Abstract:
The present invention provides a system and method encompassing a new metric and MATLAB tool box that phone makers may use to improve the design of the secondary path, in order to improve ANC performance. The metric measures how invertible the secondary path is and then evaluates ANC performance at a worst case scenario where P(z)=1 and W(z) becomes a complete predictor. The invention can be easily extended to a multi-channel ANC system.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     The present application claims priority from Provisional U.S. Patent Application No. 61/815,281 filed on Apr. 24, 2013, and incorporated herein by reference. 
    
    
     FIELD OF THE INVENTION 
     The present invention relates to the field of Adaptive Noise Cancellation (ANC) systems. In particular, the present invention is directed toward a metric and tool to evaluate secondary path design in adaptive noise cancellation systems to improve performance of adaptive noise cancellation systems. 
     BACKGROUND OF THE INVENTION 
     A personal audio device, such as a wireless telephone, includes an adaptive noise canceling (ANC) circuit that adaptively generates an anti-noise signal from a reference microphone signal and injects the anti-noise signal into the speaker or other transducer output to cause cancellation of ambient audio sounds. An error microphone is also provided proximate the speaker to measure the ambient sounds and transducer output near the transducer, thus providing an indication of the effectiveness of the noise canceling. A processing circuit uses the reference and/or error microphone, optionally along with a microphone provided for capturing near-end speech, to determine whether the ANC circuit is incorrectly adapting or may incorrectly adapt to the instant acoustic environment and/or whether the anti-noise signal may be incorrect and/or disruptive and then take action in the processing circuit to prevent or remedy such conditions. 
     Examples of such Adaptive Noise Cancellation systems are disclosed in published U.S. Patent Application 2012/0140943, published on Jun. 7, 2012, and also in Published U.S. Patent Application 2012/0207317, published on Aug. 16, 2012, both of which are incorporated herein by reference. Both of these references are assigned to the same assignee as the present application and name at least one inventor in common and thus are not “Prior Art” to the present application, but are discussed herein to facilitate the understating of ANC circuits as applied in the field of use. 
     Referring now to  FIG. 1 , a wireless telephone  10  is illustrated in proximity to a human ear  5 , or more specifically the pinna of a human ear. The pinna is the part of the human ear that extends from the head, and varies in shape and size between various individuals. As a result, the acoustical characteristics of a wireless telephone and the human ear will vary from person to person, based on the shape and size of their pinna  5 . Moreover, how closely wireless telephone  10  is held to the pinna  5  will vary the acoustical characteristics and thus affect noise cancellation. For this reason as well as others, adaptive noise cancellation techniques are used to adaptively cancel background noise in a manner that is responsive to changes in the acoustical path between wireless phone  10  and pinna  5 . 
     Wireless telephone  10  includes a transducer, such as speaker SPKR that reproduces distant speech received by wireless telephone  10 , along with other local audio events such as ring tones, stored audio program material, injection of near-end speech (i.e., the speech of the user of wireless telephone  10 ) to provide a balanced conversational perception, and other audio that requires reproduction by wireless telephone  10 , such as sources from web-pages or other network communications received by wireless telephone  10  and audio indications such as battery low and other system event notifications. A near-speech microphone NS is provided to capture near-end speech, which is transmitted from wireless telephone  10  to the other conversation participant(s). 
     Wireless telephone  10  includes adaptive noise canceling (ANC) circuits and features that inject an anti-noise signal into speaker SPKR to improve intelligibility of the distant speech and other audio reproduced by speaker SPKR. A reference microphone R is provided for measuring the ambient acoustic environment, and is positioned away from the typical position of a user&#39;s mouth, so that the near-end speech is minimized in the signal produced by reference microphone R. A third microphone, error microphone E, is provided in order to further improve the ANC operation by providing a measure of the ambient audio combined with the audio reproduced by speaker SPKR close to ear pinna  5 , when wireless telephone  10  is in close proximity to ear pinna  5 . Exemplary circuit  14  within wireless telephone  10  includes an audio CODEC integrated circuit  20  that receives the signals from reference microphone R, near speech microphone NS and error microphone E and interfaces with other integrated circuits such as an RF integrated circuit  12  containing the wireless telephone transceiver. CODEC  20  may incorporate ANC circuitry to provide adaptive noise cancellation. 
