Patent Publication Number: US-9432790-B2

Title: Real-time sound propagation for dynamic sources

Description:
BACKGROUND 
     Video gaming technologies have advanced in recent years to allow a game player to have a rich experience when playing a video game. In the recent past, video game environments were limited to two dimensions. In other words, a video game player could control one or more graphical characters on a video screen in two dimensions (e.g., left and right; up and down). This limitation to a two-dimensional environment due to limitations in processors associated with gaming consoles. Specifically, the processors were unable to render and update graphical scenes in three dimensions responsive to user input. 
     These older video games also output audio signals when certain circumstances occurred in the game. For example, when a player caused a character to jump a particular audible output would be generated that indicated to the player that the jump had occurred. These output sounds were identical regardless of where in the two-dimensional environment the character was undertaking the particular action. 
     In currently available game systems with respect to certain games, a player can cause a character to navigate through a virtual three-dimensional environment. Additionally, such games can output sounds that depend upon the perspective of the user in the game with respect to the three-dimensional environment. For example, in a “first-person” game, a game developer can cause sounds to be output that sound to the player as if the noise came from a certain position in the three-dimensional environment while the player is positioned at a certain location in the three-dimensional environment. Game developers have traditionally undertaken this output of sound by, for instance, coding different sounds depending on where in the three-dimensional environment the player is desired to reside. Programming so many different sounds for a variety of possible noises can take an incredible amount of time and effort by the game developer. 
     SUMMARY 
     The following is a brief summary of subject matter that is described in greater detail herein. This summary is not intended to be limiting as to the scope of the claims. 
     Described herein are various technologies pertaining to playing back an arbitrary audio signal such that it is perceived by a listener to have been generated at a particular location in a virtual three-dimensional environment and received at a different particular location in the virtual three-dimensional environment. In other words, various technologies pertaining to undertaking real-time acoustic modification that supports dynamic sources and listeners in a particular virtual three-dimensional environment are described herein. Such real-time modification of an arbitrary audio signal can be accomplished through utilization of a numerical simulator that can simulate a sample audio signal from a plurality of source locations and received at a plurality of receiver locations in a static virtual three-dimensional environment. In an example, a sample audio signal may be a pulse, and the numerical simulator may be configured to ascertain impulse responses at various receiver locations for a plurality of different source locations. 
     Pursuant to an example, a virtual three-dimensional environment can be created. For instance, this environment may be a room or series of rooms, or an outdoor scene with particular boundaries, generated by a game developer. In another example, a virtual three-dimensional environment may be a representation of a room in a house (e.g., generated by a CAD program or automatically generated through utilization of sensors). Various features pertaining to the three-dimensional environment may also be included in such three-dimensional environment, including but not limited to, type of materials that make up walls in the three-dimensional environment, types of materials that make up furniture in the three-dimensional environment (e.g., absorption data), or other suitable data. The three-dimensional environment may be partitioned into a volumetric grid. A numerical simulator may then be configured to simulate output of a sample audio signal from a particular source location (e.g., from a particular cell in the volumetric grid). The numerical simulator may be configured to ascertain an impulse response at a plurality of receiver locations in the volumetric grid, given that the sample audio signal is output from the particular source location. For example, the numerical simulator can determine an impulse response from receivers placed in each cell of the volumetric grid, or from a subsampled set of cells in the volumetric grid. These impulse responses may be subject to sub-sampling, compression (factoring) such that a resulting data file can be utilized in connection with real-time modification of an arbitrary audio signal given dynamic sources and receivers. This process can be repeated for a plurality of different source locations in the three-dimensional environment, such that the data file can comprise compressed responses pertaining to the sampled audio signal at different source and receiver locations. 
     Example data that can be included in the aforementioned data file for a particular source and receiver location in the virtual three-dimensional environment can include data representative of a late reverberation phase of a response (e.g., peaks detected during the late reverberation phase, wherein the peaks are indicative of frequency and amplitude of the response signal), data indicative of an early reflection phase of the response signal (e.g., peaks detected with respect to time in the early reflection phase of the response signal), and a frequency trend computed based at least in part upon the detected frequencies in the early reflection phase of the response signal. In an example, the early reflection phases of response signals can be computed more spatially densely when compared with the late reverberation portion of response signals. For instance, the late reverberation phase can be computed a single time and utilized for each source/receiver location pair, while early reflection phases of response signals can be computed independently for each source/receiver location pair. 
     Once this data file has been generated, such data file can be used in connection with modifying arbitrary audio signal in real time for dynamic sources and/or receivers in the virtual three-dimensional environment. For example, a desired location of a source of the arbitrary audio signal can be identified in the virtual three-dimensional environment, and a desired location of a receiver of the arbitrary audio signal can be identified in the virtual three-dimensional environment. The precomputed data file can be accessed, and an interpolation can be undertaken using data pertaining to simulated source locations and receiver locations. Once the interpolation has been undertaken, the resulting interpolated data can be convolved in real time with the arbitrary audio signal. The result of the convolution can be a modified signal that is perceived by a listener as if it was output at the source location and the listener is at the receiver location. 
     Other aspects will be appreciated upon reading and understanding the attached figures and description. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a functional block diagram of an example system that facilitates automatically and in real time propagating audio signals for dynamic sources and/or receivers in a virtual three-dimensional environment. 
         FIG. 2  is an example depiction of a three-dimensional environment partitioned into a volumetric grid. 
         FIG. 3  is a functional block diagram of an example system that facilitates generating a precomputed data file used in connection with real-time audio propagation for dynamic sources and receivers. 
         FIG. 4  is a functional block diagram of an example system that facilitates generating the precomputed data file. 
         FIG. 5  illustrates a sample response signal that comprises an early reflection and late reverberation phase. 
         FIG. 6  is a graphical depiction of peaks extracted in an early reflection phase and a frequency trend that is based at least in part upon the extracted peaks. 
         FIG. 7  is a functional block diagram of a playback component that automatically and in real time propagates audio for dynamic sources and/or dynamic receivers. 
         FIG. 8  is a flow diagram that illustrates an example methodology for automatically playing back an audio signal, based at least in part upon a late reverberation signal computed through utilization of a numerical simulator. 
         FIG. 9  is a flow diagram that illustrates an example methodology for extracting peaks and determining a frequency trend with respect to an early reflection portion of a response ascertained during a numerical simulation. 
         FIG. 10  is a flow diagram that illustrates an example methodology for automatically modifying an arbitrary audio-signal in real-time based at least in part upon a precomputed data file. 
         FIG. 11  is an example computing system. 
     
