Abstract:
Encoding and decoding methods and apparatus as described. An example method of obtaining auxiliary information in an audio signal using a plurality of frequency components residing in a plurality of code bands comprises transforming an audio signal into a frequency domain representation; determining characteristic of frequencies of the frequency domain representation that may contain the auxiliary information; normalizing across the code bands the characteristics of frequencies of the frequency domain representation in a respective one of the code bands that may contain the auxiliary information, wherein the normalization is carried out against a characteristic of a frequency in that code band; summing the normalized characteristics of the frequencies representative of auxiliary information to determine a sum for a frequency representative of auxiliary information; and determining that the sum is representative of the auxiliary information.

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
       [0001]    This patent arises from a divisional of U.S. patent application Ser. No. 12/249,619, filed Oct. 10, 2008, which claims the benefit of U.S. Provisional Application Nos. 60/987,280 and 61/043,952, filed Nov. 12, 2007, and Apr. 10, 2008, respectively, and the entireties of which are incorporated by reference. 
     
    
     TECHNICAL FIELD 
       [0002]    The present disclosure relates generally to media monitoring and, more particularly, to methods and apparatus to perform audio watermarking and watermark detection and extraction. 
       BACKGROUND 
       [0003]    Identifying media information and, more specifically, audio streams (e.g., audio information) is useful for assessing audience exposure to television, radio, or any other media. For example, in television audience metering applications, a code may be inserted into the audio or video of media, wherein the code is later detected at monitoring sites when the media is presented (e.g., played at monitored households). The information payload of the code/watermark embedded into original signal can consist of unique source identification, time of broadcast, transactional or additional content metadata. Monitoring sites typically include locations such as, for example, households where the media consumption of audience members or audience member exposure to the media is monitored. For example, at a monitoring site, codes from the audio and/or video are captured and may be associated with audio or video streams of media associated with a selected channel, radio station, media source, etc. The collected codes may then be sent to a central data collection facility for analysis. However, the collection of data pertinent to media exposure or consumption need not be limited to in-home exposure or consumption. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0004]      FIG. 1  is a schematic depiction of a broadcast audience measurement system employing a program identifying code added to the audio portion of a composite television signal. 
           [0005]      FIG. 2  is a block diagram of an example encoder of  FIG. 1 . 
           [0006]      FIGS. 3A-3C  are charts illustrating different example code frequency configurations that may be used in the code frequency selector of  FIG. 2 . 
           [0007]      FIG. 4  is a flow diagram illustrating an example process that may be carried out by the example encoder of  FIG. 2 . 
           [0008]      FIG. 5  is a block diagram of an example decoder of  FIG. 1 . 
           [0009]      FIG. 6  is a flow diagram illustrating an example process that may be carried out by the example decoder of  FIG. 4 . 
           [0010]      FIG. 7  is a schematic illustration of an example processor platform that may be used and/or programmed to perform any or all of the processes or implement any or all of the example systems, example apparatus and/or example methods described herein. 
       
    
    
     DETAILED DESCRIPTION 
       [0011]    The following description makes reference to audio encoding and decoding that is also commonly known as audio watermarking and watermark detection, respectively. It should be noted that in this context, audio may be any type of signal having a frequency falling within the normal human audibility spectrum. For example, audio may be speech, music, an audio portion of an audio and/or video program or work (e.g., a television program, a movie, an Internet video, a radio program, a commercial spot, etc.), a media program, noise, or any other sound. 
         [0012]    In general, the encoding of the audio inserts one or more codes into the audio and ideally leaves the code inaudible to hearers of the audio. However, there may be certain situations in which the code may be audible to certain listeners. Additionally, the following refers to codes that may be encoded or embedded in audio; these codes may also be referred to as watermarks. The codes that are embedded in audio may be of any suitable length and any suitable technique for assigning the codes to information may be selected. Furthermore, as described below, the codes may be converted into symbols that are represented by signals having selected frequencies that are embedded in the audio. Any suitable encoding or error correcting technique may be used to convert codes into symbols. 
