Pub Date : 1900-01-01DOI: 10.1109/ASPAA.1991.634134
B. Champagne, A. Lobo, P. Kabal
In this paper, we describe two methods for efficiently simulating the response of a microphone to a moving talker in a rectangular room. Both methods are based on an extension of the image method to moving sources. In the first method, the microphone output signal is obtained by performing a time-domain filtering operation on the original speech signal, while in the second method, a timefrequency representation of this filtering operation is used. In each case, computational load and memory requirements are considerably reduced by taking advantage of the fact that the talker velocity is much smaller than the speed of sound.
{"title":"Efficient Methods for Simulating a Moving Talker in a Rectangular Room","authors":"B. Champagne, A. Lobo, P. Kabal","doi":"10.1109/ASPAA.1991.634134","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634134","url":null,"abstract":"In this paper, we describe two methods for efficiently simulating the response of a microphone to a moving talker in a rectangular room. Both methods are based on an extension of the image method to moving sources. In the first method, the microphone output signal is obtained by performing a time-domain filtering operation on the original speech signal, while in the second method, a timefrequency representation of this filtering operation is used. In each case, computational load and memory requirements are considerably reduced by taking advantage of the fact that the talker velocity is much smaller than the speed of sound.","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":"129312967","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.1991.634106
S. Smith
Data "sonification." the representation of da t a in sound. is the auditory counterpart of da ta visualization. '171itle data isualizatioii is a matuiiiig-if not actuall? mature-field, sonification is quite young. It criii 1~~~ h a i d i o l i ( ~ e beguii i i t l i B1h ' 5 pioneeiing 1982 stud). Because tlie field 1s $0 nen , sonification li,is not >et eitahli5lietl i t . slur as tool for exploring and understanding data; inoleover. sonification f,lcc> t i i f f i ( l i l t ol)5tCic lei to i t> toritiniied eiJolution. These obstacles are the focus of this presentation.
数据“声音化”:数据在声音中的表现。是数据可视化的听觉对应物。“小数据可视化是一种成熟——如果不是实际上的话?”成熟领域的超声技术相当年轻。criii 1 h ~ ~ ~我d l o (t l ~ e beguii 我我B1h 1982 pioneeiing螺栓)。因为这个领域的15美元的新，声波li，并不是> >在它上面的10美元。slur作为探索和理解数据的工具;inoleover。f, lcc > t我我f f (l i l t ol) 5 tcic lei我t > toritiniied eiJolution。这些障碍是本次演讲的重点。
{"title":"Data sonification: issues and challenges","authors":"S. Smith","doi":"10.1109/ASPAA.1991.634106","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634106","url":null,"abstract":"Data \"sonification.\" the representation of da t a in sound. is the auditory counterpart of da ta visualization. '171itle data isualizatioii is a matuiiiig-if not actuall? mature-field, sonification is quite young. It criii 1~~~ h a i d i o l i ( ~ e beguii i i t l i B1h ' 5 pioneeiing 1982 stud). Because tlie field 1s $0 nen , sonification li,is not >et eitahli5lietl i t . slur as tool for exploring and understanding data; inoleover. sonification f,lcc> t i i f f i ( l i l t ol)5tCic lei to i t> toritiniied eiJolution. These obstacles are the focus of this presentation.","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":"114262117","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.1991.634144
L. Eriksson, M. Allie
Adaptive filters are an attractive approach for control of an active attenuation system due to their ability t o adapt t o changes in the acoustical system or noise source. One approach, based on the filtered-X algorithm, uses a finite impulse response (FIR) filter structure with coefficients that are adapted using the least mean squares (LMS) algorithm [ll. The filtered-U algorithm features an infinite impulse response (IIR) filter structure and uses the recursive least mean squares (RLMS) adaptive algorithm [21. Both algorithms require knowledge of auxiliary path transfer functions following the adaptive filter to ensure proper convergence of the algorithm. One approach to obtaining these transfer functions has been previously described by the authors and uses an independent random noise source, as shown in Fig. 1, for the filtered-U algorithm [31. This presentation will explore the use of an alternative approach to auxiliary path modeling that does not require an additional noise source. This approach utilizes an overall system model, Q, and auxiliary path model, T, and is known as the Q-T modeling algorithm [2,4]. As