    
    
     DETAILED DESCRIPTION 
     Various technologies pertaining to real-time audio propagation for dynamic sources and/or receivers in a static virtual three-dimensional environment will now be described with reference to the drawings, where like reference numerals represent like elements throughout. In addition, several functional block diagrams of example systems are illustrated and described herein for purposes of explanation; however, it is to be understood that functionality that is described as being carried out by certain system components may be performed by multiple components. Similarly, for instance, a component may be configured to perform functionality that is described as being carried out by multiple components. 
     With reference to  FIG. 1 , an example system  100  that facilitates real-time audio propagation for dynamic sources and/or receivers in a virtual three-dimensional environment is illustrated. The system  100  comprises a data repository  102  that includes a (pre-computed) data file  104 . The data file  104  comprises data that is based at least in part upon a pre-computed, offline, wave-based simulation for a static virtual three-dimensional environment  106 . The wave-based simulation can be computed in terms of the seven-dimensional spatially varying acoustic response pertaining to the virtual three-dimensional environment  106 ; S (t, p s , p r ) where t is time, p s  is source location in the virtual three-dimensional environment  106 , and p r  is receiver location in the virtual three-dimensional environment  106 . More detail pertaining to an example manner for generating the data file  104  will be provided below. For purposes of explanation of  FIG. 1 , what is to be understood is that the data file  104  is precomputed and comprises data pertaining to a simulation of a sample audio signal originating in the virtual three-dimensional environment  106  from a plurality of different source locations to a receiver in a plurality of different receiver locations. 
     The system  100  additionally includes a receiver component  108  that can receive an arbitrary audio signal from a source  110 . The source  110  may be a footstep, a mouth of an individual or a virtual individual in the virtual three-dimensional environment  106 , a breaking vase in the virtual three-dimensional environment  106 , or any other suitable arbitrary audible signal that is intended to originate from the source  110  in the virtual three-dimensional environment  106 . 
     A location determiner component  112  can determine a first location and a second location in the virtual three-dimensional environment  106 . The first location can be a location of the source  110  in the virtual three-dimensional environment  106 , and the second location can be a location of a receiver  114  in the virtual three-dimensional environment  106 . For example, as will be described in greater detail below, the virtual three-dimensional environment  106  can be partitioned into a volumetric grid, and the location determiner component  112  can determine that the source  110  is within a particular cell within the volumetric grid and the receiver  114  is in another cell in the volumetric grid. For instance, the virtual three-dimensional environment  106  can pertain to a three-dimensional environment in a video game. The video game may be a first-person game such that a player of the video game perceives herself to be at a location in the virtual three-dimensional environment  106  that corresponds to the receiver  114 . The source  110  may be a character taking a footstep in the virtual three-dimensional environment  106  at a particular location in the virtual three-dimensional environment  106 . Thus, the source  110  may be a foot hitting the ground in the virtual three-dimensional environment  106 , and the audio signal may be representative of the sound that is output at the source location when such foot hits the ground. The location determiner component  112  can determine location of the source  110  in the virtual three-dimensional environment  106 , and can also determine location of the receiver  114  in the virtual three-dimensional environment  106 . 
     A playback component  116  can access the data file  104  responsive to the receiver component  108  receiving the audio signal (e.g., intended to originate from the source  110 ) and the location determiner component  112  determining the location of the source  110  and the location of the receiver  114  in the virtual three-dimensional environment  106 . The playback component  116  can access the data repository based at least in part upon the first location (the location of the source  110  in the virtual three-dimensional environment  106 ) and the second location (the location of the receiver  114  in the virtual three-dimensional environment  106 ). The playback component  116  can automatically cause the audio received from the source  110  to be modified such that it is perceived by a listener as being initiated from the first location (the location of the source  110 ) when the listener is at the second location (the location of the receiver  114 ). 
     Continuing with the video game example, the sound caused by the foot hitting the floor in the virtual three-dimensional environment  106  will be perceived by the listener (the game player) to have been generated at the location of the source  110  in the virtual three-dimensional environment  106  when the game player (the listener) is placed at the location of the receiver  114  in the virtual three-dimensional environment  106 . Therefore, if the video game is a first-person game, the listener will be at the location of the receiver  114  in the virtual three-dimensional environment  106 , and the audio signal when output by the playback component  116  will sound as if it were emitted from the location of the source  110  in the virtual three-dimensional environment  106  when the listener is at the location of the receiver  114  in such virtual three-dimensional environment  106 . 
     Moreover, as the source  110  and/or the receiver  114  change position in the virtual three-dimensional environment  106 , the playback component  116  can be configured to modify the audio signal in real-time as such positions change. For instance, if the source  110  is a person talking that is moving closer to the receiver, the playback component  116  can cause the volume of the audio signal to increase as it becomes closer to the receiver  114 . 
     While the system  100  has been described in the example of video games (such that the system can be included in a gaming console), the system  100  may be used in a variety of other applications. For example, the system  100  may be used in connection with a virtual sound studio or karaoke machine. In such an example, the source  110  may be a person that is outputting the audio signal, and such person may desire that the audio sound as if it were being output from a particular location in a certain cathedral. The virtual three-dimensional environment  106  can be representative of the cathedral. The person may then configure the system  100  to cause the audio to sound as if the person is walking down the stairs of the cathedral while a listener is sitting at a certain pew in the cathedral. Another example application of the system  100  may be determining an optimal position of speakers in a stereo system, or a manner in which to output audio that sounds optimal for different listener locations. For instance, the virtual three-dimensional environment  106  can represent a room and a source of sound can be a speaker in such room. A sensor can be coupled to the listener to ascertain location of a listener in the room (e.g., a sensor in a person&#39;s watch, etc.) As the listener moves about the room, the location determiner component  112  can update the respective location of the listener in the virtual three-dimensional environment  106 , and the playback component  116  can automatically modify audio to be transmitted from the speakers such that the audio will have optimal sound quality as perceived by the listener. 
     In still yet another example application, the system  100  may be utilized in connection with a telephone conferencing system. The three dimensional virtual environment  106  can represent a room in which a telephone is positioned, and the location of such telephone can be the location of the source  110  in the virtual three-dimensional environment  106 . Again, the listener can have a sensor corresponding thereto that indicates position in the room of the listener (and thus position of the receiver  114  in the virtual three-dimensional environment  106 ). The playback component  116  can automatically modify audio to be transmitted from the telephone to cause the audio to be perceived by the listener as being clear as the listener moves about the room. Still further, the system  100  may be employed in a mobile computing device, a personal computer, or other suitable computing device. Other applications will be contemplated and are intended to fall under the scope of the hereto-appended claims. 
