of visual and auditory perception are therefore figuring more prominently in signal coding. For example, taking account of the eye's sensitivity to quantizing noise as a function of temporal and spatial frequencies leads to good-quality coding of color motion images at fractions of a bit per pixel. Similarly, the characteristics of auditory masking, in both time and frequency domains, provide leverage to identify signal components which are irrelevant to perception and which need not consume coding capacity. This discussion draws a perspective on recent coding advances and points up opportunities for increased sophistication in representing perceptual I y imp0 rtan t factors. It also indicates relations hips between economies gained by perceptual coding alone, and those where source coding can trade on signal-specific characteristics to achieve further reductions in bit rate. It COnChdeS with brief consideration of other sensory modalities, such as the tactile dimension, that might contribute to naturalness and ease of use in interactive multimedia information systems.","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":"129242670","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.1991.634101
J. C. Middlebrooks
When presented with narrowband sound sources, human subjects make characteristic errors in localization that are largely restricted to the vertical dimension. The current study attempts to account for this behavior in terms of the directional characteristics of the head arid external ears. A model is described that effectively predicts the errors in narrowband localization and that can be applied to localization of more general types of sounds.
{"title":"Narrowband Sound Localization Related To Acoustical Cues","authors":"J. C. Middlebrooks","doi":"10.1109/ASPAA.1991.634101","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634101","url":null,"abstract":"When presented with narrowband sound sources, human subjects make characteristic errors in localization that are largely restricted to the vertical dimension. The current study attempts to account for this behavior in terms of the directional characteristics of the head arid external ears. A model is described that effectively predicts the errors in narrowband localization and that can be applied to localization of more general types of sounds.","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":"125705873","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.1991.634150
M. Karjalainen, U. Laine, V. Valimaki
This paper will address the problem of modeling the acoustic guitar for real-time synthesis on signal processairs. We will present a scheme for modeling the string for high-quality sound synthesis when the length of Ihe string is changing dynamically. We will focus also on the problem of modeling the body of the guitar for real-time synthesis. Filter-based approaches were experimented by LPC estimation, IIR-filter synthesis and FIR-filter approximation. Perceptual evaluation was used and taken into account. Real-time synthesis was implemented on the TMS32OC30 floating-point signal processor. The presentation includes audio examples. Introduction Computational modeling of musical instruments is an alternative to commonly used and more straightforward sound synthesis techniques like FA4 synthesis and waveform sampling. The traditional,approach 10 efficient modeling of a vibrating string has been to use proper digital filters or transmission lines, see e.g. Kauplus and Strong [l] and its extensions by Jaffe and Smith [2]. These represent "semiphysical" modeling where only some of the most fundamental features of the string, especially the transmission line property, are retained to achieve efficient computation. More complete finite element models and other kinds of physical modeling may lead to very realistic sounds but tend to be computationally too expensive for real-time purposes. Modeling of the guitar body for real-time sound synthesis seems too difficult unless a digital filter approach to approximate the transfer function is used. The derivation of the detailed transfer function from mechanical and acoustical parameters seems impossible. The remaining choice is to estimate the transfer function filter from measurements of a real guitar or to design a filter that approximates the general properties of the real guiltar body. In addition to strings and body the interactions between them (at least between the strings) should be included. String Modeling The natural way of modeling a guitar string is to describe it as a two-directional transmission or delay line (see Fig. la.) where the vibrational waves travel in both directions, reflecting at both ends. If all losses and other nonidealities are reduced to the reflection filters at the end points the computation of the ideal string is efficient by using two delay lines. The next problem is how to approximate the fractional part of the delay to achieve any (non-integer) length of the delay Wine. Allpass filters [2] are considered as a good solution if the string length is fixed. If the length is dynamically varying, however, it is very difficult to avoid transients and glitches when Ihe integer part of the delay line must change its length. E x c i t a t i d po in t