         [0013]    The following examples pertain generally to encoding an audio signal with information, such as a code, and obtaining that information from the audio via a decoding process. The following example encoding and decoding processes may be used in several different technical applications to convey information from one place to another. 
         [0014]    The example encoding and decoding processes described herein may be used to perform broadcast identification. In such an example, before a work is broadcast, that work is encoded to include a code indicative of the source of the work, the broadcast time of the work, the distribution channel of the work, or any other information deemed relevant to the operator of the system. When the work is presented (e.g., played through a television, a radio, a computing device, or any other suitable device), persons in the area of the presentation are exposed not only to the work, but, unbeknownst to them, are also exposed to the code embedded in the work. Thus, persons may be provided with decoders that operate on a microphone-based platform so that the work may be obtained by the decoder using free-field detection and processed to extract codes therefrom. The codes may then be logged and reported back to a central facility for further processing. The microphone-based decoders may be dedicated, stand-alone devices, or may be implemented using cellular telephones or any other types of devices having microphones and software to perform the decoding and code logging operations. Alternatively, wire-based systems may be used whenever the work and its attendant code may be picked up via a hard wired connection. 
         [0015]    The example encoding and decoding processes described herein may be used, for example, in tracking and/or forensics related to audio and/or video works by, for example, marking copyrighted audio and/or associated video content with a particular code. The example encoding and decoding processes may be used to implement a transactional encoding system in which a unique code is inserted into a work when that work is purchased by a consumer. Thus, allowing a media distribution to identify a source of a work. The purchasing may include a purchaser physically receiving a tangible media (e.g., a compact disk, etc.) on which the work is included, or may include downloading of the work via a network, such as the Internet. In the context of transactional encoding systems, each purchaser of the same work receives the work, but the work received by each purchaser is encoded with a different code. That is, the code inserted in the work may be personal to the purchaser, wherein each work purchased by that purchaser includes that purchaser&#39;s code. Alternatively, each work may be may be encoded with a code that is serially assigned. 
         [0016]    Furthermore, the example encoding and decoding techniques described herein may be used to carry out control functionality by hiding codes in a steganographic manner, wherein the hidden codes are used to control target devices programmed to respond to the codes. For example, control data may be hidden in a speech signal, or any other audio signal. A decoder in the area of the presented audio signal processes the received audio to obtain the hidden code. After obtaining the code, the target device takes some predetermined action based on the code. This may be useful, for example, in the case of changing advertisements within stores based on audio being presented in the store, etc. For example, scrolling billboard advertisements within a store may be synchronized to an audio commercial being presented in the store through the use of codes embedded in the audio commercial. 
         [0017]    An example encoding and decoding system  100  is shown in  FIG. 1 . The example system  100  may be, for example, a television audience measurement system, which will serve as a context for further description of the encoding and decoding processes described herein. The example system  100  includes an encoder  102  that adds a code  103  to an audio signal  104  to produce an encoded audio signal. The code  103  may be representative of any selected information. For example, in a media monitoring context, the code  103  may be representative of an identity of a broadcast media program such as a television broadcast, a radio broadcast, or the like. Additionally, the code  103  may include timing information indicative of a time at which the code  103  was inserted into audio or a media broadcast time. Alternatively, as described below, the code may include control information that is used to control the behavior of one or more target devices. 
         [0018]    The audio signal  104  may be any form of audio including, for example, voice, music, noise, commercial advertisement audio, audio associated with a television program, live performance, etc. In the example of  FIG. 1 , the encoder  102  passes the encoded audio signal to a transmitter  106 . The transmitter  106  transmits the encoded audio signal along with any video signal  108  associated with the encoded audio signal. While, in some instances, the encoded audio signal may have an associated video signal  108 , the encoded audio signal need not have any associated video. 
         [0019]    Although the transmit side of the example system  100  shown in  FIG. 1  shows a single transmitter  106 , the transmit side may be much more complex and may include multiple levels in a distribution chain through which the audio signal  104  may be passed. For example, the audio signal  104  may be generated at a national network level and passed to a local network level for local distribution. Accordingly, although the encoder  102  is shown in the transmit lineup prior to the transmitter  106 , one or more encoders may be placed throughout the distribution chain of the audio signal  104 . Thus, the audio signal  104  may be encoded at multiple levels and may include embedded codes associated with those multiple levels. Further details regarding encoding and example encoders are provided below. 