shown in Fig. 2, two error signals are combined in this approach to form an overall error signal, ET(z), that is used t o adapt Q(z) and T(z): where the residual acoustic noise, and the difference of the outputs of models Q and T, EJz) = E(i<)-E(z) (1) The model, M(z), adapts to minimize E(z) while Q(z) and T(z) adapt to minimize E,Cz). The model, M(z), may use either a finite impulse response (FIR) filter structure or an infinite impulse response (IIR) filter structure. The supplementary models, Q(z) and T(z), could also use either an FIR or IIR model structure. Adaptation can be done using the LMS o r RLMS algorithms for the FIR or IIR structures, respectively. The error signal, E(z), goes t o zero for an IIW model formed from A(z) and B(z) when: M(z) = P(z)/[H(z)(l-P(~)F(z))l = A(z)/[l-B(z)] (4) where P(z> is the direct plant, F(z) is the feedback plant, and H(z) is the auxiliary path transfer function. In general, there are many possible solutions for A(z) and B(z) for various physical parameters. The overall error signal, ET(z), goes to zero and the residual noise is minimized when: E(z) = E'(z) = 0 (5) which requires $!(z)~(z) = M(z) = P(z)/[H(z)(l-P(~)F(z))l (6) and there are again many solutions for Q(z) and T(z) for various physical parameters. However, T(z) is also used …
{"title":"Active Attenuation With Overall System Modeling","authors":"L. Eriksson, M. Allie","doi":"10.1109/ASPAA.1991.634144","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634144","url":null,"abstract":"Adaptive filters are an attractive approach for control of an active attenuation system due to their ability t o adapt t o changes in the acoustical system or noise source. One approach, based on the filtered-X algorithm, uses a finite impulse response (FIR) filter structure with coefficients that are adapted using the least mean squares (LMS) algorithm [ll. The filtered-U algorithm features an infinite impulse response (IIR) filter structure and uses the recursive least mean squares (RLMS) adaptive algorithm [21. Both algorithms require knowledge of auxiliary path transfer functions following the adaptive filter to ensure proper convergence of the algorithm. One approach to obtaining these transfer functions has been previously described by the authors and uses an independent random noise source, as shown in Fig. 1, for the filtered-U algorithm [31. This presentation will explore the use of an alternative approach to auxiliary path modeling that does not require an additional noise source. This approach utilizes an overall system model, Q, and auxiliary path model, T, and is known as the Q-T modeling algorithm [2,4]. As shown in Fig. 2, two error signals are combined in this approach to form an overall error signal, ET(z), that is used t o adapt Q(z) and T(z): where the residual acoustic noise, and the difference of the outputs of models Q and T, EJz) = E(i<)-E(z) (1) The model, M(z), adapts to minimize E(z) while Q(z) and T(z) adapt to minimize E,Cz). The model, M(z), may use either a finite impulse response (FIR) filter structure or an infinite impulse response (IIR) filter structure. The supplementary models, Q(z) and T(z), could also use either an FIR or IIR model structure. Adaptation can be done using the LMS o r RLMS algorithms for the FIR or IIR structures, respectively. The error signal, E(z), goes t o zero for an IIW model formed from A(z) and B(z) when: M(z) = P(z)/[H(z)(l-P(~)F(z))l = A(z)/[l-B(z)] (4) where P(z> is the direct plant, F(z) is the feedback plant, and H(z) is the auxiliary path transfer function. In general, there are many possible solutions for A(z) and B(z) for various physical parameters. The overall error signal, ET(z), goes to zero and the residual noise is minimized when: E(z) = E'(z) = 0 (5) which requires $!(z)~(z) = M(z) = P(z)/[H(z)(l-P(~)F(z))l (6) and there are again many solutions for Q(z) and T(z) for various physical parameters. However, T(z) is also used …","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":"129437537","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.1991.634153
M. Puckette, E. Lindemann, C. Lippe
This is a project begun in August 19SS involving eight to ten engineers. The intention is to provide a system which is n-ell adapted to both real-time signal processing and event processing. The system uses the NeXT machine as host computer. We have developed a high-speed general purpose multiprocessor configured as plugin boards for the NeXT cube. The board, designed at IRCAM, uses two Intel i860 processors for number crunching and a 560001 for I/O. Three boards can be plugged into a NeXT cube for a total of 6 i860's.