     Moreover, in an example, the system  100  can be configured to automatically modify sounds from sources in adjacent virtual three-dimensional environments. For example, the virtual three-dimensional environment  106  may be a room, and the pre-computed data file  104  may pertain to such room. A separate three-dimensional data file can be computed for an adjacent room (a different virtual three-dimensional environment). To propagate an audio file from the adjacent room, the audio file can be modified as it would sound to a receiver at an exit point of the adjacent room (and an entry point of the virtual three-dimensional environment  106 ). Such modified audio signal can then be treated as the arbitrary audio signal being emitted from the entry point of the virtual three-dimensional environment  106  (the exit point from the adjacent room). The pre-computed data file  104  can be accessed by the playback component  116 , which can propagate the audio signal as if the source were at the aforementioned entry point and the receiver were at a determined receiver location. 
     Referring now to  FIG. 2 , an example depiction  200  of a virtual three-dimensional environment  202  is illustrated. The virtual three-dimensional environment  202  can be partitioned into a plurality of cells  204 - 210 . In an example, the virtual three-dimensional environment  202  may be representative of a certain room in a building, and various aspects pertaining to the virtual three-dimensional environment  202  may be specified by a designer of such environment  202 . For instance, type of materials used for walls can be specified, thickness of walls can be specified, location and type of furniture can be specified, materials included in the furniture can be specified, amongst other suitable data pertaining to audio absorption/reflection. Furthermore, while the virtual three-dimensional environment  202  is shown as being cubical in nature, it is to be understood that the virtual three-dimensional environment may be or include any suitable shape. Moreover, while the virtual three-dimensional environment  202  is shown as being partitioned into four cells, it is to be understood that a virtual three-dimensional environment may be partitioned into any suitable number of cells, and the cells may be equivalently sized and shaped or of different sizes and shapes. 
     As indicated above, a wave-based numerical simulation (a numerical simulation that is based at least in part upon the Linear Acoustic Wave Equation) can be undertaken with respect to a plurality of source locations and a plurality of receiver locations in a virtual three-dimensional environment. In the example depicted in  FIG. 2 , a source  212  of a sample audio signal can be located in the first cell  204 . During execution of the numerical simulation, response signals can be computed at receivers  214 - 218  in other cells of the virtual three-dimensional environment  202  (as well as at the source location). For instance, response signals can be generated at receiver locations in each cell of the virtual three-dimensional environment or from a subset of cells in the virtual three-dimensional environment. Pursuant to an example, the numerical simulation may be configured to simulate the source  212  outputting a sample signal from the first cell  204  to receivers in the first cell  204 , second cell  206 , the third cell  208 , and the fourth cell  210 , respectively. Accordingly, response signals pertaining to the sample audio signal simulated as being output by the source  212  can be generated for receiver locations at each of the cells  204 ,  206 ,  208  and  210 . Thereafter, such receiver locations can be sampled, for instance, to reduce an amount of storage space utilized in connection with storing the data file  104  ( FIG. 1 ). In another example, such sampling of cells can be undertaken prior to the simulation of the source  212  being configured to output the sample audio signal. 
     The virtual three-dimensional environment  202  may be generated through any suitable mechanism. For instance, the virtual three-dimensional environment  202  may be generated by a game developer in connection with designing a video game. In another example, the virtual three-dimensional environment  202  can be automatically generated through utilization of sensors that sense location of objects in a room (e.g., sonar sensors or other suitable sensors). In still yet another example, the virtual three-dimensional environment  202  can be created based at least in part upon one or more images of a static scene. 
     Referring now to  FIG. 3 , an example system  300  that facilitates pre-computing a data file (e.g., the data file  104 ) that can be used in connection with propagating audio in real time with dynamic sources/receivers is illustrated. The system  300  includes a generator component  302  that is configured to generate the data file  104  that is retained in the data repository  102 . The generator component  302  comprises a numerical simulator  304 , which can be an acoustic simulator that utilizes the wave equation to simulate response signals at various receiver locations with respect to a sample signal output from one or more source locations in the virtual three-dimensional environment  106 . The numerical simulator  304  receives a plurality of data pertaining to the virtual three-dimensional environment  106 , including but not limited to geometry of the virtual three-dimensional environment  106 , absorption parameters pertaining to the virtual three-dimensional environment  106 , grid resolution of the virtual three-dimensional environment  106  (cell distribution), a sample signal desirably output by the source  110 , and a desired location of the source  110  in the virtual three-dimensional environment  106 . Additionally, constraints on frequencies simulated by the numerical simulator  304  can be received. 
     The numerical simulator  304  can be configured to execute a first numerical simulation with a sample audio signal when the source  110  is positioned at approximately a center of the virtual three-dimensional environment  106 . This simulation can be referred to herein as an “oracle” simulation. Results of the oracle simulation executed by the numerical simulator  304  can be utilized in connection with selecting source locations of subsequent simulations executed by the numerical simulator  304  and determining a split between an early reflection phase of a response signal and a late reverberation phase of a response signal. As will be described in greater detail below, the late reverberation phase of a response signal in the oracle simulation can be retained and utilized as the late reverberation phase of every response signal for every simulation undertaken with respect to the virtual three-dimensional environment  106 . For instance, the human ear cannot perceive a great difference between late reverberation phases of an audio signal emitted from different source locations in a same room. Therefore, a single late reverberation phase determined in the oracle simulation can be utilized as an estimate for late reverberation phases of simulated response signals for different source and receiver locations in a virtual three-dimensional environment. This can effectively reduce computation time utilized to generate the data file  104  ( FIG. 1 ) as well as memory utilization at runtime. It is to be understood, however, that late reverberation phases can be computed for various source locations and/or various receiver locations if desired (e.g., if time needed to generate the data file  104  is not a concern). 
     As indicated above, the oracle simulation can be utilized to determine a plurality of source locations for subsequent simulations. Such source locations, in an example, can be chosen based on k-means clustering of early decay time derived from the initial simulation undertaken by the numerical simulator  304 . Early decay time is a standard room acoustic metric that quantifies how fast sound decays when emitted from different room locations. In another example, a uniform sampling of cells in the virtual three-dimensional environment  106  at a suitable down-sampled resolution relative to the simulation grid can be undertaken to determine the plurality of source locations for subsequent simulations. The oracle simulation can also be employed to determine a time duration of a response signal that needs to be simulated at the various source locations. Pursuant to an example, the oracle simulation can be utilized of to capture an entirety of the acoustic response in the virtual three-dimensional environment  106  at various receiver locations in the virtual three-dimensional environment  106  (e.g., at each cell). Pursuant to an example, an input signal provided to the numerical simulator  304  can be a pulse, such as a Gaussian derivative pulse of unit amplitude given by the following equation: 
                 s   ⁡     (   t   )       =         ⅇ     σ     ⁢     (     t   -     5   ⁢   σ       )     ⁢     exp   ⁡     (     -         (     t   -     5   ⁢   σ       )     2       σ   2         )           ,         
where
 