     In general, ANC techniques measure ambient acoustic events (as opposed to the output of speaker SPKR and/or the near-end speech) impinging on reference microphone R, and also measures the same ambient acoustic events impinging on error microphone E. The ANC processing circuits of illustrated wireless telephone  10  adapt an anti-noise signal generated from the output of reference microphone R to have a characteristic that minimizes the amplitude of the ambient acoustic events at error microphone E. 
     Since acoustic path P(z) (also referred to as the Passive Forward Path) extends from reference microphone R to error microphone E, the ANC circuits are essentially estimating acoustic path P(z) combined with removing effects of an electro-acoustic path S(z) (also referred to as Secondary Path) that represents the response of the audio output circuits of CODEC IC  20  and the acoustic/electric transfer function of speaker SPKR including the coupling between speaker SPKR and error microphone E in the particular acoustic environment, which is affected by the proximity and structure of ear pinna  5  and other physical objects and human head structures that may be in proximity to wireless telephone  10 , by the proximity and structure of ear pinna  5  and other physical objects and human head structures that may be in proximity to wireless telephone  10 , and how firm the wireless telephone is pressed to ear pinna  5 . 
       FIG. 2  is a block diagram illustrating the relationship between the elements of a type of ANC circuit known as Feed Forward ANC. The various types of ANC circuits (Feed-Forward, Feedback, and Hybrid) are described in more detail in the paper entitled  On maximum achievable noise reduction in ANC systems , by A. A. Milani, G. Kannan, and I. M. S. Panahi, in Proc. ICASSP, 2010, pp. 349-352, published on March 2010 and incorporated herein by reference. The diagram of  FIG. 2  is not an electrical block diagram, but rather illustrates the relationship of electrical, mechanical, and acoustical components in the overall system as shown in  FIG. 1 . 
     Input to the device is from reference microphone R, which outputs signal x(n) which represent the source of acoustic noise recorded by the reference microphone. The transfer function between the reference and error microphones is known as the Primary path P(z) or the passive forward path between error microphone E and the reference microphone R. Primary Path P(z) is represented in block  210 . The noise signal after passing through P(z) is called d(n) which also represents the auto output received by error microphone E. 
     Secondary path S(z) is represented by block  230  and represents the transfer function of the electrical path, including the microphones E, R, and NS, digital circuitry (of  FIG. 1 ), and canceling loudspeaker SPKR (of  FIG. 1 ) plus the acoustical path between the loudspeaker SPKR (of  FIG. 1 ) and the error microphone E. The input signal x(n) is fed to anti-noise filter  260  which has a transfer function W(z). The output y(n) from anti-noise filter  260  is then passed to adder  245 , where it is added to a training signal (generally white noise) from Personal Entertainment System  290  (e.g., cellphone, pad device, or the like) and, after being inverted by inverter  255  (so as to subtract the resultant anti-noise signal) is input to secondary path transfer function  230 . The output of this secondary path is added in adder  220  and the resultant signal e(n) is output to error microphone E via speaker SPKR (not shown). 
     SE(z) in block  280  represents an estimate of S(z). Due to the delay characteristics of the primary and secondary paths P(z), S(z), the feed-forward system of  FIG. 2  may include an estimator to predict future noise and compensate for the delay characteristics in the overall system. Output signal e(n) is fed to adder  225  having an output that is inverted in inverter  235  and fed to least means square filter  250  which in turn generates a predicted S(z) filter value SE(z) in block  240 . The output of block  240  in turn is fed into adder  225  in a feedback loop, so that this filter value is updated over time. 
     Predictive filter SE(z), that is shown as block  280 , then accepts the input x(n) and uses the output through Least Means Squared filter  270  to create anti-noise filter value W(z) for anti-noise filter  260   
     The transfer function between the reference and error microphones is known as the Primary path P(z) or the passive forward path between error microphone E and the reference microphone R. The noise signal after passing through P(z) is called d(n). 
