Patent Publication Number: US-8126172-B2

Title: Spatial processing stereo system

Description:
BACKGROUND 
     1. Field of the Invention 
     The invention is generally related to a sound generation approach that generates spatial sounds in a listening room. In particular, the invention relates to modeling with only a few user input parameters the listening room responses for a two-channel audio input based upon adjustable real-time parameters without coloring the original sound. 
     2. Related Art 
     The aim of a high-quality audio system is to faithfully reproduce a recorded acoustic event while generating a three-dimensional listening experience without coloring the original sound, in places such as a listening room, home theater or entertainment center, personal computer (PC) environment, or automobile. The audio signal from a two-channel stereo audio system or device is fundamentally limited in its ability to provide a natural three-dimensional listening experience, because only two frontal sound sources or loudspeakers are available. Phantom sound sources may only appear along a line between the loudspeakers at the loudspeaker&#39;s distance to the listener. 
     A true three-dimensional listening experience requires rendering the original acoustic environment with all sound reflections reproduced from their apparent directions. Current multi-channel recording formats add a small number of side and rear loudspeakers to enhance listening experience. But, such an approach requires the original audio media to be recorded or captured from each of the multiple directions. However, two-channel recording as found on traditional compact discs (CDs) is the most popular format for high-quality music today. 
     The current approaches to creating three-dimensional listening experiences have been focused on creating virtual acoustic environments for hall simulation using delayed sounds and synthetic reverb algorithms with digital filters. The virtual acoustic environment approach has been used with such devices as headphones and computer speakers. The synthetic reverb algorithm approach is widely used in both music production and home audio/audio-visual components such as consumer audio/video receivers (AVRs). 
     In  FIG. 1 , a block diagram  100  illustrating an example of a listening room  102  with a traditional two-channel AVR  104  is shown. The AVR  104  may be in signal communication with a CD player  106  having a two-channel stereo output (left audio channel and a right audio channel), television  108 , or other audio/video equipment or device (video recorders, turntables, computers, laser disc players, audio/video tuners, satellite radios, MP3 players). Audio device is being defined to include any device capable of generating two-channel or more stereo sound, even if such a device may also generate video or other signals. 
     The left audio channel carries the left audio signal and the right audio channel carries the right audio signal. The AVR  104  may also have a left loudspeaker  110  and a right loudspeaker  112 . The left loudspeaker  110  and right loudspeaker  112  each receive one of the audio signals carried by the stereo channels that originated at the audio device, such as CD player  106 . The left loudspeaker  110  and right loudspeaker  112  enables a person sitting on sofa  114  to hear two-channel stereo sound. 
     The synthetic reverb algorithm approach may also be used in AVR  104 . The synthetic reverb algorithm approach uses tapped delay lines that generate discrete room reflection patterns and recursive delay networks to create dense reverb responses and attempts to generate the perception of a number of surround channels. However, a very high number of parameters are needed to describe and adjust such an algorithm in the AVR to match a listening room and type of music. Such adjustments are very difficult and time-consuming for an average person or consumer seeking to find an optimum setting for a particular type of music. For this reason, AVRs may have pre-programmed sound fields for different types of music, allowing for some optimization for music type. But, the problem with such an approach it the pre-programmed sound fields lack any optimization for the actual listening room. 
     Another approach to generate surround channels from two-channel stereo signals employs a matrix of scale factors that are dynamically steered by the signal itself. Audio signal components with a dominant direction may be separated from diffuse audio signals, which are fed to the rear generated channels. But, such an approach to generating sound channels has several drawbacks. Sound sources may move undesirably due to dynamic steering and only one dominant, discrete source is typically detected. This approach also fails to enhance very dryly recorded music, because such source material does not contain enough ambient signal information to be extracted. 
     Along with the foregoing considerations, the known approaches discussed above for generation of surround channels typically add “coloration” to the audio signals that is perceptible by a person listening to the audio generated by the AVR  104 . Therefore, there is a need for an approach to processing stereo audio signals that filters the input channels and generates a number of surround channels while allowing a user to control the filters in a simple and intuitive way in order to optimize their listening experience. 
     SUMMARY 
     An approach to spatial processing of audio signals receives two or more audio signals (typically a left and right audio signal) and generates a number of additional surround sound audio signals that appear to be generated from around a predetermined location. The generation of the additional audio signals is customized by a user who inputs a limited number of parameters to define a listening room. A spatial processing stereo system then determines a number of coefficients, room impulse responses, and scaling factors from the limited number of parameters entered by the user. The coefficients, room impulse responses and scaling factors are then applied to the input signals that are further processed to generate the additional surround sound audio signals. 
     Other systems, methods, features and advantages of the invention will be or will become apparent to one with skill in the art upon examination of the following figures and detailed description. It is intended that all such additional systems, methods, features and advantages be included within this description, be within the scope of the invention, and be protected by the accompanying claims. 
    