         [0020]    The transmitter  106  may include one or more of a radio frequency (RF) transmitter that may distribute the encoded audio signal through free space propagation (e.g., via terrestrial or satellite communication links) or a transmitter used to distribute the encoded audio signal through cable, fiber, etc. In one example, the transmitter  106  may be used to broadcast the encoded audio signal throughout a broad geographical area. In other cases, the transmitter  106  may distribute the encoded audio signal through a limited geographical area. The transmission may include up-conversion of the encoded audio signal to radio frequencies to enable propagation of the same. Alternatively, the transmission may include distributing the encoded audio signal in the form of digital bits or packets of digital bits that may be transmitted over one or more networks, such as the Internet, wide area networks, or local area networks. Thus, the encoded audio signal may be carried by a carrier signal, by information packets or by any suitable technique to distribute the audio signals. 
         [0021]    When the encoded audio signal is received by a receiver  110 , which, in the media monitoring context, may be located at a statistically selected metering site  112 , the audio signal portion of the received program signal is processed to recover the code, even though the presence of that code is imperceptible (or substantially imperceptible) to a listener when the encoded audio signal is presented by speakers  114  of the receiver  110 . To this end, a decoder  116  is connected either directly to an audio output  118  available at the receiver  110  or to a microphone  120  placed in the vicinity of the speakers  114  through which the audio is reproduced. The received audio signal can be either in a monaural or stereo format. Further details regarding decoding and example decoders are provided below. 
       Audio Encoding 
       [0022]    As explained above, the encoder  102  inserts one or more inaudible (or substantially inaudible) codes into the audio  104  to create encoded audio. One example encoder  102  is shown in  FIG. 2 . In one implementation, the example encoder  102  of  FIG. 2  includes a sampler  202  that receives the audio  104 . The sampler  202  is coupled to a masking evaluator  204 , which evaluates the ability of the sampled audio to hide codes therein. The code  103  is provided to a code frequency selector  206  that determines audio code frequencies that are used to represent the code  103  to be inserted into the audio. The code frequency selector  206  may include conversion of codes into symbols and/or any suitable detection or correction encoding. An indication of the designated code frequencies that will be used to represent the code  103  are passed to the masking evaluator  204  so that the masking evaluator  204  is aware of the frequencies for which masking by the audio  104  should be determined. Additionally, the indication of the code frequencies is provided to a code synthesizer  208  that produces sine wave signals having frequencies designated by the code frequency selector  206 . A combiner  210  receives both the synthesized code frequencies from the code synthesizer  208  and the audio that was provided to the sampler and combines the two to produce encoded audio. 
         [0023]    In one example in which the audio  104  is provided to the encoder  102  in analog form, the sampler  202  may be implemented using an analog-to-digital (A/D) converter or any other suitable digitizer. The sampler  202  may sample the audio  104  at, for example, 48,000 Hertz (Hz) or any other sampling rate suitable to sample the audio  104  while satisfying the Nyquist criteria. For example, if the audio  104  is frequency-limited at 15,000 Hz, the sampler  202  may operate at 30,000 Hz. Each sample from the sampler  202  may be represented by a string of digital bits, wherein the number of bits in the string indicates the precision with which the sampling is carried out. For example, the sampler  202  may produce 8-bit, 16-bit, 24-bit, or 32-bit. 
         [0024]    In addition to sampling the audio  104 , the example sampler  202  accumulates a number of samples (i.e., an audio block) that are to be processed together. For example, the example sampler  202  accumulates a 512 sample audio block that is passed to the masking evaluator  204  at one time. Alternatively, in one example, the masking evaluator  204  may include an accumulator in which a number of samples (e.g., 512) may be accumulated in a buffer before they are processed. 
