Patent Publication Number: US-9837064-B1

Title: Generating spectrally shaped sound signal based on sensitivity of human hearing and background noise level

Description:
TECHNICAL FIELD 
     The present disclosure relates to generating a spectrally shaped sound signal based on the sensitivity of human hearing and background noise levels. 
     BACKGROUND 
     A video conference system includes an endpoint device that exchanges audio-visual information with participants and their personal/user devices, such as smartphones, laptops, and the like, in a room during a conference session and transmits/receives such audio-visual information over a network to/from remote endpoint devices. Identifying those participants and their user devices that are in physical proximity to the endpoint device helps setup the conference session. “Pairing” is a means by which the endpoint device and each user device can ensure that they are in physical proximity to each other. Once the endpoint device and a given user device are paired, they may share confidential information during the conference session over a primary, secure (e.g., encrypted) channel between the devices. In one conventional pairing technique, the endpoint device generates and then transmits an ultrasonic signal as a proximity probe to user devices over a secondary channel. A disadvantage of this technique is that many user devices are not ultrasound capable, i.e., not configured to receive and process the ultrasound signal. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an illustration of a video conference (e.g., teleconference) endpoint device deployed in a room and in which embodiments directed to spectrally shaping a sound signal (e.g., a pairing signal) for transmission by the endpoint device may be implemented, according to an example embodiment. 
         FIG. 2  is block diagram of a controller of the video conference endpoint, according to an example embodiment. 
         FIG. 3  there is a block diagram of the endpoint device showing details of transmit (TX) and receive (RX) paths of the endpoint device, according to an embodiment. 
         FIG. 4  is an illustration of a frame format for a sound signal transmitted from the endpoint device, according to an example embodiment. 
         FIG. 5  shows predetermined models or curves for auditory thresholds of human hearing (i.e., frequency responses or sensitivities of human hearing) as developed by various audio standards bodies and that may be used by the endpoint device. 
         FIG. 6  shows a spectrally shaped sound signal produced by the endpoint device when the background noise levels in the room follow a “weak” pink noise spectral distribution, according to an example embodiment. 
         FIG. 7  shows a shaped frequency spectrum of a sound signal produced by the endpoint device when the background noise levels in the room follow a “strong” pink noise spectral distribution, according to an example embodiment. 
         FIG. 8  is an illustration of a static frequency response for a shaping filter of a spectral shaper in the endpoint device, according to an example embodiment. 
         FIG. 9  is a block diagram of a receiver capable of receiving and processing/decoding the sound signal transmitted by the endpoint device, according to an example embodiment. 
         FIG. 10  is a flowchart of a summary method of generating spectrally shaped sound performed by the endpoint device. 
     
    
    