{"title":"A Demonstration of The Ircam Signal Processing Workstation","authors":"M. Puckette, E. Lindemann, C. Lippe","doi":"10.1109/ASPAA.1991.634153","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634153","url":null,"abstract":"This is a project begun in August 19SS involving eight to ten engineers. The intention is to provide a system which is n-ell adapted to both real-time signal processing and event processing. The system uses the NeXT machine as host computer. We have developed a high-speed general purpose multiprocessor configured as plugin boards for the NeXT cube. The board, designed at IRCAM, uses two Intel i860 processors for number crunching and a 560001 for I/O. Three boards can be plugged into a NeXT cube for a total of 6 i860's.","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":"133581246","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.1991.634112
M. Bosi, G. Davidson, L. Fielder
An adaptive block size transform coder for high quality music has been developed. The adaptability of the input size of the transform combined with the properties of the transform as developed in the Dolby AC-2 technology allows one to exploit both maximum time and frequency resolution while keeping the bit rate as low as 128 kb/s per channel. The low complexity of the system permits a real-time implementation of encoder or decoder using one general purpose, programmable DSP chip per channel pair.
{"title":"Time versus Frequency Resolution in a Low-Rate, High Quality Audio Transform Coder","authors":"M. Bosi, G. Davidson, L. Fielder","doi":"10.1109/ASPAA.1991.634112","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634112","url":null,"abstract":"An adaptive block size transform coder for high quality music has been developed. The adaptability of the input size of the transform combined with the properties of the transform as developed in the Dolby AC-2 technology allows one to exploit both maximum time and frequency resolution while keeping the bit rate as low as 128 kb/s per channel. The low complexity of the system permits a real-time implementation of encoder or decoder using one general purpose, programmable DSP chip per channel pair.","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":"132355655","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.1991.634118
B.D. Wwdruff, D. Preves, T. Fortune
Traditionally, the goal of a hearing aid fitting is to bring the acoustic level of speech above the hearing threshold of the impaired ear. Linear amplification is usually sufficient to bring the overall level of speech above threshold. Unfortunately, the information-bearing;, but low level, high frequency spectral components of speech often do not receive sufficient amplification from linear hearing aids to ensure their audibility.