         [0025]    The masking evaluator  204  receives or accumulates the samples (e.g., 512 samples) and determines an ability of the accumulated samples to hide code frequencies to human hearing. That is, the masking evaluator determines if code frequencies can be hidden within the audio represented by the accumulated samples by evaluating each critical band of the audio as a whole to determine its energy and determining the noise-like or tonal-like attributes of each critical band and determining the sum total ability of the critical bands to mask the code frequencies. Critical frequency bands, which were determined by experimental studies carried out on human auditory perception, may vary in width from single frequency bands at the low end of the spectrum to bands containing ten or more adjacent frequencies at the upper end of the audible spectrum. If the masking evaluator  204  determines that code frequencies can be hidden in the audio  104 , the masking evaluator  204  indicates the amplitude levels at which the code frequencies can be inserted within the audio  104 , while still remaining hidden and provides the amplitude information to the code synthesizer  208 . 
         [0026]    In one example, the masking evaluator  204  conducts the masking evaluation by determining a maximum change in energy E b  or a masking energy level that can occur at any critical frequency band without making the change perceptible to a listener. The masking evaluation carried out by the masking evaluator  204  may be carried out as outlined in the Moving Pictures Experts Group-Advanced Audio Encoding (MPEG-AAC) audio compression standard ISO/IEC 13818-7:1997, for example. The acoustic energy in each critical band influences the masking energy of its neighbors and algorithms for computing the masking effect are described in the standards document such as ISO/IEC 13818-7:1997. These analyses may be used to determine for each audio block the masking contribution due to tonality (e.g., how much the audio being evaluated is like a tone) as well as noise like (i.e., how much the audio being evaluated is like noise) features. Further analysis can evaluate temporal masking that extends masking ability of the audio over short time, typically, for 50-100 ms. The resulting analysis by the masking evaluator  204  provides a determination, on a per critical band basis, the amplitude of a code frequency that can be added to the audio  104  without producing any noticeable audio degradation (e.g., without being audible). 
         [0027]    In one example, the code frequency selector  206  may be implemented using a lookup table that relates an input code  103  to a state, wherein each state is represented by a number of code frequencies that are to be emphasized in the encoded audio signal. For example, the code frequency selector  206  may include information relating symbols or data states to sets of code frequencies that redundantly represent the data states. Of course, the number of states selected for use may be based on the types of input codes. For example, an input code representing two bits may be converted to code frequencies representing one of four symbols or states (e.g., 2 2 ). In another example, an input code representing four bits of information may be represented by one of 16 symbols or states (e.g., 2 4 ). Of course, some other encoding may be used to build in error correction when converting the code  103  to one or more symbols or states. Additionally, in some examples, more than one code may be embedded in the audio  104 . 
         [0028]    One example chart illustrating a code frequency configuration is shown in  FIG. 3A  at reference numeral  300 . The chart includes frequency indices that range in value from 360 to 1366. These frequency indices correspond to frequencies of the sine waves to be embedded into an audio signal when viewed in the frequency domain via a Fourier transformation of a block of 18,432 samples. The reason that reference is made to frequency indices rather than actual frequencies is that the frequencies to which the indices correspond vary based on the sampling rate used within the encoder  102  and the number of samples processed by the decoder  116 . The higher the sampling rate, the closer in frequency each of the indices is to its neighboring indices. Conversely, a low sampling rate results in adjacent indices that are relatively widely space in frequency. For example, at a sampling rate of 48,000 Hz, the spacing between the indices shown in the chart  300  of  FIG. 3A  is 2.6 Hz. Thus, frequency index  360  corresponds to 936 Hz (2.6 Hz×360). 
         [0029]    As shown in  FIG. 3A , the chart  300  includes a top row  302  listing 144 different states or symbols represented in columns, wherein the chart  300  shows the first three states and the last state. The states are selected to represent codes or portions of codes. The states between the third state and the last state are represented by dashed boxes for the sake of clarity. Each of the states occupies a corresponding column in the chart  300 . For example, state S 1  occupies a column denoted with reference numeral  304 . Each column includes a number of frequency indices representing a frequency in each of seven different code bands, which are denoted in the left-hand column  306  of the chart  300 . For example, as shown in column  304 , the state S 1  is represented by frequency indices  360 ,  504 ,  648 ,  792 ,  936 ,  1080 , and  1224 . To send one of the 144 states, the code indices in the column of the selected state are emphasized in a block of 18,432 samples. Thus, to send state S 1 , indices  360 ,  504 ,  6489 ,  792 ,  936 ,  1080 , and  1224  are emphasized. In one example encoder  102 , the indices of only one of the states are ever emphasized at one time. 