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
       The invention can be better understood with reference to the following figures. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the invention. Moreover, in the figures, like reference numerals designate corresponding parts throughout the different views. 
         FIG. 1  shows a block diagram representation  100  illustrating an example listening room  102  with a typical room two-channel stereo system. 
         FIG. 2  shows a block diagram representation  200  illustrating an example of an AVR  202  having a spatial processing stereo system (“SPSS”)  204  within listening room  208  in accordance with the invention. 
         FIG. 3  shows a block diagram representation  300  illustrating another example of an AVR  302  having a SPSS  304  within listening room  306  in accordance with the invention. 
         FIG. 4  shows a block diagram representation  400  of AVR  302  of  FIG. 3  with SPSS  304  implemented in the digital signal processor (DSP)  406 . 
         FIG. 5  shows a block diagram representation  500  of the SPSS  304  of  FIG. 4 . 
         FIG. 6  shows a block diagram representation  600  of an example of the coefficient matrix  502  of  FIG. 5  with a two-channel audio input. 
         FIG. 7  shows a block diagram representation  700  of an example of the coefficient matrix  502  of  FIG. 5  with a three-channel audio input. 
         FIG. 8  shows a block diagram representation  800  of an example of the shelving filter processor  506  of  FIG. 5  with a two-channel audio input. 
         FIG. 9  depicts a graph  900  of the response  902  of the first order shelving filters  802  and  804  of  FIG. 8 . 
         FIG. 10  is a block diagram representation  1000  of the fast convolution processor  510  of  FIG. 5  with a combined left audio signal and right audio signal as an input. 
         FIG. 11  is a graph  1100  of an example of an impulse response  1102  of the decorrelation filters  1006  and  1008  of  FIG. 10 . 
         FIG. 12  is a block diagram representation  1200  of an example of a first portion of processing in the Room Response Generator  420  of  FIG. 4 . 
         FIG. 13  is a graph  1300  that depicts a waveform  1302  of a typical sequence r(k) generated by the first portion  1202  of processing in the Room Response Generator  420  of  FIG. 4 . 
         FIG. 14  is a block diagram representation  1400  of an example of a second portion  1402  of processing in the Room Response Generator  420  of  FIG. 4 . 
         FIG. 15  is a graph  1500  that depicts the filter bank  1404  processing of r(k) signal received from the first portion  1202  of  FIG. 12 . 
         FIG. 16  is a graph  1600  of the gain factors ci for (i=1 . . . 10) with linear interpolation between the ten frequency points. 
         FIG. 17  is a graph  1700  that depicts the logarithmic magnitudes of the time window functions in seconds for rooms  1  . . .  10 . 
       In  FIG. 18  is a graph  1800  that depicts the chosen reverb times over frequency for rooms  1  . . .  10 . 
         FIG. 19  is a block diagram representation  1900  of the last portion  1902  of the Room Response Generator  420  of  FIG. 4 . 
         FIG. 20  is a graph  2000  that depicts the gentler build-up of reflective energy using a half Hanning window of the last portion  1902  of  FIG. 19 . 
         FIG. 21  is a graph that depicts the final results  2100  generated by the Room Response Generator  420  of  FIG. 4 . 
         FIG. 22  is a graph that depicts the samples of a room impulse response  2200  generated by Room Response Generator  420  of  FIG. 4 . 
         FIG. 23  is a block diagram representation of the user response processor  416  of  FIG. 4 . 
         FIG. 24  is a graph  2400  of a defined mapping for impulse response one to seven employed by the user response processor  416  of  FIG. 4 . 
         FIG. 25  is a graph  2500  of the diffuse energy levels employed by the user response processor  416  of  FIG. 4 . 
         FIG. 26  is a graph  2600  of the attenuation of discrete reflections of the side channel audio signals. 
         FIG. 27  is a graph  2700  of the attenuation of the rear channel audio signal reflections. 
         FIG. 28  is flow diagram of an approach for spatial processing in a spatial processing stereo system. 
     