     DESCRIPTION OF EXAMPLE EMBODIMENTS 
     Overview 
     An embodiment is implemented in a communication device having a loudspeaker to transmit sound into a room. A signal having a white noise-like frequency spectrum spanning a frequency range of human hearing is generated. Auditory thresholds of human hearing for frequencies spanning the frequency range are stored. Respective levels of background noise in the room at the frequencies are determined. The white noise-like frequency spectrum is spectrally shaped to produce a shaped frequency spectrum having, for each frequency, a respective level that follows either the auditory threshold or the level of background noise at that frequency, whichever is greater. The shaped frequency spectrum is transmitted from the loudspeaker into the room. 
     Example Embodiments 
     With reference to  FIG. 1 , there is an illustration of a video conference (e.g., teleconference) endpoint (EP) device  100  (referred to simply as “endpoint”  100 ) in which embodiments directed to spectral (i.e., frequency spectrum) shaping of a sound signal transmitted by the endpoint device may be implemented. By way of example, endpoint  100  is depicted as being deployed in a room  101  (depicted simplistically as an outline) alongside a user  102  of the endpoint. Endpoint  100  is configured to establish audio-visual teleconference collaboration sessions with other video conference endpoints over a communication network (not shown in  FIG. 1 ). User  102  may be quipped with a user device  103  to communicate with endpoint  100  proximate the user device over wired or wireless communication links with the endpoint. The term “proximate” means co-located at the same geographical location and within acoustic communication range. Typically, a user device is considered proximate a video conference endpoint when the two occupy the same room. User device  103  may be a wired or a wireless communication device capable of receiving, processing, storing, and/or communicating with endpoint  100 , and may include, but are not limited to laptop and tablet computers, a smartphone, and the like. 
     Endpoint  100  may include a video camera (VC)  112 , a video display  114 , a loudspeaker  116  to transmit sound into room  106 , and a microphone  118  to detect sound in the room. Loudspeaker  116  and microphone  118  may respectively transmit and detect sound in the frequency range of human hearing, i.e., in the range of frequencies perceptible to the human ear, typically considered to be in the frequency range of 0-22.5 KHz. Loudspeaker  116  and microphone  118  may also operate at higher frequencies considered to be in the ultrasound frequency range. Microphone  118  may be integrated with endpoint  100  as shown in the example of  FIG. 1 , or may be positioned in room  101  at approximate locations of the user(s). Endpoint  100  may be a wired or a wireless communication device equipped with the aforementioned components, such as, but not limited to laptop and tablet computers, a smartphone, and the like. In a transmit direction, endpoint  100  captures sound/video from user  102  with microphone  118 /VC  112 , processes the captured sound/video into data packets, and transmits the processed data packets to other endpoints. In a receive direction, endpoint  100  decodes sound/video from data packets received from the other endpoints and presents the sound/video to user  102  via loudspeaker  116 /display  114 . 
     According to embodiments presented herein, endpoint  100  transmits into room  101  a sound signal  130  that may be used for pairing with user device  103 , in which case the sound signal is referred to as a “pairing” signal. Sound signal  130  may convey/carry information to user device  103 . For reasons that will be apparent from the description below, sound signal  130  may also be referred to as a “shaped” sound signal. Ideally, sound signal  130  has (i) a frequency spectrum that spans at least portions of the frequency range of human hearing so that user device  103  need only be equipped with a conventional sound microphone to detect the sound signal, and (ii) a level (i.e., sound level) that is as high as possible without being noticeable to user  102 , so as not to irritate or distract the user. To achieve these goals, endpoint  100  generates sound signal  130  so that it has content across a frequency spectrum that spans at least a substantial portion of the frequency range of human hearing. In one example, the frequency spectrum spans the full range of human hearing. In another example, the frequency spectrum spans a more limited range from approximately 20 or 50 Hz up to approximately 18 or 20 KHz, although other examples of limited ranges are possible. In addition, endpoint  100  shapes (i.e., spectrally shapes) the frequency spectrum so that, at each frequency thereof, a level of the sound signal is approximately equal to either (i) a sound level of background noise detected in the room, or (ii) a sound threshold of human hearing (referred to as an auditory threshold of human hearing), whichever is greater. 
     Mathematically, endpoint  100  spectrally shapes sound signal  130  as a function of frequency f according to the following equation: output power(f)=max{noise power(f), hearing threshold(f)}. Where output power(f) is the power of sound signal  130  at frequency f, noise power(f) is an estimated power of the background noise in room  101  at frequency f, and hearing threshold(f) is the auditory threshold (i.e., sensitivity level) of human hearing at the frequency f. Such frequency-dependent shaping maximizes the level of sound signal  130  across the frequency range of human hearing, while rendering the sound signal largely imperceptible to human hearing because the level is either (i) substantially masked/hidden by the background noise if the background noise level exceeds the threshold of human hearing, or (ii) no higher than the threshold of human hearing if the threshold of human hearing exceeds the background noise level. 
     Reference is now made to  FIG. 2 , which shows an example block diagram of a controller  200  of endpoint  100  configured to implement the embodiments presented herein. There are numerous possible configurations for controller  200  and  FIG. 2  is meant to be an example. Controller  200  includes a network interface (I/F) unit (NIU)  242 , a processor  244 , and memory  248 . NIU  242  is, for example, an Ethernet card or other interface device having a connection port and that allows the controller  200  to communicate over a communication network via the connection port. NIU  242  may include wired and/or wireless connection capability. In a wireless embodiment, NIU  242  includes a wireless transceiver and an antennal to transmit and receive wireless communication signals to and from the communication network. 