               σ   =     1     2   ⁢   π   ⁢           ⁢   v         ,         
and where v=500. The Fourier transform of this function is a Gaussian with center at 500 Hz and width spanning an entire frequency range from 0 to 1 kHz, for example.
 
     In another example, the simulation grid can have a resolution of approximately 12 centimeters (e.g., the virtual three-dimensional environment  106  can be partitioned into twelve centimeter cubes). Since humans do not perceive sound variation at such high spatial resolution, simulation results can be down-sampled by a factor of 2 to 3, to reduce runtime memory and computational requirements. As indicated above, only an early reflection phase of a response signal at a receiver location need be retained, as the late reverberation phase can be estimated for all response signals using the oracle simulation (as will be described in greater detail herein). 
     In an example, the numerical simulator  304  can cause a response of the virtual three-dimensional environment  106  to be retained as a band-limited Gaussian derivative (rather than a true impulse response). This Gaussian derivative can be converted to an impulse response by way of a simple computation. In the following examples, all functions are discrete vectors of samples in time or frequency, but continuum notation is utilized for the sake of brevity. If an actual response at a receiver at a particular cell can be given by a function l(t) and a corresponding ideal impulse response by I(t) using   to denote convolution, · to denote element-wise multiplication, and {circumflex over (x)} to denote the Fourier transform of x, the following can be obtained:
 
 l ( t )= s ( t )   I ( t ) {circumflex over ( l )}( f )={circumflex over ( s )}( f )·{circumflex over ( I )}( f )
 
To solve for the impulse response, deconvolution can be undertaken using a frequency coefficient division to obtain the Fourier transform of the impulse response, called the Frequency Response (FR).
 