    
    
     DETAILED DESCRIPTION 
     In the following description of examples of implementations of the present invention, reference is made to the accompanying drawings that form a part hereof, and which show, by way of illustration, specific implementations of the invention that may be utilized. Other implementations may be utilized and structural changes may be made without departing from the scope of the present invention. 
     Turning to  FIG. 2 , a block diagram illustrating an example of an AVR  202  having a spatial processing stereo system (“SPSS”)  204  within listening room  208  in accordance with the invention is shown. The AVR  202  may be connected to one or more audio generating devices, such as CD player  206  and television  210 . The audio generating devices will typically be two-channel stereo generating devices that connect to the AVR  202  with a pair of electrical cables, but in some implementations, the connection may be via fiber optic cables, or single cable for reception of a digital audio signal. 
     The SPSS  204  processes the two-channel stereo signal in such a way to generate seven audio channels in addition to the original left channel and right channel. In other implementations, two or more channels, in addition to the left and right stereo channels may be generated. Each audio channel from the AVR  202  may be connected to a loudspeaker, such as a center channel loudspeaker  212 , four surround channel loudspeakers (side left  222 , side right  224 , rear left  226 , and rear right  228 ), two elevated channeling loudspeakers (elevated left  218  and elevated right  220 ) in addition to the left loudspeakers  214  and right loudspeaker  216 . The loudspeakers may be arranged around a central listening location or spot, such as sofa  230  located in listening room  208 . 
     In  FIG. 3 , a block diagram illustrating another example of an AVR  302  having a SPSS  304  connected to seven loudspeakers ( 310 - 322 ) within listening room  306  in accordance with the invention is shown. The AVR  302  is shown as connecting to a television via a left audio cable  326 , right audio cable  328  and center audio cable  330 . The SPSS  304  within the AVR  302  receives and processes the left, right and a center audio signal carried by the left audio cable  326 , right audio cable  328 , and center audio cable  330  and generates four additional audio signals. In other implementations, fiber optic cable may connect the television  308  or other audio/video components to the AVR  302 . In order to generate the center channel, a known approach to center channel generation may be used within the television  308  to convert the mono or two channel stereo signal typically received by a television into three channels. 
     The additional four audio channels may be generated from the original right, left and center audio channels received from the television  308  and are connected to loudspeakers, such as the left loudspeaker  310 , right loudspeaker  312  and center loudspeaker  314 . The additional four audio channels are the rear left, rear right, side left and side right, and are connected to the rear left loudspeaker  320 , rear right loudspeaker  322 , side left loudspeaker  314 , side right loudspeaker  318 . All the loudspeakers may be located in a listing room  306  and placed relative to a central position, such as the sofa  324 . The connection to the loudspeakers may be via wires, fiber optics, or electro magnetic waves (radio frequency, infrared, Bluetooth, wireless universal serial bus, or other non-wired connections). 
     In  FIG. 4 , a block diagram of AVR  302  of  FIG. 3  with SPSS  304  implemented in the digital signal processor (DSP)  406  is shown. Two-channel or three-channel stereo input signals from an audio device, such as CD player  206 , television  308 , or MP3 player  302  may be received at a respective input  408 ,  410 , and  412  in AVR  304 . A selector  412  may be located within the AVR  302  and control which of the two-channel stereo signals or three-channel stereo signals is made available to the DSP  406  for processing in response to the user interface  414 . The user interface  414  may provide a user with buttons or other means (touch screen, mouse, touch pad, infra-red remote control, etc . . . ) to select one of the audio devices. Once a selection occurs at the user interface  414 , the user response processor (URP)  416  in DSP  406  identifies the device detected and generates a notification that is sent to selector  412 . The selector  412  may also have analog-to-digital converters that convert the two-channel stereo signals or three-channel stereo signals into digital signals for processing by the SPSS  304 . In other implementations, the selector  412  may be directly controlled from the user interface  414  without involving the DSP  406  or other types of microprocessors or controllers that may take the place of DSP  406 . 
     The DSP  406  may be a microprocessor that processes the received digital signal or a controller designed specifically for processing digital audio signals. The DSP  406  may be implemented with different types of memory (i.e. RAM, ROM, EEPROM) located internal to the DSP, external to the DSP, or a combination of internal and external to the DSP. The DSP  406  may receive a clock signal from an oscillator that may be internal or external to the DSP, depending upon implementation design requirements such as cost. Preprogrammed parameters, preprogrammed instructions, variables, and user variables for filters  418 , URP  416 , and room response generator  420  may be incorporated into or programmed into the DSP  406 . In other implementations, the SPSS  304  may be implemented in whole or in part within an audio signal processor separate from the DSP  406 . 
     The SPSS  304  may operate at the audio sample rate of the analog-to-digital converter (44.1 KHz in the current implementation). In other implementations, the audio sample rate may be 48 KHz, 96 KHz or some other rate decided on during the design of the SPSS. In yet other implementations, the audio sample may be variable or selectable, with the selection based upon user input or cable detection. The SPSS  304  may generate the additional channels with the use of linear filters  418 . The seven channels may then be passed through digital-to-analog (D/A) converters  422 - 434  and results in seven analog audio signals that may be amplified by amplifiers  436 - 448 . The seven amplified audio signals are then output to the speakers  310 - 322  of  FIG. 3 . 