{"title":"Aspects In Modeling And Real-time Synthesis Of The Acoustic Guitar","authors":"M. Karjalainen, U. Laine, V. Valimaki","doi":"10.1109/ASPAA.1991.634150","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634150","url":null,"abstract":"This paper will address the problem of modeling the acoustic guitar for real-time synthesis on signal processairs. We will present a scheme for modeling the string for high-quality sound synthesis when the length of Ihe string is changing dynamically. We will focus also on the problem of modeling the body of the guitar for real-time synthesis. Filter-based approaches were experimented by LPC estimation, IIR-filter synthesis and FIR-filter approximation. Perceptual evaluation was used and taken into account. Real-time synthesis was implemented on the TMS32OC30 floating-point signal processor. The presentation includes audio examples. Introduction Computational modeling of musical instruments is an alternative to commonly used and more straightforward sound synthesis techniques like FA4 synthesis and waveform sampling. The traditional,approach 10 efficient modeling of a vibrating string has been to use proper digital filters or transmission lines, see e.g. Kauplus and Strong [l] and its extensions by Jaffe and Smith [2]. These represent \"semiphysical\" modeling where only some of the most fundamental features of the string, especially the transmission line property, are retained to achieve efficient computation. More complete finite element models and other kinds of physical modeling may lead to very realistic sounds but tend to be computationally too expensive for real-time purposes. Modeling of the guitar body for real-time sound synthesis seems too difficult unless a digital filter approach to approximate the transfer function is used. The derivation of the detailed transfer function from mechanical and acoustical parameters seems impossible. The remaining choice is to estimate the transfer function filter from measurements of a real guitar or to design a filter that approximates the general properties of the real guiltar body. In addition to strings and body the interactions between them (at least between the strings) should be included. String Modeling The natural way of modeling a guitar string is to describe it as a two-directional transmission or delay line (see Fig. la.) where the vibrational waves travel in both directions, reflecting at both ends. If all losses and other nonidealities are reduced to the reflection filters at the end points the computation of the ideal string is efficient by using two delay lines. The next problem is how to approximate the fractional part of the delay to achieve any (non-integer) length of the delay Wine. Allpass filters [2] are considered as a good solution if the string length is fixed. If the length is dynamically varying, however, it is very difficult to avoid transients and glitches when Ihe integer part of the delay line must change its length. E x c i t a t i d po in t","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":"114638829","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.1991.634140
J. Valière, S. Montrésor, J. Allard, M. Baudry
Digital techniques used for the restoration of old recordings are presented in this paper. Three different flaws can be present in old recordings, these being, harmonic distortion, impulsive noise, and background noise. Only the cancellation of the impulsive noise and the reduction of the background noise are considered. In order to cancel the impulsive noise, the corrupted samples are replaced by interpolated samples. An interpolator that uses the information located near the impulsive noise must be achieved. In this paper, two different methods of interpalation are compared. For the reduction of the background noise, we have used a method worked out by Ephraim and Malah that dces riot crzate musical noise. In order to improve the filtering of transcients, a decomposition of the signal in several frequency channels is beforehand perf ormed.
{"title":"New technics based on the wavelet transform for the restoration of old recordings","authors":"J. Valière, S. Montrésor, J. Allard, M. Baudry","doi":"10.1109/ASPAA.1991.634140","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634140","url":null,"abstract":"Digital techniques used for the restoration of old recordings are presented in this paper. Three different flaws can be present in old recordings, these being, harmonic distortion, impulsive noise, and background noise. Only the cancellation of the impulsive noise and the reduction of the background noise are considered. In order to cancel the impulsive noise, the corrupted samples are replaced by interpolated samples. An interpolator that uses the information located near the impulsive noise must be achieved. In this paper, two different methods of interpalation are compared. For the reduction of the background noise, we have used a method worked out by Ephraim and Malah that dces riot crzate musical noise. In order to improve the filtering of transcients, a decomposition of the signal in several frequency channels is beforehand perf ormed.","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":"128942355","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.1991.634129
S. Lipshitz, R. Wannamaker, J. Vanderkooy, J. N. Wright
A mathematical investigation of quantizing systems using non-subtractive dither is presented. It is shown that with a suitably-chosen dither probability density function (pdf), certain moments of the total error can be made signal-independent and the error signal rendered white, but that statistical independence of the error and the input signal is not achievable. Some of these results are known but appear to be unpublished. The earliest references to many of these results are contained in manuscripts by one of the authors [JNW'] but they were later discovered independently by Stockham and Brinton2i3, Lipshitz and Vanderkooy4, and Gray5. In view of many widespread misunderstandings regarding non-subtractive dither, it seems that formal presentation of these results is long overdue.