     Block  230  represents transfer function S(z) or the secondary path, which comprises the combined transfer functions of (a) a D/A converter, (b) a power amplifier, (c) speaker SPKR, (d) the air gap between speaker SPKR and error microphone E, (e) error microphone E itself, (f) an A/D converter, and (g) the physical structure of the audio device. 
     The ANC includes an adaptive filter (not shown) which receives reference microphone signal x(n), and under ideal circumstances, adapts its transfer function W(z) to be a ration of the primary path and secondary path (e.g., P(z)/S(z)) to generate the anti-noise signal. The coefficients of the adaptive filter  260  are controlled by a W(z) coefficient control block  260  that uses a correlation of two signals to determine the response of the adaptive filter, which generally minimizes, in a least-mean squares sense, those components of reference microphone signal x(n) that are present in error microphone signal. 
     The signals provided as inputs to LMS block  270  are the reference microphone signal x(n) as shaped by a copy of an estimate of the response of path S(z) provided by filter  280  and another signal provided from the output of a combiner  225  that includes the error microphone signal. By transforming reference microphone signal x(n) with a copy of the estimate of the response of path S(z),SE(z), and minimizing the portion of the error signal that correlates with components of reference microphone signal ref, adaptive filter  32  adapts to the desired response of P(z)/S(z). 
     One problem encountered in designing an adaptive noise cancellation system for a cellular telephone or other device is that the performance of an ANC system is very much dependent on the secondary path structure S(z). The secondary path contains the transfer functions of the D/A converter(s) and power amplifiers within integrated circuit  14 , as well as the speaker, the air gap between the speaker and error microphone, the error microphone, A/D converter(s) within the integrated circuit  14 , as well as the physical structure of the wireless telephone  10  itself. 
     Thus, in the prior art, a phone designer (or designer of other audio device) might place microphones and the speaker on the device based on aesthetic design criteria, or based on assumptions as to what would be a good location for a microphone or speaker. Only by building a testing model of the device could the designer evaluate the microphone and speaker placements. At that stage, it may be difficult to change the design if the microphone and speaker placements are found to be less than optimal. Moreover, testing each microphone and speaker combination and placement may be time consuming, particularly in terms of data acquisition and processing. Comparing different combinations of microphones and speakers and their placement, as well as phone case design and other secondary path variables may be difficult, as some combinations may provide superior performance in one frequency range, while others may provide better performance in other frequency ranges. 
     The inherent delay in the non-minimum phase S(z) is the major bottleneck which forces W(z) to be a predictor. This delay is mainly produced by the speaker transfer function and the air gap which corresponds to the relative placement of the speaker SPKR and the error microphone E. As a result, some of the zeros of S(z) fall outside the unit circle and make S(z) non-invertible. As transfer function W(z) is causal, if there is more delay, then the worse the performance of ANC system becomes. The physical structure and design of the audio system alter the transfer function S(z). There is no single metric that ANC designers and phone makers can use to evaluate the secondary path design (i.e., selection and placement of speaker and microphones, as well as the physical structure and design of the audio device). 
     Thus, it remains a requirement in the art to provide a metric and tool to evaluate secondary path design in an adaptive noise cancellation system, to allow designers to improve the design of such audio devices, and compare different designs more easily. 
     SUMMARY OF THE INVENTION 
     The present invention provides a system and method encompassing a new metric and MATLAB toolbox that phone makers may use to improve the design of the secondary path, in order to improve ANC performance. The metric measures how invertible the secondary path is and then evaluates ANC performance at a worst-case scenario where P(z)=1 and W(z) becomes a complete predictor. The invention can be easily extended to a multi-channel ANC system. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an illustration of a wireless telephone  10  in accordance with an embodiment of the present invention. 
         FIG. 2  is a block diagram illustrating the electrical, acoustical, and physical relationships between the elements of a type of ANC circuit known as Feed Forward ANC. 
         FIG. 3  is a simplified block diagram illustrating how the noise reduction metric is measured. 