     Processor  244  may include a collection of microcontrollers and/or microprocessors, for example, each configured to execute respective software instructions stored in the memory  248 . The collection of microcontrollers may include, for example: a video controller to receive, send, and process video signals related to display  114  and video camera  112 ; a sound processor to receive, send, and process sound signals related to loudspeaker  116  and microphone (MIC)  118 ; and a high-level controller to provide overall control. Portions of memory  248  (and the instruction therein) may be integrated with processor  244  and the aforementioned video and sound controllers. In the transmit direction, processor  244  prepares sound/video captured by microphone  118 /VC  112  for transmit, and causes the prepared data packets to be transmitted to the communication network. In a receive direction, processor  244  processes sound/video from data packets received from the communication network and causes the processed sound/video to be presented to local participant  102  via loudspeaker  116 /display  114 . Processor  244  also performs sound signal processing to implement embodiments directed to generating and spectral shaping of sound signal  130  as described herein. As used herein, the terms “audio” and “sound” are synonymous and interchangeably. 
     The memory  248  may comprise read only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical, or other physical/tangible (e.g., non-transitory) memory storage devices. Thus, in general, the memory  248  may comprise one or more computer readable storage media (e.g., a memory device) encoded with software comprising computer executable instructions and when the software is executed (by the processor  244 ) it is operable to perform the operations described herein. For example, the memory  248  stores or is encoded with instructions for a spectral shaping encoder  250  to generate the above-mentioned spectrally shaped sound signal, and a decoder  252  to decode sound. 
     In addition, memory  248  stores data  254  used and generated by spectral shaping encoder  350 , including, but not limited to human hearing auditory thresholds, noise level estimates, filter coefficients, and detected sound samples, as described below. 
     With reference to  FIG. 3 , there is a block diagram of endpoint  100  as deployed in room  102  showing details of a transmit (TX) path  301  and a receive (RX) path  302  of the endpoint, according to an embodiment. Transmit path  301  includes: spectral shaping encoder  250  to convert a digital signal  304  to a spectrally shaped, digitized sound signal  306  (which is a digitized representation of sound signal  130 ); a digital-to-analog (D/A) converter  308  following the spectral shaping encoder to convert digitized, spectrally shaped signal  306  to an analog or continuous-time signal; a reconstruction filter  310  following the D/A to filter the analog signal and provide a filtered version thereof to loudspeaker  116 ; and loudspeaker  116  to transmit the filtered signal into room  102  as sound signal  130 . Receive path  302  includes: microphone  118  to detect sound in room  102 ; an anti-aliasing filter  312  to filter the detected sound; an analog-to-digital (A/D) converter  314  to convert the filtered, detected sound to a digitized sound signal  316  and to provide the digitized sound signal to spectral shaping encoder  250  and decoder  252 ; and decoder  252  to decode the digitized, detected sound signal. 
     In transmit path  301 , spectral shaping encoder  250  includes a signal generator  320  (also referred to as a “core encoder”  320 ), a spectral shaper  322 , and a spectral shaper controller  324 . In the non-limiting example of  FIG. 3 , spectral shaping encoder  250  operates in the digital domain; however the signal processing components of the encoder may be implemented in analog circuitry. Signal generator  320  receives digital signal  304 , e.g., a series of bits, and generates a (perceptually) white noise-like, information-carrying, signal  326  into which the bits are encoded, and which, once spectrally shaped, provides robust digital communication through a noisy and convolutive distorted channel. White noise-like signal  326  has a substantially flat (i.e., constant level) frequency spectrum spanning substantially the full frequency range of human hearing. In an example, signal generator  320  may generate signal  326  using a direct spread spectrum technique, e.g., using a binary non-return-to-zero (NRZ) encoded maximum-length sequence (MLS) for spreading a payload portion of signal  326  that carries information and a preamble portion of signal  326  that may be used for convolutive channel estimation at a decoder that receives the signal. A frame format of signal  326  including both of the preamble and payload portions is described below in connection with  FIG. 4 . 
     Following signal generator  320 , spectral shaper  322  shapes the white noise-like spectrum of signal  326  based on a control signal  330  generated by spectral shaper controller  324  in the manner described below, to produce spectrally-shaped digitized sound signal  306  representative of sound signal  130 . More specifically, spectral shaper  322  shapes the white noise-like frequency spectrum of sound signal  326  to produce a shaped frequency spectrum (of sound signal  306 ) having, for each frequency across the frequency range, a respective level that follows either (i) an auditory threshold of human hearing at that frequency, or (ii) a level of background noise at that frequency, whichever is greater. In other words, spectrally shaped sound signal  306  has a sound level that follows the greater of either the auditory threshold of human hearing or the level of background noise across the frequency range. 
     Following spectral shaper  322 , D/A  308  and reconstruction filter  310  transform sound signal  306  to sound signal  130  such that sound signal  130  has substantially the same shaped frequency spectrum as sound signal  306 . 