{"title":"Non-Subtractive Dither","authors":"S. Lipshitz, R. Wannamaker, J. Vanderkooy, J. N. Wright","doi":"10.1109/ASPAA.1991.634129","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634129","url":null,"abstract":"A mathematical investigation of quantizing systems using non-subtractive dither is presented. It is shown that with a suitably-chosen dither probability density function (pdf), certain moments of the total error can be made signal-independent and the error signal rendered white, but that statistical independence of the error and the input signal is not achievable. Some of these results are known but appear to be unpublished. The earliest references to many of these results are contained in manuscripts by one of the authors [JNW'] but they were later discovered independently by Stockham and Brinton2i3, Lipshitz and Vanderkooy4, and Gray5. In view of many widespread misunderstandings regarding non-subtractive dither, it seems that formal presentation of these results is long overdue.","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":"132766997","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.1991.634100
F. Wightman, D. Kistler
Published data from our laboratory and others suggest that under laboratory conditions human listeners localize virtual sound sources with nearly the same accuracy as they do real sources. The virtual sources in these experiments are digitally synthesized and presented to listeners over headphones. Synthesis of a given virtual source is based on freefield to eardrum acoustical transfer functions ("head-related" transfer functions, or HRTFs) that are measured from both ears of each individual listener. It folllows that synthesis of a virtual auditory space of 265 source locations for each listener requires storage and processing of 530 complex, floating-point HRTFs. If each HRTF is represented by 256 complex spectral values, the total database consists of 271,360 floating-point numbers. Thus, while the perceptual data may argue for the viability of 3-dimensional auditory displays based on the virtual source techniques, the massive data storage and management requirements may impose some practical limitations.
{"title":"Localization of virtual sound sources synthesized from model HRTFs","authors":"F. Wightman, D. Kistler","doi":"10.1109/ASPAA.1991.634100","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634100","url":null,"abstract":"Published data from our laboratory and others suggest that under laboratory conditions human listeners localize virtual sound sources with nearly the same accuracy as they do real sources. The virtual sources in these experiments are digitally synthesized and presented to listeners over headphones. Synthesis of a given virtual source is based on freefield to eardrum acoustical transfer functions (\"head-related\" transfer functions, or HRTFs) that are measured from both ears of each individual listener. It folllows that synthesis of a virtual auditory space of 265 source locations for each listener requires storage and processing of 530 complex, floating-point HRTFs. If each HRTF is represented by 256 complex spectral values, the total database consists of 271,360 floating-point numbers. Thus, while the perceptual data may argue for the viability of 3-dimensional auditory displays based on the virtual source techniques, the massive data storage and management requirements may impose some practical limitations.","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":"130926728","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.1991.634090
R. Patterson, J. Holdsworth, P. Thurston, T. Robinson
Over the past decade, hearing scientists have developed a number of time-domain models of the processing performed by the cochlea in an effort to develop a reasonably accurate multi-channel representation of the pattern of neural activity flowing from the cochlea up the auditory nerve to the cochlear nucleus [l]. It is often assumed that peripheral auditory processing ends at the output of the cochlea and that the pattern of activity in the auditory nerve is in some sense what we hear. In reality, this neural activity pattern (NAP) is not a good representation of our auditory sensations because it includes phase differences that we do riot hear and it does not include auditory temporal integration (TI). As a result, several of the models have been extended to include periodicity-sensitive TI [2], [3], [4] which converts the fast-flowing neural activity pattern into a form that is much more like the auditory images we experience in response to sounds. When these models are applied to speech sounds, the auditory images of vowels reveal an elaborate formant structure that is absent in the more traditional representation of speech -the spectrogram. An example is presented on the left in the figure; it is the auditory image of the stationary part of the vowel /ae/ as in 'bab' [4]. The abscissa of the auditory image is 'temporal integration interval' and each line of the image shows the activity in one frequency channel of the auditory model. In general terms, activity on a vertical line in the auditory image shows that there is a correlation in the sound at that temporal interval. The coincentrations of activity are the formants of the vowel.