         FIG. 4A  is a graph illustrating the secondary path response. 
         FIG. 4B  is a graph illustrating the inverse of the secondary path transfer function S(z). 
         FIG. 5A  is a graph illustrating the frequency response of the secondary path transfer function S (z) and its inverse. 
         FIG. 5B  is a graph illustrating the phase response of the secondary path transfer function S(z) and its inverse. 
         FIG. 6  is s a graph illustrating the amount of cancellation achieved using the inverse of the secondary path transfer function. 
         FIG. 7  is a block diagram illustrating how the quality factor metric is calculated. 
         FIG. 8  is a graph illustrating the frequency response of the secondary path transfer function to a particular portable device, and the resultant quality factor. 
         FIG. 9  is a graph illustrating noise cancellation gain versus quality factor for a number of different portable devices, illustrating the linear relationship between noise cancellation gain and quality factor. 
         FIG. 10  is a side view of the pinna test dummy used to test a cell phone to evaluate secondary path design. 
         FIG. 11  is an applications test board used in evaluating an adaptive noise reduction system in conjunction with the pinna test dummy of  FIG. 9 . 
         FIG. 12  is a simplified block diagram of the test system as assembled, showing the pinna test dummy, applications test board, and computer system displaying the secondary path evaluation metric. 
         FIG. 13  is a screen shot of the display in the computer  1000  of  FIG. 11 , illustrating the displayed metric and other data relating to secondary path evaluation. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       FIG. 3  is a simplified block diagram of the design metric of the present invention, where W(z) represents the transfer function of the noise reduction filter and S(z) represents the secondary path transfer function. Signal x(n) represents the noise signal to be cancelled, while e(n) represents the error signal, or difference between the noise signal and the anti-noise coming out of transfer function S(z). When the error e(n)=0 (in an ideal filter), transfer function W(z) then becomes the causal inverse of the transfer function S(z). The amount of noise reduction between 100 Hz-3 kHz is then measured as the metric of invertibility. 
     A Causal Wiener solution can be calculated as the Least Means Squared (LMS) filter moves toward W 0  as the optimal causal Wiener solution, according to equation (1) below, where Ambient noise Power Spectral Density (PSD) is determined by equation (2) and S(z) is determined by equation (3): 
                     w   o     =       1         S   MP     ⁡     (   z   )       ·       Γ   x     ⁡     (   z   )           ⁢       {         P   ⁡     (   z   )       ·       Γ   x     ⁡     (   z   )             S   AP     ⁡     (   z   )         }     +               (   1   )               Γ xx ( z )Γ x ( z )·Γ x ( z   −1 )=  (2)
 
 S ( z )= S   MP ( z )· S   AP ( z )  (3)
 
where S MP (Z) is the minimum phase factor, S AP (z) is the all pass factor and Γ xx (z) is the power spectral density. From these equations, it is determined that S AP (z) is the non-minimum phase, and thus has zeros outside the unit circle and has a delay.
 
     The inherent delay in the non-minimum phase S(z) is the major bottleneck which forces transfer function W(z) to be a predictor. This delay is mainly produced by the speaker transfer function and the air gap which corresponds to the relative placement of the speaker SPKR and the error microphone E. As a result, some of the zeros of the transfer function S(z) fall outside the unit circle and make S(z) non-invertible. As transfer function W(z) is causal, if more delay exists in the transfer function S(z) then the worse the performance of ANC system becomes. In the prior art, there is no single metric that ANC designers (phone makers) can use to evaluate a secondary path design, such as selection and placement of speaker and microphones, and altering physical structure and design of audio device. 
       FIG. 4A  is a graph illustrating the secondary path response S(z), and  FIG. 4B  is a graph illustrating the inverse of the secondary path transfer function S(z), both of which are in the sample domain.  FIG. 5A  is a graph illustrating the frequency response of the secondary path transfer function S(z) and its inverse.  FIG. 5B  is a graph illustrating the phase response of the secondary path transfer function S(z) and its inverse. As illustrated in these two figures, the inverted secondary path response S inv (z) is not a mirror image of the secondary path response S(z) in terms of either amplitude or phase. The invertability is proportional to the performance of the error correction circuit. 