     In an embodiment, spectral shaper  322  includes a spectral shaping filter, such as a Finite Impulse Response (FIR) filter or an Infinite Impulse Response (IIR), having a frequency response that spectrally shapes white noise-like signal  326 . Spectral shaper  322  may also include a programmable gain stage in series with the shaping filter to set a gain of the spectral shaper. This gain allows a perceptually sensible either increase of communication robustness or decrease of audibility through a single scalar parameter. The frequency response of the shaping filter may be determined by a set of filter coefficients generated by spectral shaper controller  324  and provided to the shaping filter via control signal  330 , i.e., control signal  330  includes the filter coefficients derived by the spectral shaper controller. As described below, spectral shaper controller  324  derives the filter coefficients based in part on noise detected in room  101  and, therefore, the controller changes the filter coefficients responsive to detected noise changes. This in turn adapts the shaping filter to accommodate the noise changes. In this way, the shaping filter may be an adaptive shaping filter and the filter coefficients may be adaptive filter coefficients. 
     Spectral shaper controller  324  includes a spectral noise estimator  340 , a human hearing auditory thresholds model  342 , a maximum level selector  346 , and a filter synthesizer  350  that cooperate to generate spectral shaping control signal  330  based on background noise in room  102  as detected by microphone  118  and the human hearing auditory threshold model, as is now described. Spectral noise estimator  340  receives detected sound signal  316  and estimates frequency-dependent noise levels in the detected sound signal, which are representative of background noise levels in room  102 . More specifically, spectral noise estimator  340  estimates respective (sound) levels of noise at frequencies (e.g., at frequency points, or in frequency bins/narrow frequency subbands) across the frequency range of human hearing. Any known or hereafter developed technique for estimating noise may be used. For example, in one embodiment, spectral noise estimator  340  may (i) convert sound signal  316  to a frequency spectrum spanning the frequency range of human hearing using a Fast Fourier Transform (FFT), for example, and (ii) estimate a respective (sound) level of noise for each frequency of the frequency spectrum, e.g., in each frequency bin/narrow frequency subband of the FFT, across the frequency range. In an embodiment, spectral noise estimator  340  may use a so-called “minimum-statistics” method of estimating the sound level, which is robust against non-stationary speech. Spectral noise estimator  340  provides the estimated levels of noise for the corresponding frequencies to maximum level selector  346 . 
     Human hearing auditory thresholds model  342  (also referred to simply as “auditory thresholds” model  342 ) stores a model or plot/curve of a frequency response of human hearing, i.e., auditory thresholds of human hearing across the frequency range of human hearing. For example, auditory thresholds model  342  may include a respective auditory threshold of human hearing for each frequency (or narrow frequency subband) of the frequency range of human hearing. Auditory thresholds model  342  provides the respective auditory thresholds for the frequencies to maximum level selector  346 . Candidate models or plots that may be used for the auditory thresholds of human hearing are described below in connection with  FIG. 5 . 
     Maximum level selector  346  compares, at each frequency across the frequency range of human hearing, the estimated noise level (from spectral noise estimator  340 ) against the auditory threshold (from auditory threshold model  342 ) corresponding to that frequency and, based on the comparison, selects either the estimated noise level or the auditory threshold, whichever is greater (i.e., selects the maximum level of the estimated noise level and the auditory threshold). Maximum level selector  346  outputs to filter synthesizer  350  the selected maximum level for each frequency across the frequency range. The selected maximum levels across frequency that are output by maximum selector  346  represent a spectral shape (i.e., level vs. frequency) to be imposed on the white noise-like frequency spectrum of sound signal  326  by spectral shaper  322  such that the resulting spectral shape of sound signal  306 / 130  matches or follows the spectral shape output by the maximum level selector, i.e., at each frequency, the spectral shape of sound signal  306 / 130  follows either the auditory threshold or the level of background noise, whichever is greater. 
     Filter synthesizer  350  generates/derives the filter coefficients for the shaping filter of spectral shaper  322  that, when applied to the shaping filter, cause the shaping filter to have a frequency response (i.e., gain/loss vs. frequency) that follows the spectral shape output by maximum level selector  346 . Filter synthesizer  350  derives the filter coefficients using any known or hereafter technique used to derive filter coefficients for a known type of filter based on a desired frequency response for that filter. Filter synthesizer  350  provides the filter coefficients to spectral shaper  322  via control signal  330 . The shaping filter of spectral shaper  322  shapes the white noise-like spectrum of sound signal  326  according to the frequency response of the shaping filter. 
     It may be assumed that microphone  118  is a proxy for the hearing of user  102  and that the sound pressure level (SPL) detected at the microphone due to either background noise in room  101  or audio signal  130  is representative of the sound pressure level at the user. In the case of either noise or sound signal  130 , the sound pressure level at microphone  118  may be estimated within each narrow frequency subband according to the following:
         α=0.01 (or some other fraction of 1);   y[n]=bandpassfilter(x[n]), n is a time or sequence number index, x[n] is the level input to spectral noise estimator  340 , and y[n] is the estimated noise level; and   sp[n]=α*abs((y[n]+(1−α))sp[n−1]), where sp[n] is the sound pressure at the microphone,   where, if x[n] is in units of Sound Pressure [Pascal], the SPL is 20*log 10 (Sound Pressure/Reference Pressure).       