     The URP  416  receives input or data from the user interface  414 . The data is processed by the URP  416  to compute system variables for the SPSS  304  and may process other types of user interface input, such as input for the selector  412 . The data for the SPSS  304  from the user interface  414  may be a limited set of input parameters related to spatial attributes, such as the three spatial attributes in the current implementation (stage width, stage distance, and room size). 
     The room response generator  420  computes a set of synthetic room impulse responses, which are filter coefficients. The room response generator  420  contains a statistical room model that generates modeled room impulse responses (RIRs) at its output. The RIRs may be used as filter coefficients for FIR filters that may be located in the AVR  302 . A “room size” spatial attribute may be entered as an input parameter via the user interface  414  and processed by the URP  416  for generation of the RIRs by the room response generator  420 . The “room size” spatial attribute input as an input parameter in the current implementation is a number in the range of 1 to 10, for example room_size=10. The room response generator  420  may be implemented in the DSP  406  as a background task or thread. In other implementations, the room response generator  420  may run off-line in a personal computer or other processor external to the DSP  406  or even the AVR  302 . 
     Turning to  FIG. 5 , a block diagram  500  of the signal processing block  418  of the SPSS  304  of  FIG. 4  is shown. The SPSS  304  generates audio signals for a number of surround channels. In the current example, seven audio channels are being processed by the SPSS  304 . The input audio signals may be from a two-channel (left and right), three channel (left, right and center), or a multichannel (left, right, center, left side, right side, left back, and right back) source. In other implementations, a different number of input channels may be made available to the SPSS  304  for processing. The input channels will typically carry an audio signal in a digital format when received by the SPSS  304 , but in other implementations the SPSS may include A/D converters to convert analog audio signals to digital audio signals. 
     In the current implementation, a coefficient matrix  502  receives the left, right and center audio inputs. The coefficient matrix  502  is created in association with a “stage width” input parameter that is entered via the user interface  414  of  FIG. 4 . The left, right, and center channels&#39; inputted audio signals are processed with the coefficient matrix that generates a weighted linear combination of the audio signals. The resulting signals are the left, right, center, left side and right side audio signals and are typically audio signals in a digital format. 
     The left and right audio inputs may also be processed by a shelving filter processor  506 . The shelving filter processor  506  applies shelving filters along with delay periods to the left and right audio signals inputted on the left and right audio inputs. The shelving filter processor  506  may be configured using a “stage distance” parameter that is input via the user interface  414  of  FIG. 4 . The “stage distance” parameter may be used to aid in the configuration of the shelving filters and delay periods. The shelving filter processor  506  generates the left side audio signal, right side audio signal, left back audio signal and the right back audio signal and are typically in a digital format. 
     The left and right audio inputs may also be summed by a signal combiner  508 . The combined left and right audio inputs may then be processed by a fast convolution processor  510  that uses the “room size” input parameter. The “room size” input parameter may be entered via the user interface  414  of  FIG. 4 . The fast convolution processor  510  enables the generated left side, right side, left back and right back output audio signals to be adjusted for apparent room size. 
     The left side, right side, left back and right back audio signals generated by the coefficient matrix  502 , shelving filters box  506 , and fast convolution processor  510 , along with the left side, right side, left back and right back input audio signals inputted from all audio source are respectively combined. A sound field such as a five or seven channel stereo signal may also be selected via the user interface  414  and applied to or superimposed on the respectively combined signals to achieve a final audio output for the left side, right side, left back and right back output audio signals. 
     In  FIG. 6 , a block diagram representation  600  of an example of the coefficient matrix  502  of  FIG. 5  with a two-channel (left and right channel) audio source is shown. The left audio signal from the left channel and the right audio signal from the right channel are received at a variable 2×2 matrix  602 . The variable 2×2 matrix may have a crosstalk coefficient p 1  that is dependent with the “stage width” input parameter and results in the left audio signal and the right audio signal. The left audio signal and the right audio signal are received by a fixed 2×2 matrix  604  that employs a static coefficient p 5 . The static coefficient p 5  may be set to a value of −0.33. Positive values for the coefficient have the effect of narrowing the sound stage, while negative coefficients widen the sound stage. 
     The center audio signal may be generated by the summation of the received left audio signal with the received right audio signal in a signal combiner  606 . The signal combiner  606  may also employ a weight factor p 2  that is dependent upon the state width parameter. The left side output signal and the right side output signal may also be scaled by a variable factor p 3 . All output signals (left, right, center, left side, and right side) may also be scaled by a common factor p 4 . The scale factors are determined by the URP  416  of  FIG. 4 . 
     The stage width input parameter is an angular parameter φ in the range of zero to ninety degrees. The parameter controls the perceived width of the frontal stereo panorama, from minimum zero degrees to a maximum of ninety degrees. The scale factors p 1 -p 4  are derived in the present implementation with the following formulas:
 