{"title":"Adaptive High Pass Filtering with Expansion","authors":"B.D. Wwdruff, D. Preves, T. Fortune","doi":"10.1109/ASPAA.1991.634118","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634118","url":null,"abstract":"Traditionally, the goal of a hearing aid fitting is to bring the acoustic level of speech above the hearing threshold of the impaired ear. Linear amplification is usually sufficient to bring the overall level of speech above threshold. Unfortunately, the information-bearing;, but low level, high frequency spectral components of speech often do not receive sufficient amplification from linear hearing aids to ensure their audibility.","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":"128423787","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.1991.634091
T. Hirahara
Introduction It has been expected that speech recognition performance can be improved by replacing a traditional front-end with a model of the auditory periphery. The underlying assumption is that if a model could be designed properly, it should generate a more efficient representation compared to traditional physical spectrum representations. From this viewpoint, several works have been reported [11-[41. However, these studies do not always show an auditory front-end to be superior to a traditional front-end. Some auditory front-ends are superior only for noisy speech, but many show little, if any, superiority in processing clean speech. We also have been developing an auditory model characterized by an adaptive Q cochlear filter not only for the front-end of a speech recognition system but also for a general purpose spectral1 analyzer in speech research [SI. In this paper, several auditory front-ends based on the adaptive Q cochlear filter and its relatives are tested in speaker dependent phoneme recognition using different stochastic pattern classifier!;, a shift invariant multi template matching system using LVQ2-trained codebook, and a VQ-HMM system. Further, we will discuss problems of using an auditory model as a frontend of an automatic speech recognition system. 2. Adaptive Q Cochlear Filter An adaptive Q cochlear filter (AQF) is a computational filter that functionally simulates the nonlinear filtering characteristics of the basilar membrane vibrating system. The AQF consists of three parts: (1) cascaded second-order notch filters (NOTCH), (2) second-order band pass filters (BPF) connected to each NOTCH output, and (3) adaptive Q circuits connected to each BPF output. The adaptive Q circuit consists of a second-order low-pass filter (LPF) in
{"title":"An Adaptive Q Cochlear Filter in Phoneme Recognition","authors":"T. Hirahara","doi":"10.1109/ASPAA.1991.634091","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634091","url":null,"abstract":"Introduction It has been expected that speech recognition performance can be improved by replacing a traditional front-end with a model of the auditory periphery. The underlying assumption is that if a model could be designed properly, it should generate a more efficient representation compared to traditional physical spectrum representations. From this viewpoint, several works have been reported [11-[41. However, these studies do not always show an auditory front-end to be superior to a traditional front-end. Some auditory front-ends are superior only for noisy speech, but many show little, if any, superiority in processing clean speech. We also have been developing an auditory model characterized by an adaptive Q cochlear filter not only for the front-end of a speech recognition system but also for a general purpose spectral1 analyzer in speech research [SI. In this paper, several auditory front-ends based on the adaptive Q cochlear filter and its relatives are tested in speaker dependent phoneme recognition using different stochastic pattern classifier!;, a shift invariant multi template matching system using LVQ2-trained codebook, and a VQ-HMM system. Further, we will discuss problems of using an auditory model as a frontend of an automatic speech recognition system. 2. Adaptive Q Cochlear Filter An adaptive Q cochlear filter (AQF) is a computational filter that functionally simulates the nonlinear filtering characteristics of the basilar membrane vibrating system. The AQF consists of three parts: (1) cascaded second-order notch filters (NOTCH), (2) second-order band pass filters (BPF) connected to each NOTCH output, and (3) adaptive Q circuits connected to each BPF output. The adaptive Q circuit consists of a second-order low-pass filter (LPF) in","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":"130300520","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.1991.634099
N. Xiang, K. Genuit