     Also, both transmit path  301  and receive path  302  may be calibrated such that a known sound pressure level transmitted by loudspeaker  116  results in a known sound pressure level at microphone  118  (and thus at user  102 ). Moreover, the sound levels represented by auditory thresholds model  342  and the frequency response of the shaping filter of spectral shaper  322  may also be referenced to the known calibrated levels such that a particular auditory threshold, or noise level, translates to a particular gain/attenuation of the frequency response that in turn results in a known sound pressure level being transmitted from loudspeaker  116 . 
     With reference to  FIG. 4 , there is an illustration of a frame format  400  for sound signals  326 ,  306 , and  130 , as generated by signal generator  320 . Frame format  400  includes a preamble  405  followed by a payload  410  carrying a message of N bits. In the example of  FIG. 4 , N=64, where each bit is spread using a spreading code of 1024 chips. In an example, signal generator  320  performs direct spreading at a sample rate of 48 KHz, where a chip rate is equal to the sample rate. These spreading parameters result in a message packet having 65536 samples for a duration of approximately 1.37 seconds. Signal generator  320  modulates each bit in payload  410  as + or −1024 “ones” multiplied by a chronologically increasing chunk of a larger length MLS of order 16 (i.e., 2 16 −1). Signal generator  320  modulates each bit of preamble  405  with a different MLS of order 14 (i.e., 2 14 −1). Appended preamble  405  and payload  410  represent a combined 81919 samples or approximately 1.7 seconds for a 37.5 bits/second rate. The periodic noise-like signal represented by frame format  400 , having a periodicity of greater than 1 second (e.g., 1.7 seconds), conveys information, while sounding like white noise to human hearing. Other values of N, sample rate, and chip rate may be used. 
     As depicted in the example of  FIG. 4 , frame format  400  includes the sequence [preamble, payload1, preamble, payload2, . . . ]. Thus, the preamble is temporally multiplexed with the payload. Generally, the preamble will remain the same as it is used for receiver synchronization and channel estimation purposes, while the payload may change over time. Repeated payloads may be used, depending on how fast a given pairing system is required to detect that a user/user device has left the room. 
     With reference to  FIG. 5 , there are shown predetermined models or plots/curves for auditory thresholds of human hearing (i.e., frequency responses or sensitivities of human hearing) as developed by various audio standards bodies and that may be used auditory thresholds model  342  or on which the model may be based. The illustrated models include an inverse International Telecommunication Union (ITU)-R 468 weighting curve  505  (which may be referenced to 0 dB SPL @ 1 kHz), an inverse A-weighting curve  510 , and a predetermined International Organization for Standardization (ISO) 226 0-phon curve  515 . Auditory thresholds curves  505 - 515  exhibit the following common characteristics: the curves span the frequency range of human hearing and low ultrasound from 0-25 KHz; each of the curves resembles a “hammock” shape having relatively high auditory thresholds in both a relatively low frequency subband (e.g., at relatively low frequencies of 0-1 KHz) and a relatively high frequency subband (e.g., relatively high frequencies of 10-25 KHz), and relatively low auditory thresholds that are lower than the relatively high auditory thresholds in a relatively mid-range frequency subband (e.g., mid-range frequencies of 1-10 KHz) between the low and high frequency subbands. 
     With reference to  FIG. 6 , there is shown an example (spectrally) shaped frequency spectrum  605  of sound signal  130  produced by spectral shaping encoder  250  when (i) auditory thresholds model  342  uses ITU-R 468 weighting curve  505 , and (ii) the background noise levels in room  102  follow a “weak” pseudo-pink noise spectral distribution or spectrum  610 . Shaped frequency spectrum  605  also represents the frequency response of spectral shaper  322 , e.g., the frequency response of the shaping filter of the spectral shaper. Pink noise or 1/f noise (where f is frequency) has equal energy in all octaves and, in terms of power at constant bandwidth, falls off at 3 dB per octave. The pink noise represents an example of a more general case of colored noise or 1/f β  noise, where β can take any value greater than or equal to 1. The frequency spectrum of the colored noise (including the pink noise) generally follows a low pass filter shape (i.e., follows the shape of the frequency response of a low pass filter). 