 p   1 =0.3·[ cos(2πφ/180)−1],
 
 p   2 =0.01·[80+0.2·φ], with center at input,
 
 p   2 =0.01·[50+0.2·φ], without center at input,
 
 p   3 =0.0247·φ,
 
 p   4 =1/√{square root over ( 1 + p   1   2   +p   2   2   +P   3   2 (1+ p   5   2 ))},
 
φε└0 . . . 90°┘.
 
     The mappings are empirically optimized, in terms of perceived loudness, regardless of the input signals and chosen width setting, and in terms of uniformity of the image across the frontal stage. The output scale factor p 4  normalizes the output energy for each width setting. 
     Turning to  FIG. 7 , a block diagram representation  700  of an example of the coefficient matrix  502  of  FIG. 5  with a three-channel (left, right, and center channel) audio source is shown. The right and left input audio is processed by a variable 2×2 matrix  702  and a fixed 2×2 matrix  704  as described in  FIG. 6 . The center channel audio input is weighted by 2 times a weight factor p 2  and then scaled by the common factor p 4 . The crosstalk coefficient p 1 , weight factor p 2 , variable factor p 3 , common factor p 4 , and static coefficient p 5  may be derived from the “stage width” input parameter that may be entered via the user interface  414  of  FIG. 4 . 
     In  FIG. 8 , a block diagram representation  800  of an example of the shelving filter processor  506  of  FIG. 5  with a two-channel audio input is shown. The purpose of the shelving filter processor  506  is to simulate discrete reflected sound energy, as it occurs in natural acoustic environments (e.g. performance halls). The reflected sound energy provides cues for the human brain to estimate the distance of the sound sources. In the current implementation, each loudspeaker produces one reflection from its particular location. Reflections from the side loudspeakers significantly aid the simulated sensation of distance. In simpler terms, the shelving filter processor  506  models the frequency response alteration when sound is bounced off a wall and some absorption of the sound occurs. 
     The shelving filter process  506  receives the left audio signal at a first order high-shelving filter  802 . Similarly, the shelving filter process  506  receives the right audio signal at another first order high shelving filter  804 . The parameters of the shelving filters  802  and  804  may be gain “g” and corner frequency “f cs ” and depend on the intended wall absorption properties of a modeled room. In the current implementation, “g” and “f cs ” may be set to fixed values for convenience. Delays T 1   806 , T 2   808 , T 3   810 , and T 4   812  are adjusted according to the intended stage distance parameter as determined by the URP  416  entered via the user interface  414 . The resulting signals left side, left back, right side, and right back are attenuated by c 11   814 , c 12   816 , c 13   818 , and c 14   820  respectively, resulting in attenuated signals left side, left back, right side, and right back. 
     Turning to  FIG. 9 , a graph  900  of the response  902  of the first order shelving filters  802  and  804  of  FIG. 8  is depicted. The vertical axis  904  of the graph  900  is in decibels and the horizontal axis  906  is in Hertz. The gain “g” is set to 0.3 and corner frequency “f cs ” is set to 6.8 kHz resulting in a response plot  902  from the first order shelving filters  802  and  804  within the shelving filter processor  506 . 
     In  FIG. 10 , a block diagram  1000  of the fast convolution processor  510  of  FIG. 5  with a combined left audio signal and right audio signal as an input is shown. The combined left audio signal and right audio signal are down-sampled by a factor of two in the current implementation via a finite impulse response (FIR) filter (decimation filter)  1002 . Another FIR filter that may have a long finite impulse response, such as 10,000-60,000 samples then realizes a simulated room impulse response (RIR) filter  1004  with coefficient that are stored in memory and generated previously by the room response generator  420 . The RIR filter  1004  may be implemented using partitioned fast convolutions. The use of partitioned fast convolutions reduces computation cost when compared to direct convolution in the time domain and has lower latency than conventional fast convolutions in the frequency domain. The reduced computation cost and lower latency are achieved by splitting the RIR filter  1004  into uniform partitions. For example, a RIR filter of length 32768 may be split into 128 partitions of length 256. The output signal is a sum of 128 delayed signals generated by the 128 sub-filters of length 256, respectively. 
     The pair of shorter decorrelation filters  1006  and  1008  with a length between 500-2,000 coefficients generates decorrelated versions of the room response. The impulse response of the decorrelation filters  1006  and  1008  may be constructed by using an exponentially decaying random noise sequence with normalization of its complex spectrum by the magnitude spectrum. With the resulting time domain signal computed with an inverse fast Fourier transform (FFT). The resulting filter may be classified as an all-pass filter and does not alter the frequency response in the signal path. However, the decorrelation filters  1006  and  1008  do cause time domain smearing and re-distribution, thereby generating decorrelated output signals when applying multiple filters with different random sequences. 
     The output from the decorrelation filters  1006  and  1008  are up-sampled by a factor of two respectively, by up-samplers  1010  and  1012 . The resulting audio signal from the up-sampler  1010  is the left side audio signal that is scaled by a scale factor c 21 . The resulting audio signal from the up-sampler  1012  is the right audio signal that is scaled by a scale factor c 24 . The Ls and Rs are then used to generate the left back audio signal and right back audio signal. 
     The left back and right back audio signals are generated by another pair of decorrelated outputs using a simple 2×2-matrix with coefficients “a”  1014  and “b”  1016 . Coefficients are chosen such that the center signal in the resulting stereo mix is attenuated, and the lateral signal (stereo width) amplified (for example a=0.3 and b=−0.7). The signals in the 2×2 matrix are combined by mixers  1018  and  1020 . The resulting left back audio signal from mixer  1018  is scaled by a scale factor c 22  and the resulting right back audio signal from mixer  1020  is scaled by a scale factor of c 23 . 
     Turning to  FIG. 11 , a graph  1100  of an example of an impulse response  1102  of the decorrelation filters  1006  and  1008  of  FIG. 10  is shown. The vertical axis  1104  is the amplitude of the signal and the horizontal axis  1106  is the time in samples. The impulse response  1102  may be constructed by using an exponentially decaying random noise sequence. 
     Turning to  FIG. 12 , a block diagram  1200  of an example of a first portion  1202  of processing in the Room Response Generator  420  of  FIG. 4 . Two independent, random noise sequences are the inputs to the first portion  1202  of the RIR filter  1004 . The two independent random noise sequences contain samples that are uniform or Gaussian distributed, with constant power density spectra (white noise sequence). The sequence lengths may be equal to the desired final length of the RIR. Such sequences can be generated with software, such at Matlab™ with the function “rand” or “randn”, respectively. The second random noise sequence may be filtered by a first order lowpass filter of corner frequency f cl , the value of which depends on the “room size” input parameter. For example, in the case where there are ten room sizes available (R-10), the parameter f cl  may be obtained by the following logarithmic mapping of the 10 frequencies between 480 Hz and 19200 Hz:
 