A normal listening situation in a room involes, at least, a listener who has a pair of functioning ears. The emphasis does lie on the word ears because our auditory system can be referred to as a final receiver in this listening situation, while the human external-ear can be observed as an antenna of acoustic signals in the sense of telecomunication. Generally speaking, a listening situation in a room usually contains one or several sound source(s). In the perspective of system theory, such a situation may be modelled by a transmission system between the inputs of sound sources and the outputs of receivers. This acoustic environment can often be described, particularly for one listener, by a linear time-invariant system with two outputs and probably several inputs (FigJ), if the source(s) and the receiver are not moving. Define an impulse response hi, between each input and each output, the relation between the output signals E, and the input signals Ij of the system can therefore be presented by the following equation:
{"title":"Modelling of Binaural Listening Situation and Its Realization by Using Tenth Scaled-Down Modelling-Technique","authors":"N. Xiang, K. Genuit","doi":"10.1109/ASPAA.1991.634099","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634099","url":null,"abstract":"A normal listening situation in a room involes, at least, a listener who has a pair of functioning ears. The emphasis does lie on the word ears because our auditory system can be referred to as a final receiver in this listening situation, while the human external-ear can be observed as an antenna of acoustic signals in the sense of telecomunication. Generally speaking, a listening situation in a room usually contains one or several sound source(s). In the perspective of system theory, such a situation may be modelled by a transmission system between the inputs of sound sources and the outputs of receivers. This acoustic environment can often be described, particularly for one listener, by a linear time-invariant system with two outputs and probably several inputs (FigJ), if the source(s) and the receiver are not moving. Define an impulse response hi, between each input and each output, the relation between the output signals E, and the input signals Ij of the system can therefore be presented by the following equation:","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":"130024685","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.1991.634103
J. Jullien, O. Warusfel
Background For telecommunication services such as teleconferencing or visioconferencing, the true restitution of sound environment, through a complete transmission system, has become a new goal. The aim now encompasses the presentation of the localization of distant speakers as well as other aspects of the distant sound ambiance such as the room effect which contains auditive infoxmations about its size and the positions of the speakers within the room. This extended version of sound transmission fidelity will become a necessity when will be available sophisticated syste:ms for image transmission, now under project, offering high definition, large screen and stereo vision. At present, the applications of what is often called "virtual acousiics" are found primarily in the musical domain. One goal is to allow an auditor tio listen just as if he were in the hall during the performance although he listens through a complete system including performance recording and replaying or transmission. An other application for contemporary music is to achieve sound diffusion of digitally transformed signals of natural sources, previously recorded or synthesized with loudspeakers.
{"title":"Study of the perceptive variations of room effect for different systems of sound recording and replaying","authors":"J. Jullien, O. Warusfel","doi":"10.1109/ASPAA.1991.634103","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634103","url":null,"abstract":"Background For telecommunication services such as teleconferencing or visioconferencing, the true restitution of sound environment, through a complete transmission system, has become a new goal. The aim now encompasses the presentation of the localization of distant speakers as well as other aspects of the distant sound ambiance such as the room effect which contains auditive infoxmations about its size and the positions of the speakers within the room. This extended version of sound transmission fidelity will become a necessity when will be available sophisticated syste:ms for image transmission, now under project, offering high definition, large screen and stereo vision. At present, the applications of what is often called \"virtual acousiics\" are found primarily in the musical domain. One goal is to allow an auditor tio listen just as if he were in the hall during the performance although he listens through a complete system including performance recording and replaying or transmission. An other application for contemporary music is to achieve sound diffusion of digitally transformed signals of natural sources, previously recorded or synthesized with loudspeakers.","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":"122833614","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.1991.634141
O. Cappé, A. Chaigne