     In a low frequency range from below 100 Hz to 1 KHz in which the auditory thresholds of auditory thresholds curve  505  exceed the noise levels given by weak pink noise spectrum  610 , the levels of shaped frequency spectrum  605  follow, i.e., match or are substantially equal to, the auditory thresholds rather than the noise levels. In a middle frequency range from 1 KHz to nearly 10 KHz in which the noise levels exceed the auditory thresholds, the levels of shaped frequency spectrum  605  follow pink noise spectrum  610  rather than the auditory thresholds. In a high frequency range above 10 KHz in which the auditory thresholds again exceed the noise levels, the levels of shaped frequency spectrum  605  follow the auditory thresholds. In summary, given a room environment in which the background noise level follows weak pink noise spectrum  610 , spectral shaping encoder  250  spectrally shapes output signal  130  in low, middle, and high frequency subbands of the frequency range of human hearing to follow auditory thresholds, pink noise levels, and then auditory thresholds again, respectively. Pink noise spectrum  610  is considered “weak” because the auditory thresholds dominate over the noise for most of the output spectrum of audio signal  130 . In other words, being limited by his or her auditory thresholds, a human listener would be unable to perceive acoustic noise over large portions of the human auditory spectrum. 
     With reference to  FIG. 7 , there is shown an example shaped frequency spectrum  705  of sound signal  130  produced by spectral shaping encoder  250  when (i) auditory thresholds model  342  uses ITU-R 468 weighting curve  505 , and (ii) the background noise levels in room  102  follow a “strong” pink noise spectral distribution or spectrum  710 . Shaped frequency spectrum  705  also represents the frequency response of spectral shaper  322 , e.g., the frequency response of the shaping filter of the spectral shaper. Strong pink noise spectrum  710  is similar to weak pink noise spectrum  610 , except that the noise levels of the strong pink noise spectrum are all increased by 15 dB relative to those of the weak pink noise spectrum. 
     In a low frequency range from below 100 Hz to approximately 14 KHz in which the noise levels exceed the auditory thresholds, shaped frequency spectrum  705  follows pink noise spectrum  710 . In a high frequency range above 14 KHz in which the auditory thresholds exceed the noise levels, shaped frequency spectrum  705  follows the auditory thresholds. In summary, given a room environment in which the background noise level follows strong pink noise spectrum  710 , spectral shaping encoder  250  spectrally shapes sound signal  130  in low and high frequency subbands of the frequency range of human hearing so as to follow noise levels and then auditory thresholds, respectively. Pink noise spectrum  710  is considered “strong” because the noise levels dominate over the auditory thresholds for most of the spectrum of audio signal  130 . 
     While  FIGS. 6 and 7  show pink noise spectrums, room noise may follow other types of noise spectrums. 
     As mentioned above, the embodiment of spectral shaping encoder  250  depicted in  FIG. 3  is adaptive because it automatically adjusts to different noise levels/frequency spectrums in room  101 . In another embodiment, the spectral shaping encoder may use a shaping filter having a static frequency response based on an assumption of a noise spectrum for a room environment. In the static embodiment, the noise may be assumed to be one of weak pink (e.g., as shown in  FIG. 6 ), strong pink (as shown in  FIG. 7 ), or an intermediate-level pink and, therefore, the filter coefficients are derived and programmed into the shaping filter for the assumed noise spectrum, so that the shaping filter has a static frequency response corresponding to the assumed noise spectrum. An example of a static frequency response is described below in connection with  FIG. 8 . In yet another embodiment, endpoint  100  may be configured to (i) enable manual selection by a user of any of multiple predetermined noise spectrums, and, in response to a selection, program the frequency response of the shaping filter accordingly using a corresponding set of filter coefficients, for example. 