 f   cl ( R size)=[480, 723, 1090, 1642, 2473, 3726, 5614, 8458, 12744, 19200] Hz.
 
     The first sequence may be element-wise multiplied using the multiplier  1206  by the second, lowpass filtered sequence. The result may be filtered with a first order shelving filter  1208  having a corner frequency f cs =10 kHz and gain “g”=0.5 in the current implementation, in order to simulate wall absorption properties. The two parameters are normally fixed. 
     In  FIG. 13 , a graph  1300  that depicts a waveform  1302  of a typical sequence r(k) generated by the first portion  1202  of processing in the Room Response Generator  420  of  FIG. 4  is shown. The vertical axis  1304  is amplitude and the horizontal axis  1306  is the number of time samples. The waveform exhibits occurrences of high amplitudes with a low probability that resemble discrete room reflections. The density of the discrete reflections is higher at larger room sizes (higher f cl ). Larger rooms will therefore sound smoother, less “rough” to the human brain. 
     Turning to  FIG. 14  a block diagram  1400  of an example of a second portion  1404  of processing in the Room Response Generator  420  of  FIG. 4 . The second portion  1404  receives the r(k) signal or sequence from the first portion  1202  of  FIG. 12 . A filter bank  1404  further processes the received r(k) signal. The filters bank  1404  may split the signal into several sub-bands (M sub-bands). Each sub-band signal may be scaled by a predetermined gain factor “c i ” where i=1−M. Each of the respective c i  filtered signal portions are then element-wise multiplied by an exponentially decaying sequence (a time window) d i (k)  1406 ,  1408  and  1410 , characterized by a time constant T 60,i : 
                 d   i     ⁡     (   k   )       =     ⅇ       -     3         log   10     ⁡     (   e   )       ⁢     T     60   ,   i       ⁢     f   s           ⁢   k             
T60,i are the reverb times in the i-th band and f s  is the sample frequency (typically f s =48 kHz). The sub-band signals may then be summed by a signal combiner  1412  or similar circuit to form the output sequence y(k).
 