Restoration of audio recordings degraded by surface noise can be viewed as an analysWsynthesis procedure where the modulus of the Fouriex transform is replaced by an estimator before resynthesis. The goal is usually to find the best possible estimator in terms of noise power reduction. In current restoration procedures there are no modifications of the phase specuum, because most authors consider that the phase is perceptually irrelevant [l]. Therefore the prime objective of the work presented here was to check the validity of these assumptions, and put some emphasis on the degradation of the phase. For that purpose, an analysis/synthesis procedure simulating a restoration p m s has been carried out on artificially degraded signals. An overview of this procedure can be Seen in Fig. 1. addibve noise phase Original signal-EK""'"' phase Fig. 1 Simulation of a restoration process based on Short-Time-Fourier-Transform, with perfect modulus recovering and degraded phase. In these later experiments, the restored signal is obtained from the modulus of the original signal and from the phase of the degraded signal. Thus the estimator of the modulus is equivalent to the one which would be obtained through "perfect" cancellation of the noise. As a consequence, the remaining degradation of the restored signal is only due to the influence of the additive noise in the phase spectrum. The first goal of the work is to calculate an estimator for the phase deviation in the restored signal, which depends on both the noise characteristics and the parameters of the analysis/synthesis plocedure. The results are then compared with psychoacoustical data related to the perception of modulations. This comparison is aimed at providing an appropriate selection for the STFT parameters. Following Vary [2]. the noise component is assumed to be gaussian. For a sine wave of frequency fo = p Fe / N, where Fe is the sampling frequency and N the size of the window, it can be shown that the expectation for the maximum phase deviation at fo is given by
被表面噪声退化的录音的恢复可以看作是一个分析合成过程，在重新合成之前，傅里叶变换的模量被一个估计量取代。目标通常是在降低噪声功率方面找到最好的估计器。在目前的恢复过程中，相位谱没有变化，因为大多数作者认为相位在感知上是不相关的[1]。因此，这里提出的工作的主要目标是检查这些假设的有效性，并把一些重点放在阶段的退化上。为此，对人为退化的信号进行了模拟恢复过程的分析/合成过程。这个过程的概述可以在图1中看到。图1基于短时傅立叶变换的模量完全恢复、相位退化的恢复过程仿真。在这些后期的实验中，从原始信号的模量和退化信号的相位中获得恢复信号。因此，模量的估计量等于通过“完全”消除噪声而得到的估计量。因此，恢复信号的剩余退化仅是由于相位谱中加性噪声的影响。这项工作的第一个目标是计算恢复信号中相位偏差的估计量，这取决于噪声特性和分析/合成过程的参数。然后将结果与与调制感知相关的心理声学数据进行比较。这种比较的目的是为STFT参数提供一个适当的选择。Following Vary[2]。假设噪声分量是高斯的。对于频率为fo = p Fe / N的正弦波，其中Fe为采样频率，N为窗口大小，可以表明，在fo处最大相位偏差的期望为
{"title":"Perceptual Effects Of Noise Disturbances On Phase Spectrum In Stft Analysis/synthesis Procedures. Application To Restoration Processes","authors":"O. Cappé, A. Chaigne","doi":"10.1109/ASPAA.1991.634141","DOIUrl":"https://doi.org/10.1109/ASPAA.1991.634141","url":null,"abstract":"Restoration of audio recordings degraded by surface noise can be viewed as an analysWsynthesis procedure where the modulus of the Fouriex transform is replaced by an estimator before resynthesis. The goal is usually to find the best possible estimator in terms of noise power reduction. In current restoration procedures there are no modifications of the phase specuum, because most authors consider that the phase is perceptually irrelevant [l]. Therefore the prime objective of the work presented here was to check the validity of these assumptions, and put some emphasis on the degradation of the phase. For that purpose, an analysis/synthesis procedure simulating a restoration p m s has been carried out on artificially degraded signals. An overview of this procedure can be Seen in Fig. 1. addibve noise phase Original signal-EK\"\"'\"' phase Fig. 1 Simulation of a restoration process based on Short-Time-Fourier-Transform, with perfect modulus recovering and degraded phase. In these later experiments, the restored signal is obtained from the modulus of the original signal and from the phase of the degraded signal. Thus the estimator of the modulus is equivalent to the one which would be obtained through \"perfect\" cancellation of the noise. As a consequence, the remaining degradation of the restored signal is only due to the influence of the additive noise in the phase spectrum. The first goal of the work is to calculate an estimator for the phase deviation in the restored signal, which depends on both the noise characteristics and the parameters of the analysis/synthesis plocedure. The results are then compared with psychoacoustical data related to the perception of modulations. This comparison is aimed at providing an appropriate selection for the STFT parameters. Following Vary [2]. the noise component is assumed to be gaussian. For a sine wave of frequency fo = p Fe / N, where Fe is the sampling frequency and N the size of the window, it can be shown that the expectation for the maximum phase deviation at fo is given by","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":"122543648","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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