     With reference to  FIG. 8 , there is shown an example static frequency response  800  for the shaping filter of spectral shaper  322 . An FIR filter having a number N taps (filter coefficients) may be programmed to have frequency response  800 . In an example, the number N of taps may include many taps, such as 100 taps or more; however, for convenience, less taps may be used to generate a rough approximation of frequency response  800 . Frequency response  800  exhibits cascaded frequency responses including those of a low pass filter up 8 KHz, a notch filter centered about 8 KHz, and a high pass filter above 8 KHz. Frequency response  800  also includes an anti-aliasing notch centered at 24 KHz, which is half of the sampling/chip rate. Frequency response  800  reflects typical room environments in which noise dominates lower frequencies and auditory thresholds dominate higher frequencies, that is, noise dominates the frequency response up to the notch, while auditory thresholds dominate the frequency response at the notch and at frequencies above notch. 
     With reference to  FIG. 9 , there is a block diagram of an example receiver  900  capable of receiving and processing/decoding sound signal  130 . Receiver  900  may be implemented in user device  103 , for example. Receiver  130  includes: a microphone  902  to detect sound signal  130 ; an A/D  904  to digitize the detected sound signal; an anti-aliasing filter  906  to filter the digitized sound signal; a spectral shaper  908  to spectrally shaped the filtered digitized sound signal based on information from a noise model  910 ; and a core decoder  912  to decode the spectrally shaped signal. Spectral shaper  908 , noise model  910 , and core decoder  912  collectively represent a spectral shaping decoder  914 . Spectral shaper  908  may include a high pass filter to reduce the influence of, typically low-frequency dominated, stationary background noise as well as, typically low-frequency dominated, highly non-stationary in-room speech. The filter may introduce on the order of 20-40 dB of attenuation at direct current (DC) frequencies, while smoothly transitioning to 0 dB gain at 0.5 times the Nyquist frequency. 
     With reference to  FIG. 10 , there is a flowchart of an example method  1000  of generating a spectrally shaped sound performed by a communication device, such as endpoint  100 . Method  1000  summarizes operations described above. 
     At  1005 , endpoint  100  (e.g., controller  200 ) generates sound signal  326  having the white noise-like frequency spectrum spanning at least a portion of the frequency range of human hearing. 
     At  1010 , endpoint  100  (e.g., controller  200 ) stores auditory/sound thresholds of human hearing model  342  for various frequencies (e.g., frequency points, bins, or narrow subbands) spanning the frequency range. For example, endpoint  100  stores a respective auditory/sound threshold corresponding to each of the frequencies. 
     At  1015 , endpoint  100  (e.g., controller  200 ) determines respective levels of background noise in room  101  at the various frequencies. Endpoint  100  may determine the levels of background noise adaptively as described above in connection with  FIG. 3 , or may access the levels from a predetermined noise spectrum, e.g., plot of noise levels vs. frequency. For example endpoint  100  determines a respective level of background noise corresponding to each of the frequencies. 
     At  1020 , endpoint  100  (e.g., controller  200 ) spectrally shapes the white noise-like frequency spectrum of signal  326  to produce a signal (e.g., signal  306 ,  130 ) having a shaped frequency spectrum. The shaped frequency spectrum has, for/at each frequency across the shaped frequency spectrum, a respective level that follows either the auditory threshold or the level of background noise at that frequency, whichever is greater. In the adaptive embodiment, the spectral shaping adapts to different room noise spectrums over time based on the adaptive noise determination in operation  1015 . In a static embodiment, the spectral shaping may be static, and based on a predetermined noise level spectrum accessed in operation  1015 , such as a pink noise spectrum. Spectral shaping may be implemented in the time domain (e.g., by filtering time domain samples using an FIR filter) or, alternatively, in the frequency domain (e.g., by manipulating frequency domain samples produced by an FFT) to achieve the same end result, i.e., a shaped frequency spectrum. 
     At  1025 , endpoint  100  transmits signal  130  having the shaped frequency spectrum from loudspeaker  106  into the room (e.g., controller  200  causes signal  130  to be transmitted from loudspeaker  106 ). 
     Table 1 below formalizes trade-offs between communication conditions and perceptual conditions that results when using the embodiments described herein. The trade-offs assume similar acoustic conditions at the microphones used in the endpoint and at the users. 
     