{"title":"Auditory Images As Input For Speech Recognition Systems","authors":"R. Patterson, J. Holdsworth, P. Thurston, T. Robinson","doi":"10.1109/ASPAA.1991.634090","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634090","url":null,"abstract":"Over the past decade, hearing scientists have developed a number of time-domain models of the processing performed by the cochlea in an effort to develop a reasonably accurate multi-channel representation of the pattern of neural activity flowing from the cochlea up the auditory nerve to the cochlear nucleus [l]. It is often assumed that peripheral auditory processing ends at the output of the cochlea and that the pattern of activity in the auditory nerve is in some sense what we hear. In reality, this neural activity pattern (NAP) is not a good representation of our auditory sensations because it includes phase differences that we do riot hear and it does not include auditory temporal integration (TI). As a result, several of the models have been extended to include periodicity-sensitive TI [2], [3], [4] which converts the fast-flowing neural activity pattern into a form that is much more like the auditory images we experience in response to sounds. When these models are applied to speech sounds, the auditory images of vowels reveal an elaborate formant structure that is absent in the more traditional representation of speech -the spectrogram. An example is presented on the left in the figure; it is the auditory image of the stationary part of the vowel /ae/ as in 'bab' [4]. The abscissa of the auditory image is 'temporal integration interval' and each line of the image shows the activity in one frequency channel of the auditory model. In general terms, activity on a vertical line in the auditory image shows that there is a correlation in the sound at that temporal interval. The coincentrations of activity are the formants of the vowel.","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":"125117711","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.1991.634115
S. Quackenbush
The paper describes a multi-media database browser based on a AT&T 386/SX PC with a DSP32C coprocessor. Each item in the multi-media database consists of a 512 by 480 pixel color still image and a 20 Hz to 20 kHz monophonic audio signal that can have arbitrary duration. Compressed image and audio signals are stored in a database and are retrieved through a communications channel, decoded using the DSP32C, and displayed and played. The channel could be the PC backplane, a local or wide area network, or a basic rate ISDN telecommunications link. Audio is compressed 6 1 (2.67 bits/sample at 48 lrHz sampling rate) and produces a reconstructed signal that is indistinguishable from the original when heard over a loudspeaker. Image compression is datadependent and ranges from 20:l to 5O:l (1.2 to 0.5 bits per pixel) for reconstructed images with negligible distortion.