     
       
         
           
             
               
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     Naively, an inverse Fast Fourier Transform (FFT) on the frequency response Î(f) can yield I(t). Before performing the inverse FFT, a low pass filter can be executed over the frequency response to eliminate frequencies above a particular threshold (e.g., 1 kHz), since such frequencies may be outside a range of the numerical simulator  304  and thus may include numerical errors. In an example, a frequency response vector can be zero padded in all frequency bins above the threshold frequency (e.g., up to a target rate of a certain frequency). In another example, the frequency response can be windowed, which involves attenuating frequencies well before reaching the aforementioned threshold frequency. This can reduce ringing artifacts in the time domain. The impulse response for each receiver location in the virtual three-dimensional environment  106  can be obtained by performing an inverse FFT on the windowed frequency response. Pursuant to an example, the following window function chosen from the so-called cos a (x) class can be utilized: 
                 w   ⁡     (   n   )       =       ∑     k   =   0     3     ⁢           ⁢         (     -   1     )     k     ⁢     a   k     ⁢   cos   ⁢       2   ⁢   π   ⁢           ⁢   kn     N           ,     n   ∈     [     0   ,     N   -   1       ]                     a   =     [     0.355768   ,   0.487396   ,   0.144232   ,   0.012604     ]       ,         
where N is a number of frequency bins from zero to the threshold frequency (e.g., 1 kHz). Frequency values outside such range may already be zero, as discussed above. While the above window function has been given as an example, it is to be understood that any suitable window function can be employed. For instance, a simple rectangular window function can be utilized.
 