       
         
           
               
               
               
             
               
                 TABLE 1 
               
               
                   
               
               
                   
                 Communication Signal-to- 
                 Human 
               
               
                   
                 Noise Ratio (SNR) 
                 Perceptibility 
               
               
                   
               
             
            
               
                 Noise Dominated Spectral 
                  0 dB SNR 
                 +3 dB 
               
               
                 Bands 
                   
                   
               
               
                 Audibility Thresholds 
                 &gt;0 dB SNR 
                 None 
               
               
                 Dominated Spectral Bands 
               
               
                   
               
            
           
         
       
     
     As seen in Table 1:
         a. A perceptual “price to pay” or degradation using the embodiments is (only) a rise in perceived noise levels of (at most) +3 dB, in frequency bands that are dominated by acoustic noise. In bands that are dominated by human audibility, there is no perceptual price to pay.   b. A (digital) communication opportunity or improvement that is gained across the frequencies using the embodiments is some bands with 0 dB SNR (noise-dominated bands) and others with &gt;0 dB (human audibility dominated bands).       

     In summary, in one form, a method is provided comprising: at a communication device having a loudspeaker to transmit sound into a room: generating a signal having a white noise-like frequency spectrum spanning a frequency range of human hearing; storing auditory thresholds of human hearing for respective frequencies spanning the frequency range; determining levels of background noise in the room at the respective frequencies; spectrally shaping the white noise-like frequency spectrum to produce a shaped frequency spectrum having, for each frequency, a respective level that follows either the auditory threshold or the level of background noise at that frequency, whichever is greater; and transmitting the shaped frequency spectrum from the loudspeaker into the room. 
     In summary, in another form, an apparatus is provided comprising: a loudspeaker to transmit sound into a room; a controller coupled to the loudspeaker and configured to: generate a signal having a white noise-like frequency spectrum spanning a frequency range of human hearing; store auditory thresholds of human hearing for respective frequencies spanning the frequency range; determine levels of background noise in the room at the respective frequencies; spectrally shape the white noise-like frequency spectrum to produce a shaped frequency spectrum having, for each frequency, a respective level that follows either the auditory threshold or the level of background noise at that frequency, whichever is greater; and cause the loudspeaker to transmit the shaped frequency spectrum into the room. 
     In summary, in yet another form, a processor readable medium is provided to store instructions that, when executed by a processor, cause the processor to perform the method described herein. In an example, a non-transitory computer-readable storage media encoded with software comprising computer executable instructions and when the software is executed, by a controller of a communication device having a loudspeaker to transmit sound into a room, operable to: generate a signal having a white noise-like frequency spectrum spanning a frequency range of human hearing; store auditory thresholds of human hearing for respective frequencies spanning the frequency range; determine levels of background noise in the room at the respective frequencies; spectrally shape the white noise-like frequency spectrum to produce a shaped frequency spectrum having, for each frequency, a respective level that follows either the auditory threshold or the level of background noise at that frequency, whichever is greater; and cause the loudspeaker to transmit the shaped frequency spectrum into the room. 
     The above description is intended by way of example only. Various modifications and structural changes may be made therein without departing from the scope of the concepts described herein and within the scope and range of equivalents of the claims.