{"title":"A CD-Quality Audio and Color Still Image Multi-Media Platform using the DSP32C","authors":"S. Quackenbush","doi":"10.1109/ASPAA.1991.634115","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634115","url":null,"abstract":"The paper describes a multi-media database browser based on a AT&T 386/SX PC with a DSP32C coprocessor. Each item in the multi-media database consists of a 512 by 480 pixel color still image and a 20 Hz to 20 kHz monophonic audio signal that can have arbitrary duration. Compressed image and audio signals are stored in a database and are retrieved through a communications channel, decoded using the DSP32C, and displayed and played. The channel could be the PC backplane, a local or wide area network, or a basic rate ISDN telecommunications link. Audio is compressed 6 1 (2.67 bits/sample at 48 lrHz sampling rate) and produces a reconstructed signal that is indistinguishable from the original when heard over a loudspeaker. Image compression is datadependent and ranges from 20:l to 5O:l (1.2 to 0.5 bits per pixel) for reconstructed images with negligible distortion.","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":"122021790","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.1991.634093
F. Berthommier, J. Schwartz
A B S T R A C 7 We are currently developing a model of auditory processing including several specialized modules connected partly in series, partly in parallel. Signal is first decomposed between frequency channels in the cochlea, and transduced into spike trains which are then directed towards auditory centres where they are processed by neurons with various response characteristics, with either a preference for tonic behavior synchronized on the frequency components of the incident stimulation, or for phasic responses. A number of signal characteristics are exhaustively mapped, such as frequency, amplitude modulation, intensity, interaural delays or timing between acoustic events, and these intermediary representations further converge towards decoding networks. We insist all along this pathway on the necessity to cope with the intrinsic temporal characteristics of the spike trains, and we introduce processing mechanisms based on coincidence computations, which could dcal with both time and space in a natural sa)’.
{"title":"Auditory Processing with spatio-temporal codes","authors":"F. Berthommier, J. Schwartz","doi":"10.1109/ASPAA.1991.634093","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634093","url":null,"abstract":"A B S T R A C 7 We are currently developing a model of auditory processing including several specialized modules connected partly in series, partly in parallel. Signal is first decomposed between frequency channels in the cochlea, and transduced into spike trains which are then directed towards auditory centres where they are processed by neurons with various response characteristics, with either a preference for tonic behavior synchronized on the frequency components of the incident stimulation, or for phasic responses. A number of signal characteristics are exhaustively mapped, such as frequency, amplitude modulation, intensity, interaural delays or timing between acoustic events, and these intermediary representations further converge towards decoding networks. We insist all along this pathway on the necessity to cope with the intrinsic temporal characteristics of the spike trains, and we introduce processing mechanisms based on coincidence computations, which could dcal with both time and space in a natural sa)’.","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":"127750800","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.1991.634119
H. Levitt, T. Schwander, M. Weiss
Noise reduction systems using two or more microphones are generally more effectj-ve than single-microphone systems. Under ideal conditions, an adaptive two-microphone system with one microphone placed at, the noise source can achieve perfect cancellation. For hearing-aid applications it is not usually practical to place a microphone at or near the noise source. It is possible, however, to mount both microphones on the head with a directional microphone facing the noise source and an omnidirectional microphone picking up speech plus noise. In practice, there is continual movement of the head relative to the speech and noise sourc:es which may adversely affect the adaptive cancellation algorithm. Another practical problem is that of room reverberation. A head-mounted two microphone adaptive noise cancellation system was evaluated experimentally in an anechoic chamber and in rooms, with reverberation times of up to 0.6 seconds. Significant improvements in speech intelligibility were obtained with both normal-hearing and hearing-impaired listeners.
{"title":"Adaptive Noise Cancellation for Hearing-Aid Application","authors":"H. Levitt, T. Schwander, M. Weiss","doi":"10.1109/ASPAA.1991.634119","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634119","url":null,"abstract":"Noise reduction systems using two or more microphones are generally more effectj-ve than single-microphone systems. Under ideal conditions, an adaptive two-microphone system with one microphone placed at, the noise source can achieve perfect cancellation. For hearing-aid applications it is not usually practical to place a microphone at or near the noise source. It is possible, however, to mount both microphones on the head with a directional microphone facing the noise source and an omnidirectional microphone picking up speech plus noise. In practice, there is continual movement of the head relative to the speech and noise sourc:es which may adversely affect the adaptive cancellation algorithm. Another practical problem is that of room reverberation. A head-mounted two microphone adaptive noise cancellation system was evaluated experimentally in an anechoic chamber and in rooms, with reverberation times of up to 0.6 seconds. Significant improvements in speech intelligibility were obtained with both normal-hearing and hearing-impaired listeners.","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":"121258435","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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