         [0030]    As shown in  FIG. 3A , each code band includes sequentially numbered frequency indices, one of which corresponds to each state. That is, Code Band  0  includes frequency indices  360 - 503 , each corresponding to one of the 144 different states/symbols shown in the chart  300 . Additionally, adjacent code bands in the system are separated by one frequency index. For example, Code Band  0  ranges from index  360  to index  503  and adjacent Code Band  1  ranges from index  504  to index  647 . Thus, Code Band  0  is spaced one frequency index from adjacent Code Band  1 . Advantageously, the code frequencies shown in  FIG. 3A  are close to one another in frequency and, thus, are affected in relatively the same manner by multipath interference. Additionally, the high level of redundancy in the chart  300  enhances the ability to recover the code. 
         [0031]    Thus, if the code frequency selector  206  operates premised on the chart  300  of  FIG. 3A , when an input code to the code frequency selector  206  is encoded or mapped to state S 1 , the code frequency selector  206  indicates to the masking evaluator  204  and the code synthesizer  208  that frequency indices  360 ,  504 ,  648 ,  792 ,  936 ,  1080 , and  1224  should be emphasized in the encoded signal and, therefore, the code synthesizer  208  should produce sine waves having frequencies corresponding to the frequency indices  360 ,  504 ,  648 ,  792 ,  936 ,  1080 , and  1224 , and that such sine waves should be generated with amplitudes specified by the masking evaluator  204  so that the generated sine waves can be inserted into the audio  104 , but will be inaudible (or substantially inaudible). By way of further example, when an input code identifies that state S 144  should be encoded into the audio  104 , the code frequency selector  206  identifies frequency indices  503 ,  647 ,  791 ,  935 ,  1079 ,  1223 , and  1366  to the masking evaluator  204  and the code synthesizer  208  so that corresponding sine waves can be generated with appropriate amplitudes. 
         [0032]    The encoding used to select states in the chart  300  to convey information may include data blocks and synchronization blocks. For example, the message to be encoded by the system using these 144 different states consists of a synchronization block that is followed by several data blocks. Each of the synchronization block and the data blocks is encoded into 18,432 samples and is represented by emphasizing the indices of one of the states shown in the chart  300  table below by emphasizing frequency indices shown in one column of the chart  300 . 
         [0033]    For example, a synchronization block is represented by emphasizing the indices of one of 16 states selected to represent synchronization information. That is, the synchronization block indicates the start of one of 16 different message types. For example, when considering media monitoring, network television stations may use a first state to represent synchronization and a local affiliate may use a second state to represent synchronization. Thus, at the start of a transmission, one of 16 different states is selected to represent synchronization and transmitted by emphasizing the indices associated with that state. Information payload data follows synchronization data. 
         [0034]    In the foregoing example, with regard to how these 16 states representing synchronization information are distributed throughout the 144 states, in one example the 16 states are selected so that a frequency range including first code frequencies representing each of those 16 states is larger than a frequency amount separating that frequency range from an adjacent frequency range including second code frequencies also representing each of those 16 states. For example, the 16 states representing the synchronization information may be spaced every 9 states in the table above, such that states S 1 , S 10 , S 19 , S 28 , S 37 , S 46 , S 54 , S 63 , S 72 , S 81 , S 90 , S 99 , S 108 , S 117 , S 126 , S 135  represent possible states that the synchronization information may take. In Code Band  0  and Code Band  1 , this corresponds to a width in frequency indices of 135 indices. The frequency spacing between the highest possible synchronization state (S 135 ) of Code Band  0  and the lowest possible synchronization state (S 1 ) of Code Band  1  is 10 frequency indices. Thus, the range of each collection of frequency indices representing the synchronization information is much larger (e.g., 135 indices) than the amount separating adjacent collections (e.g., 10 indices). 