     The generator component  302  may further include an encoder component  306  that can be employed to compress/factor response signals obtained via numerical simulation undertaken by the numerical simulator  304 . Additional detail pertaining to the compression and factoring of response signals is described in greater detail below. The compressed response signals can be stored in the data file  104 , which can be utilized in connection with propagating audio with dynamic sources and/or receivers. 
     Now referring to  FIG. 4 , an example depiction of the encoder component  306  is illustrated. The encoder component  306  is configured to ascertain the length of the early reflection phase of the impulse response for the oracle simulation and a length of the late reverberation phase of the impulse response with respect to the oracle simulation undertaken by the numerical simulator  304 . For instance, the oracle simulation can be undertaken to generate an initial response signal when the source is located at the centroid of the virtual three-dimensional environment and the receiver is also located at the centroid of the virtual three-dimensional environment. A peak detector component  402  is configured to detect peaks in the initial response signal. The peak detector component  402  searches for local maxima at each sample by testing against its two neighboring samples in time. If a sample in consideration is indeed a local maximum, the peak detector component  402  registers a peak at the current sample number with amplitude equaling the amplitude of the response signal at such point. With respect to the oracle simulation, the peak detector component  402  can register a relatively high number of highest amplitude peaks, such as between one hundred and two hundred peaks with highest amplitude amongst all detected peaks in the response signal. 
     A partitioner component  404  can be configured to determine a length of the early reflection phase in the response signal and, thus, an onset of the late reverberation phase in the response signal. The peaks extracted by the peak detector component  402  can be utilized by the partitioner component  404  to infer the RT60 of the virtual three-dimensional environment  106 , which is representative of a reverberation time, which is the time it takes for a sound field to decay by 60 decibels from the initial level of the sound field. To compute LT60, the impulse response can be transformed from I(t) to C(t)=10 log 10 (I 2 (t)). A least-squares line can be fit to C(t) and the RT60 can be computed as t IR =−60/s, where s is the slope of the line. The impulse response (IR) can then be truncated to this length. 
     To compute the length of the early reflection phase, a peak density threshold of τ=500 peaks per second can be employed. The highest 100 to 200 amplitude peaks (registered by the peak detector component  402 ) in the impulse response can be selected, and a sliding window of a threshold time (e.g., ten milliseconds) can be employed to find the time (late reverberation onset time) when the number of peaks within such window falls below τ/100. This can yield the length of the early reflection phase in the impulse response (t ER ). All peaks in the truncated impulse response prior to the onset time of the late reverberation phase can be removed, and the resulting signal can be stored as the late reverberation phase for use at runtime. Again, this late reverberation signal can be utilized as an estimate for each impulse response at various source locations and/or receiver locations in the virtual three-dimensional environment  106 . Of course, if computation time pertaining to execution of the numerical simulator  304  is not a concern, then an impulse response that includes both the early reflection phase and the late reverberation phase can be computed for each source location/receiver location pair simulated by the numerical simulator  304 . 
     An example method for determining which locations in the virtual three-dimensional environment the numerical simulator  304  is to simulate as source locations will now be described. This method is provided to serve as an example, and is not intended to be limiting. For instance, the numerical simulator  304  can be configured to exhaustively simulate source/receiver locations in the virtual three-dimensional environment  106 . In another example, subsampling can be employed to determine locations of sources utilized by the numerical simulator  304 . In still yet another example, a random or pseudo-random function can be employed in connection with selecting sources for simulation. 
     The oracle simulation undertaken by the numerical simulator  304  can yield impulse responses (e.g., up to t ER ) over a subsampled grid in the virtual three-dimensional environment  106  when the source is at the centroid of the virtual three-dimensional environment  106 . These impulse responses can be clustered using a similarity measure based on the early decay time or the time it takes for an impulse response to decay by 10 decibels. Early decay times can vary significantly within a room. A distance metric can be defined as D(x 1 , x 2 )=√{square root over (∥x 1 −x 2 ∥ 2 +(t 1 −t 2 ) 2 )}, and can be utilized to compute a distance (similarity) between two impulse responses at different receiver locations (x) with the respective decay times of the two impulse responses. 
     Clustering can then be undertaken, using a k-means algorithm, using D as a distance metric between points. The number of cluster points can be user-specified or automatically ascertained. Initial cluster centers can be distributed randomly in the virtual three-dimensional environment  106 . After clustering converges, resulting centers can be stored as representative source locations, and can be utilized by the numerical simulator  304  in subsequent simulations. Additional simulations may then be undertaken by the numerical simulator  304 , and compressed over locations in the virtual three-dimensional environment  106 . The length of the subsequent simulations need only be for the length of the early reflection phase, as determined by the partitioner component  404  (since computed late reverberation impulse response can be used for all source/receiver pairs). 
     In summary, as described above, the numerical simulator  304  may be configured to perform an initial wave-based numeric simulation (e.g., simulating output of a pulse) which generates a response signal (impulse response), wherein the source and the receiver are at the same location (e.g., the center of the virtual three-dimensional environment  106 ). The peak detector component  402  can detect peaks in the response signal, and based at least in part upon the peaks detected in the response signal, the partitioner component  404  can determine a length of an early reflection phase of responses in the virtual three-dimensional environment  106 . Therefore, in subsequent simulations the numerical simulator  304  can be configured to perform the simulation up until the end of the early reflection phase of response signals. 
     Subsequent to the oracle simulation being performed, particular source locations for subsequent simulations can be ascertained, and the numerical simulator  304  can be configured to perform simulations up until the end of the early reflection phase of response signals. In such subsequent simulations, for instance, a source location can be selected, and the numerical simulator  304  can compute response signals for sub-sampled cell locations in the virtual three-dimensional environment  106 . For computed response signals, the peak detector component  402  can detect peaks in such response signals. For instance, the peak detector component  402  can collect a certain threshold number of highest amplitude peaks in a response signal, and cause such highest amplitude peaks to be retained in the data file  104  in the data repository  102 . Such peaks can be determined by the peak detector component  402  for every computed response signal. 
     The encoder component  306  additionally includes a frequency trend determiner component  406  that estimates frequency trends for a particular source location/receiver location pair (for every response signal) based at least in part upon the peaks detected by the peak detector component  402  for a response signal. The frequency trend determiner component  406  can determine such a frequency trend by comparing the frequency response pertaining to the response signal computed during the simulation with the frequency response pertaining to the peaks extracted by the peak detector component  402  (e.g., the frequency response of a compressed impulse response). A transformer component  408  can execute a FFT to generate the frequency response of the simulation performed by the numerical simulator  304  and the frequency response pertaining solely to the peaks detected by the peak detector component  402 . Substantial differences between such frequency responses can indicate the presence of low pass filtering due to diffraction. 
     The response signal of the extracted peaks I′ can be constructed by summing over all peaks i with delays t i  and amplitudes a i :
 
 I′=Σ   i=1   N   a   i δ( t−t   i ),
 
where δ(t) is the analog of the signal input to the numerical simulator  304  (e.g., a Dirac-Delta function for the discrete case, a pulse of one sample width and unit amplitude). The corresponding frequency response can be denoted by Î′. Such signal can be compared to the frequency response of the uncompressed response signal prior to windowing, denoted Î(f) below. This frequency response may include complete information for the early reflection portion of the response signal up to a threshold frequency (e.g., 1 kHz).
 
     The (complex) amplitude at each frequency bin can be approximated as a product of the interference amplitude (captured by the peak locations and peak amplitudes) and the diffraction amplitude. The overall frequency-dependent diffraction trend can be obtained by way of the following: 
               T   ⁡     (   f   )       =     |         I   ^     ⁡     (   f   )           I   ^     ⁢     ′   ⁡     (   f   )           |           
for f≦the threshold (e.g., 1 kHz). T(f) may exhibit spikes due to instability in the division. Such spikes can be cleaned up with a median filter, using a bin width of 10 to 20 for an early reflection phase that is 100-200 milliseconds long. Also, the occurrence of these spikes can be reduced by perturbing the peak times at sub-millisecond resolution to find a substantially optimal fit between Î(f) and Î′(f). This can be followed by a Gaussian filter of similar width to obtain a smooth trend. The trend can then be normalized such that the trend starts with value 1 and bin 0.
 