       FIG. 6  is a graph illustrating the amount of cancellation achieved when transfer function W(z) is the inverse of the secondary path transfer function. Referring to  FIG. 6 , line  620  represents the spectrum of noise signal x(n), while line  610  represents the spectrum of error signal e(n). When the amount of error is lower, the delay is lesser and the more invertible is the secondary path S(z) and more effectively is the noise cancellation system working. The amount of noise reduction between 100 Hz-3 kHz as illustrated in window  630  is then measured as the metric of invertibility. 
       FIG. 7  is a block diagram illustrating how the quality factor metric is calculated. Signals x(n), the noise to be cancelled, and e(n), the error signal, are fed to respective bandpass filters  710  and  720  to produce filtered input signals x bp (n) and e bp (n) respectively. The bandpass filters  710  and  720  may be used to filter out a region of interest, such as the 100 Hz-3 kHz window  630  of  FIG. 6 . The quality factor may then be computed as follows: 
     
       
         
           
             
               
                 
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     This quality factor, as will be discussed in more detail in connection with  FIGS. 8-13 , may be used to judge the effects of modifications to secondary path in one phone or audio device, versus another phone device, in terms of efficacy in the operation of the ANC circuit. 
       FIG. 8  is a graph illustrating the frequency response of the secondary path transfer function to a particular portable device and the resultant quality factor. In the graph of  FIG. 8 , the frequency response of the secondary path function is illustrated, along with the quality factor calculated according to equation (4). As illustrated in  FIG. 8 , the quality factor value provides a simple numerical indicator or metric, which is easier to compare to other devices and configurations than raw graphical data. 
       FIG. 9  is a graph illustrating noise cancellation gain versus quality factor for a number of different portable devices, illustrating the linear relationship between noise cancellation gain and quality factor. The X-axis of  FIG. 9  represents quality factor as measured for one of the seven different phones evaluated, A-G. The Y-axis shows the noise cancellation, in dB, in the bandwidth of 100 Hz to 6.4 kHz. 
     Phones A, B, C, D, E, F, and G, may represent phones from various manufacturers and various models from the same manufacturer, as tested using the secondary path evaluation system and method. As illustrated in  FIG. 9 , if a line is drawn between the data points represented by phones A, B, C, D, E, F, and G, it forms a relatively straight line having a constant slope, showing a substantially linear relationship between the quality factor calculated by the secondary path evaluation system and method, and the actual noise cancellation gain.  FIG. 9  validates that the secondary path evaluation system and method provides an accurate metric for evaluating secondary path, regardless of phone type or model, or other factors affecting secondary path (e.g., microphone placement, speaker placement, microphone type, speaker type, and the like). 
       FIG. 10  is a side view of the pinna test dummy used to test a cell phone to evaluate secondary path design. The secondary path evaluation system utilizes such a dummy head to simulate the placement of a cellular phone or other communication device near the pinna (ear lobe) and head of a human being. The shape and size of the human ear varies considerably, as well as the placement of a phone near the ear. 
     Testing for various ear shapes and spacing combinations is not worthwhile, as the phone manufacturer has no control as to how the user places the phone or the shape of the user&#39;s ear—which changes the nature of the secondary path. One goal of an adaptive noise cancellation system is to adapt or modify the cancellation signal based on these changes in the secondary path. Thus, the standard pinna head  810  is used, to test various phones and models of phones, as well as variations in the designs of these phones (microphone and speaker design and placement, for example) and provide a standardized “head” that may be used to provide a baseline for design comparisons. 
     Pinna head  810  includes a simulated ear pinna  820 , which is designed to mimic the acoustical characteristics of a human ear pinna. Bracket  830  is attached to pinna head  810  to hold the cell phone or other audio device in a fixed and measured relationship to pinna  820 . When testing, a technician or engineer may place a cell phone (not shown) into bracket  830  for testing purposes. Since bracket  830  may be fixed to a desired position, a phone may be tested repeatedly, after various modifications are made, in the same position and orientation as previous tests. 