     In  FIG. 15 , a graph  1500  that depicts the filter bank  1404  processing of r(k) signal received from the first portion  1202  of  FIG. 12  is shown. The number of logarithmically spaced sub-bands may be set to ten (M=10). The each of the sub-bands overlap at −6 dB and sum up to constant amplitude. The corner frequencies fc are typically chosen to have logarithmic-octave spacing, such as fc(i)=[31.25 62.5 125 250 500 1000 2000 4000 8000 16000], i=1 . . . M. 
     The frequencies for fc(i) above denote the crossover (−6 dB) points of filter bank  1404 . The gain factors ci (i=1 . . . 10) with linear interpolation between the ten frequency points, are displayed in graph  1600  shown in  FIG. 16 . Room  1  plot  1602  in graph  1600  depicts the smallest room model and room  10  plot  1604  depicts the largest room model. The graph  1600  demonstrates that the larger the room model, the higher the gain will be at low frequencies. 
     The parameters above used to model the rooms may be obtained after measuring impulse responses in real halls of different sizes. The measured impulse responses may then be analyzed using the filter banks  1440 . The energy in each band may then be measured and apparent peaks smoothed in order to eliminate pronounced resonances that could introduce unwanted colorations of the final audio signals. 
     In  FIG. 17 , a graph  1700  that depicts the logarithmic magnitudes of the time window functions for room  1   1702  to room  10   1704  in seconds at a frequency band i=7 (8458 Hz) is shown. The exponential decay corresponds to a linear one in the logarithmic plots of graph  1700 . The reverb time T 60  is the point where the curves cross the time axis at the magnitude of −60 dB. In  FIG. 18 , a graph  1800  that depicts the chosen reverb times over frequency for rooms  1  . . .  10  is shown. The parameters have been chosen such that the model for the rooms  1  . . .  10  fits smoothed versions of the various measured rooms and hulls. 
     Turning to  FIG. 19 , a block diagram  1900  of the last portion  1902  of the RIR filter  1004  of  FIG. 10  is shown. The last portion  1902  starts the time window to shape the initial part of the modeled impulse response y(k). The time window is a half Hanning window, as is available as function Hann.m in MATLAB™. The window length may vary linearly between zero and about 150 msec for the largest room. The window models a gentler build-up of reflective energy that may be observed in a room (especially in large rooms) and adds clarity and speech intelligibility. The output of the last portion  1902  of the Room Response Generator  420  of  FIG. 4  is the h(k) impulse response, the coefficients of the RIR filter  1004  of  FIG. 10 . A graph  2000  in  FIG. 20  depicts the gentler build-up of reflective energy of the half Hanning window. In  FIGS. 21 and 22 , the final results (i.e. samples of room impulse response) generated by the RIR (room  1  and  10  respectively) are shown. 
     In  FIG. 23 , a block diagram  2302  of the URP  416  of  FIG. 4  is shown. The user response processor  416  computes the parameters used by the SPSS  304 , based upon a limited number of user input parameters (three in the current implementation). Variables that are used by the SPSS  304  may be the angle that controls the stage width, delays T 1  . . . T N  to control the temporal distribution of early reflections, coefficients c 11  . . . c 1N  to control the energy of discrete reflections, coefficients c 21  . . . c 2N  to control the energy of RIR responses, and the RIR according to the desired Room Size. The input parameters are mapped to variables and equations in the parameter mapping area of memory. The parameter mapping area of memory is accessed and the formulas and data described previous are used to generate the variables used by the SPSS  304  and to determine the RIRs in memory  420 . The URP  416  computes new coefficients sets and selects RIRs in response to a change in any of the input parameters associated with the spatial attributes (stage width, stage distance and room size). 
     Means may be provided to assure smooth transitions between the parameter settings when parameters are change, such as interpolation techniques. The number of input parameters may be further reduced by, for example, combining stage distance and room size to one parameter that are controlled simultaneously with a single input device, such as a knob or keypad. 
     In  FIG. 24 , a graph  2400  of a defined mapping for impulse response for RIR of 1 to 7 employed by the user response processor  416  of  FIG. 4  is shown. The mappings have been empirically optimized in terms of perceived loudness, regardless of input signals and chosen room width setting, and in terms of uniformity of the image across the frontal stage. In  FIG. 25 , a graph  2500  of the diffuse energy levels employed by the user response processor  416  of  FIG. 4  is shown. The room size may also scale the reflection delay values T i  in  FIG. 5 . In large rooms, walls are farther apart, thus discrete reflections are spread over larger time intervals. Typical values for a system with four surround channels are:
         T 1 =s·8 msec, T 2 =s·11 msec, T 3 =s·7 m sec, T 4 =s·13 msec, where s=0.5+Rsize/50.       