     Such trend can contain information related solely to diffraction. To detect if the overall trend is downward, a least-squares line can be fit to T(f). A non-negative slope indicates no significant diffraction. In such a case, no further processing need be performed, and the frequency filter for such pair need not be stored in the data file  104 . Otherwise, the value for T(f) can be stored for each octave band (i.e., if frequency f=60, 125, 250, 500 and 1,000 Hertz). 
     As indicated above, a numerical simulation generated by the numerical simulator  304  may not include useful information above a threshold frequency (1 kHz). This is not a major limitation, because most perceivable diffraction effects are limited to 1 kHz in common acoustic spaces. Above such frequency, high frequency shadowing effect may desirably be captured. This can be undertaken by extrapolating the downward frequency trend, if present, in the mid-frequency range 250≦f≦1,000. A line fit can be performed on the power spectrum log T(f) over the mid-frequency range. This line can thereafter be used to extrapolate the value at 2, 4, 8, 16 and 22 kHz. Finally, the trend values for all octave bands with f=60, 125, 250, 500, 1000, 2000, 4000, 8000, 16,000, 22,000 Hertz can be stored for use at runtime. 
     In summary, the numerical simulator  304  and the encoder component  306  can operate in conjunction as follows: The numerical simulator  304  can be configured to execute the oracle simulation with a relatively long duration. In the oracle simulation, the source and receiver location can be identical. After the initial simulation is executed, the encoder component  306  can be configured to determine an early reflection and late reverberation phase of the response signal (e.g., determine when the late reverberation phase is onset) and store a time that indicates the split between the early reflection and late reverberation phases. Optionally, the late reverberation phase pertaining to such oracle simulation can be retained and used as the late reverberation portion of each subsequently simulated response signal. The impulse response computed during the oracle simulation can also be utilized in connection with selecting source locations for subsequent simulation (up to the onset time of the late reverberation phase). The numerical simulator  304  may then be configured to perform simulations with each of the determined source locations, wherein duration of the simulation is for the aforementioned early reflection time period. The early reflection response periods for points on the subsampled volumetric grid can be compressed and stored with the source location, wherein the compressed early reflection response signal comprises extracted peaks and a frequency trend corresponding to such response signal. To further reduce precomputation time, it can be recognized that a response signal at a receiver location for a particular source location will also be the response signal if the source location and receiver location are switched. 
     Referring now to  FIG. 5 , an example graphical depiction  500  of a response signal obtained during the initial simulation undertaken by the numerical simulator  304  is illustrated. The graphical depiction  500  shows that the response signal includes an early reflection phase  502  and a late reverberation phase  504 . Additionally, the graphical depiction  500  displays the extraction of peaks from the early reflection phase  502  and the late reverberation phase  504 . 
     Turning now to  FIG. 6 , an example graphical depiction  600  of peak detection and frequency trend determination is illustrated. The example depiction  600  comprises a first signal  602 , which can be an early reflection portion of a response signal computed by the numerical simulator  304 . A second signal  604  represents a FFT of the first signal  602 , and is thus a frequency response for a particular source and receiver pair. A third signal  606  represents peaks extracted from the first signal  602 , wherein such peaks indicate time and amplitude of local maxima in the first signal  602 . A fourth signal  608  is a FFT of the third signal  606 . It can be ascertained that the second signal  604  is associated with a particular cutoff frequency. It is desirable to obtain a frequency trend for frequencies above such cutoff frequencies. A fifth signal  610  represents a division of the second signal  604  by the fourth signal  608 . Such division can indicate a frequency trend up to the threshold frequency, and a trend above such threshold frequency can be extrapolated as shown in  FIG. 6 . The combination of the third signal  606  and the frequency trend represented by the fifth signal  610  can be stored as representative of the first signal  602  (a compression of the response signal for the early reflection phase of the response signal). 
     With reference now to  FIG. 7 , an example system  700  that facilitates real-time propagation of an arbitrary audio signal is illustrated. The system  700  comprises the playback component  116 . The playback component  116  receives an arbitrary audio signal, a location of the source of the audio signal, and a location of the receiver of the audio signal in the virtual three-dimensional environment  106 . Responsive to receipt of the source and receiver locations, the playback component  116  accesses the data file  104 . A portion of the data file  104  accessed can be based upon source locations and receiver locations in the data file  104  that are proximate to the received source and receiver locations in the virtual three-dimensional environment  106 . The playback component  116  can include an interpolator component  702  that can interpolate data between two or more portions of the data file  104 . For instance, if the source location in the virtual three-dimensional environment  106  is between two source locations that were subject to simulation by the numerical simulator  304 , the interpolator component  702  can access portions of the data file pertaining to the two known source locations and can interpolate such portions of the data file to accord to the received location in the virtual three-dimensional environment  106 . This can also be undertaken for various receiver locations. 
     The playback component  116  can perform a FFT on the received audio signal and can perform a FFT on the interpolated data. A convolution engine  704  may then be configured to convolve the audio signal with the interpolated data. Performing computing operations on signals in the frequency domain allows for real-time modification of the audio signal. The resulting audio signal can be output via a speaker to a listener. 
     In more detail, as the audio signal is received, it can be placed in, for instance, two buffers. Once the audio signal is placed in the frequency domain, the audio signal in the two buffers can be convolved with the current interpolated response signal (as generated by the interpolator component  702 ). The audio in the second buffer can be retained and used in connection with interpolating a subsequent signal. 