       FIG. 11  shows an applications test board used in evaluating an adaptive noise reduction system in conjunction with the Pinna test dummy of  FIG. 10 . An applications test board, or development board may be offered by a semiconductor manufacturer, for a nominal fee or free, to customers or potential customers, experimenters, and the like, who wish to test the operation of a semiconductor device. In this instance, applications test board  900  is designed for testing and development of an adaptive noise cancellation semiconductor device  910 , which may be placed in a socket on the test board  900 . A display  930  may be used to display various data, or data may be output to a computer system or other data acquisition device through data port  940 . Various leads  950  may be coupled to a cell phone or other device under test, such as a cell phone mounted to pinna head  810  of  FIG. 9 . 
     One advantage of the secondary path evaluation system and method is that a standard applications test board may be used without significant modification. Thus, the system and method may be provided to a customer for the semiconductor device (e.g., cell phone manufacturer), without incurring significant cost for the manufacturer or the customer. 
       FIG. 12  is a simplified block diagram of the test system as assembled, showing the Pinna test dummy, applications test board, and computer system displaying the secondary path evaluation metric. Referring to  FIGS. 10-12 , when developing a cell phone design, an engineer or technician may mount a cell phone or other audio device to be tested, onto the mounting bracket  830  of pinna head  800 . Internal connections from the speaker, error microphone, and reference microphone may then be coupled to inputs  950  of applications test board  900 , using suitable jumpers and cabling. Output  940  may be coupled to a computer, such as a personal computer (PC) or workstation  1000 , or the like, where data may be accumulated, processed and stored. Using the measured secondary path model, the system then calculates and generates a quality factor for each device and device configuration tested, and displays this data, as well as other test data, graphically on the computer  1000 . 
       FIG. 13  is a screen shot of the display in the computer  1000  of  FIG. 12 , illustrating the displayed metric and other data relating to secondary path evaluation. Referring to  FIG. 13 , the display  1210  may appear on computer  1000  of  FIG. 12 . Various data elements may be displayed on the screen for one or more of the devices tested, for example, phones A, B, C, D, E, F, and G of  FIG. 9 . In this instance, graph  1230  of  FIG. 8  is displayed, representing cell phone configuration D, as referenced in  FIG. 9 . A quality factor for this cell phone configuration  1220  is shown at the top of the screen. 
     From the data on screen  1210 , an engineer or technician can compare the performance of one cell phone configuration against another by comparing the quality factor of one configuration to another. Rather than have to make extensive calculations as to noise cancellation at various frequencies, and make subjective judgments as to whether noise cancellation at different frequencies are comparable to noise cancellation at other frequencies, the quality factor  1220  provides a direct metric of quality of noise cancellation that can be compared across product lines, manufacturers, and configurations. 
     Once a particular phone configuration has been tested, the engineer or technician may then reconfigure the phone, for example, by moving the location of the error or reference microphones, or the location of the speaker. Different brands and models of microphones and speakers from different suppliers may be compared, to determine how these changes affect the secondary path performance. Placement and location of microphones and speakers may often be dictated by aesthetic design considerations, and type and model of speaker and microphone may be subject to cost constraints. For an engineer, juggling all of these design criteria is difficult enough, without some way of quickly and easily testing and evaluating such designs. The Quality Factor generated by the secondary path evaluation system and method simplifies this testing procedure, allowing an engineer to optimize his design in less time, at less cost. 
     The present invention may also be applied to grade a number of transducers in terms of their noise cancellation properties. A particular transducer (e.g., microphone, speaker, or the like) may be applied to a particular configuration of portable device components, and the overall system tested as previously described. Other transducers may then be substituted into the configuration, and the test repeated. Once a number of different transducers have been thus tested, the quality factors may then be compared to show the difference in performance and thus grading of different transducer types, brands, or models. As such, the system and method of the present invention may be applied to test individual components, as well as the overall system. 
     While the preferred embodiment and various alternative embodiments of the invention have been disclosed and described in detail herein, it may be apparent to those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope thereof.