         [0035]    In this example, the remaining 128 states of the 144 state space that are not used to represent synchronization maybe used to transmit information data. The data may be represented by any number of suitable states required to represent the number of desired bits. For example, 16 states may be used to represent four bits of information per state, or  128  states may be used to represent seven bits of information per state. In one example, the states selected to represent data are selected such that a frequency range including first code frequencies representing each of the data states is larger than a frequency amount separating that frequency range from an adjacent frequency range including second code frequencies also representing each of the data states. Thus, states used to represent potential data include at least one substantially low numbered state (e.g., S 2 ) and at least one substantially high numbered state (e.g., S 144 ). This ensures that the ranges including states that may be used to represent data occupy a wide bandwidth within their respective code bands, and that the spacing between adjacent ranges are narrow. 
         [0036]    The encoder  102  may repeat the encoding process and, thereby, encode a number of audio blocks with a particular code. That is, the selected code frequencies may be inserted into several consecutive 512-sample audio blocks. In one example, the code frequencies representing symbols may be repeated in 36 consecutive audio blocks of 512 samples or 72 overlapping blocks of 256 samples. Thus, at the receive side, when 18,432 samples are processed by a Fourier transformation, the emphasized code frequencies will be visible in the resulting spectrum. 
         [0037]      FIG. 3B  shows an example alternative chart  330  that may be used by the code frequency selector  208 , wherein the chart  330  lists four states in the first row  332 , each of which includes corresponding frequency indices listed in seven code bands  334 . These frequency indices correspond to frequencies of the sinusoids to be embedded into an audio signal when viewed in the frequency domain via a Fourier transformation of a block of 512 samples. By way of example, when state S 1  is to be sent, the code frequency selector  206  indicates that frequency indices  10 ,  14 ,  18 ,  22 ,  26 ,  30 , and  34  are to be used. As described above, the indication of these frequencies is communicated to the masking evaluator  204  and the code synthesizer  208 , so that sine waves having the proper amplitude and corresponding to the indicated frequency indices may be generated for addition to the audio  104 . In an example encoder  102  operating according to the chart  330 , the code frequencies corresponding to the desired symbol are encoded into 2 overlapping blocks of 256 samples in order to make it detectable. 
         [0038]    As with the chart  300  of  FIG. 3A , the chart  330  indicates that the code bands are separated by the same frequency distance as the frequency indices representing adjacent symbol. For example, Code Band  0  includes a code frequency component having a frequency index of 13, which is one frequency index from the Code Band  1  frequency index  14  representing the state S 1 . 
         [0039]    Chart  360  of  FIG. 3C  shows another example that may be used by the code frequency selector  208 , wherein the chart  360  lists 24 states in the first row  362 , each of which includes corresponding frequency indices listed in seven code bands  364 . These frequency indices correspond to frequencies of the sinusoids to be embedded into an audio signal when viewed in the frequency domain via a Fourier transformation of a block of 3072 samples. By way of example, when state S 1  is to be sent, the code frequency selector  206  indicates that frequency indices  60 ,  84 ,  108 ,  132 ,  156 ,  180 , and  204  are to be used. As described above, the indication of these frequencies is communicated to the masking evaluator  204  and the code synthesizer  208 , so that sine waves having the proper amplitude and corresponding to the indicated frequency indices may be generated for addition to the audio  104 . 
         [0040]    In an example encoder  102  operating according to the chart  360  of  FIG. 3C , the code frequencies corresponding to the desired symbol are encoded in 12 overlapping blocks of 256 samples. In this implementation the first 16 columns may be used as data symbols and the 17th column may be used as a synchronization symbol. The remaining seven columns could be used for special data such as Video On Demand—for example, columns  18 , 19 , 20 , 21 ,  22 ,  23  columns as auxiliary data symbols and these will be decoded as such only when an auxiliary synchronization symbol is present in column  24 . 
         [0041]    As with the charts  300  and  330  described above, the chart  360  indicates that the code bands are separated by the same frequency distance as the frequency indices representing adjacent symbol. For example, Code Band  0  includes a code frequency component having a frequency index of 83, which is one frequency index from the Code Band  1  frequency index  84  representing the state S 1 . 