     With reference now to  FIGS. 8-10 , various example methodologies are illustrated and described. While the methodologies are described as being a series of acts that are performed in a sequence, it is to be understood that the methodologies are not limited by the order of the sequence. For instance, some acts may occur in a different order than what is described herein. In addition, an act may occur concurrently with another act. Furthermore, in some instances, not all acts may be required to implement a methodology described herein. 
     Moreover, the acts described herein may be computer-executable instructions that can be implemented by one or more processors and/or stored on a computer-readable medium or media. The computer-executable instructions may include a routine, a sub-routine, programs, a thread of execution, and/or the like. Still further, results of acts of the methodologies may be stored in a computer-readable medium, displayed on a display device, and/or the like. 
     Referring now to  FIG. 8 , a methodology  800  that facilitates automatically propagating an audio signal in real time in an environment with dynamic sources and/or receivers is illustrated. The methodology  800  begins at  802 , and at  804  a virtual three-dimensional environment is received. The three-dimensional environment may include geometry pertaining to the environment, absorption parameters pertaining to the environment, amongst other data. 
     At  806  a numerical simulation is executed in the virtual three-dimensional environment, using a sample signal from a first source location in the virtual three-dimensional environment and received at a first receiver location in the virtual three-dimensional environment. In an example, the first source location and the first receiver location can be identical. 
     At  808 , a late reverberation portion of a response signal is located, wherein such response pertains to the sample signal utilized by the numerical simulator. At  810  the late reverberation signal is utilized in connection with automatically playing back (propagating) an arbitrary audio signal, as has been described above. The methodology  800  completes at  812 . 
     Now turning to  FIG. 9 , an example methodology  900  that facilitates utilizing extracted peaks in connection with automatically playing back an audio signal is illustrated. The methodology  900  starts at  902 , and at  904  a virtual three dimensional environment is received. At  906 , a numerical simulation is executed using a sample audio signal over a plurality of source locations and receiver locations. 
     At  908 , for a particular source location and receiver location, an early reflection portion of a response is generated. At  910 , peaks are extracted from the early reflection portion of the response signal. 
     At  912 , a frequency trend is determined based at least in part upon the extracted peaks, and at  914  the extracted peaks are utilized with the frequency trend in connection with automatically playing back an audio signal (propagating the audio signal in real time, given moving sources/receivers). The methodology  900  completes at  914 . 
     With reference now to  FIG. 10 , an example methodology  1000  that facilitates modifying audio in real-time through utilization of a pre-computed data file is illustrated. The methodology  1000  starts at  1002 , and at  1004  an audio signal is received. At  1006 , a first location is received, wherein the first location is a desired location of a source of the audio signal in a virtual three-dimensional environment. 
     At  1008 , a second location is received, wherein the second location is a desired location of a receiver of the audio signal in the virtual three-dimensional environment. At  1010 , a precomputed data file is accessed responsive to receipt of the first location and the second location, wherein the precomputed data file is based at least in part upon computed response signals with respect to a sample signal emitted from the source from a plurality of source locations and to a plurality of receiver locations in the three-dimensional environment. The methodology  1000  completes at  1012 . 
     Now referring to  FIG. 11 , a high-level illustration of an example computing device  1100  that can be used in accordance with the systems and methodologies disclosed herein is illustrated. For instance, the computing device  1100  may be used in a system that supports propagating a signal in real time, given moving sources/receivers in a virtual three-dimensional environment. In another example, at least a portion of the computing device  1100  may be used in a system that supports determining when for a particular environment an early reflection phase begins and a late reverberation phase begins in a response signal. The computing device  1100  includes at least one processor  1102  that executes instructions that are stored in a memory  1104 . The instructions may be, for instance, instructions for implementing functionality described as being carried out by one or more components discussed above or instructions for implementing one or more of the methods described above. The processor  1102  may access the memory  1104  by way of a system bus  1106 . In addition to storing executable instructions, the memory  1104  may also store a data file such as a data file generated by the generator component discussed above. 
     The computing device  1100  additionally includes a data store  1108  that is accessible by the processor  1102  by way of the system bus  1106 . The data store  1108  may include executable instructions, a data file which includes compressions of response signals, etc. The computing device  1100  also includes an input interface  1110  that allows external devices to communicate with the computing device  1100 . For instance, the input interface  1110  may be used to receive instructions from an external computer device, an audio signal from an interface device such as a microphone, etc. The computing device  1100  also includes an output interface  1112  that interfaces the computing device  1100  with one or more external devices. For example, the computing device  1100  may display text, images, etc. by way of the output interface  1112 . 
     Additionally, while illustrated as a single system, it is to be understood that the computing device  1100  may be a distributed system. Thus, for instance, several devices may be in communication by way of a network connection and may collectively perform tasks described as being performed by the computing device  1100 . 
     As used herein, the terms “component” and “system” are intended to encompass hardware, software, or a combination of hardware and software. Thus, for example, a system or component may be a process, a process executing on a processor, or a processor. Additionally, a component or system may be localized on a single device or distributed across several devices. 
     It is noted that several examples have been provided for purposes of explanation. These examples are not to be construed as limiting the hereto-appended claims. Additionally, it may be recognized that the examples provided herein may be permutated while still falling under the scope of the claims.