     In  FIG. 26 , a graph  2600  of the attenuation of discrete reflections of the side channel audio signals Ls and Rs with parameters c 11  and c 13  of  FIG. 8  is shown. The stage distance controls the attenuation of discrete reflections of the side channels and in  FIG. 27 , a graph  2700  of the attenuation of the rear channel audio signal reflections c 12  and c 14  of  FIG. 8  is shown. 
     Turning to  FIG. 28 , a flow diagram  2800  of an approach for spatial processing in a SPSS such as  204  or  304  is depicted. The flow diagram starts  2802  with receipt of parameters at a user interface associated with spatial attributes, such as room size, stage distance and stage width  2804 . The SPSS  204  may also receive a right audio signal and a left audio signal from an audio device. The right audio signal and left audio signal may be filtered by a number of filters  2806 , where the filters may use coefficients that are generated by a user response processor that processes the parameters inputted at the user interface  2806 . The user response processor uses coefficients stored in memory that have been generated by a room response generator. The left audio signal and right audio signal are processed using the filter coefficients to generate a center signal and/or two or more surround audio signals  2810 . The flow diagram is shown as ending  2812 , but in practice it is a continuous flow that generates the two or more surround audio signals. 
     Persons skilled in the art will understand and appreciate, that one or more processes, sub-processes, or process steps may be performed by hardware and/or software. Additionally, the SPSS described above may be implemented completely in software that would be executed within a processor or plurality of processors in a networked environment. Examples of a processor include but are not limited to microprocessor, general purpose processor, combination of processors, DSP, any logic or decision processing unit regardless of method of operation, instructions execution/system/apparatus/device and/or ASIC. If the process is performed by software, the software may reside in software memory (not shown) in the device used to execute the software. The software in software memory may include an ordered listing of executable instructions for implementing logical functions (i.e., “logic” that may be implemented either in digital form such as digital circuitry or source code or optical circuitry or chemical or biochemical in analog form such as analog circuitry or an analog source such an analog electrical, sound or video signal), and may selectively be embodied in any signal-bearing (such as a machine-readable and/or computer-readable) medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that may selectively fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. In the context of this document, a “machine-readable medium,” “computer-readable medium,” and/or “signal-bearing medium” (herein known as a “signal-bearing medium”) is any means that may contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The signal-bearing medium may selectively be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, air, water, or propagation medium. More specific examples, but nonetheless a non-exhaustive list, of computer-readable media would include the following: an electrical connection (electronic) having one or more wires; a portable computer diskette (magnetic); a RAM (electronic); a read-only memory “ROM” (electronic); an erasable programmable read-only memory (EPROM or Flash memory) (electronic); an optical fiber (optical); and a portable compact disc read-only memory “CDROM” (optical). Note that the computer-readable medium may even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory. Additionally, it is appreciated by those skilled in the art that a signal-bearing medium may include carrier wave signals on propagated signals in telecommunication and/or network distributed systems. These propagated signals may be computer (i.e., machine) data signals embodied in the carrier wave signal. The computer/machine data signals may include data or software that is transported or interacts with the carrier wave signal. 
     While the foregoing descriptions refer to the use of a wide band equalization system in smaller enclosed spaces, such as a home theater or automobile, the subject matter is not limited to such use. Any electronic system or component that measures and processes signals produced in an audio or sound system that could benefit from the functionality provided by the components described above may be implemented as the elements of the invention. 
     Moreover, it will be understood that the foregoing description of numerous implementations has been presented for purposes of illustration and description. It is not exhaustive and does not limit the claimed inventions to the precise forms disclosed. Modifications and variations are possible in light of the above description or may be acquired from practicing the invention. The claims and their equivalents define the scope of the invention.