         [0042]    Returning now to  FIG. 2 , as described above, the code synthesizer  208  receives from the code frequency selector  206  an indication of the frequency indices required to be included to create an encoded audio signal including an indication of the input code. In response to the indication of the frequency indices, the code synthesizer  208  generates a number of sine waves (or one composite signal including multiple sine waves) having the identified frequencies. The synthesis may result in sine wave signals or in digital data representative of sine wave signals. In one example, the code synthesizer  208  generates the code frequencies with amplitudes dictated by the masking evaluator  204 . In another example, the code synthesizer  208  generates the code frequencies having fixed amplitudes and those amplitudes may be adjusted by one or more gain blocks (not shown) that is within the code sequencer  208  or is disposed between the code synthesizer  208  and the combiner  210 . 
         [0043]    While the foregoing describes an example code synthesizer  208  that generates sine waves or data representing sine waves, other example implementations of code synthesizers are possible. For example, rather than generating sine waves, another example code synthesizer  208  may output frequency domain coefficients that are used to adjust amplitudes of certain frequencies of audio provided to the combiner  210 . In this manner, the spectrum of the audio may be adjusted to include the requisite sine waves. 
         [0044]    The combiner  210  receives both the output of the code synthesizer  208  and the audio  104  and combines them to form encoded audio. The combiner  210  may combine the output of the code synthesizer  208  and the audio  104  in an analog or digital form. If the combiner  210  performs a digital combination, the output of the code synthesizer  208  may be combined with the output of the sampler  202 , rather than the audio  104  that is input to the sampler  202 . For example, the audio block in digital form may be combined with the sine waves in digital form. Alternatively, the combination may be carried out in the frequency domain, wherein frequency coefficients of the audio are adjusted in accordance with frequency coefficients representing the sine waves. As a further alternative, the sine waves and the audio may be combined in analog form. The encoded audio may be output from the combiner  210  in analog or digital form. If the output of the combiner  210  is digital, it may be subsequently converted to analog form before being coupled to the transmitter  106 . 
         [0045]    An example encoding process  400  is shown in  FIG. 4 . The example process  400  may be carried out by the example encoder  102  shown in  FIG. 2 , or by any other suitable encoder. The example process  400  begins when the code to be included in the audio is obtained (block  402 ). The code may be obtained via a data file, a memory, a register, an input port, a network connection, or any other suitable technique. 
         [0046]    After the code is obtained (block  402 ), the example process  400  samples the audio into which the code is to be embedded (block  404 ). The sampling may be carried out at 48,000 Hz or at any other suitable frequency. The example process  400  then assembles the audio samples into a block of audio samples (block  406 ). The block of samples may include, for example, 512 audio samples. In some examples, blocks of samples may include both old samples (e.g., samples that have been used before in encoding information into audio) and new samples (e.g., samples that have not been used before in encoding information into audio). For example, a block of 512 audio samples may include 256 old samples and 256 new samples. Upon a subsequent iteration of the example process  400 , the 256 new samples from a prior iteration may be used as the 256 old samples of the next iteration of the example process  400 . 
         [0047]    The example process  400  then determines the code frequencies that will be used to include the code (obtained at block  402 ) into the audio block (obtained at block  406 ) (block  408 ). This is an encoding process in which a code or code bits are converted into symbols that will be represented by frequency components. As described above, the example process  400  may use one or more lookup tables to convert codes to be encoded into symbols representative of the codes, wherein those symbols are redundantly represented by code frequencies in the audio spectrum. As described above, seven frequencies may be used to redundantly represent the selected symbol in the block of audio. The selection of symbols to represent codes may include consideration of the block number being processed error coding, etc. 
         [0048]    Having obtained the audio into which the codes are to be included (block  406 ), as well as the code frequencies that are to be used to represent the codes (block  408 ), the process  400  computes the ability of the audio block to mask the selected code frequencies (block  410 ). As explained above, the masking evaluation may include conversion of the audio block to the frequency domain and consideration of the tonal or noise-like properties of the audio block, as well as the amplitudes at various frequencies in the block. Alternatively, the evaluation may be carried out in the time domain. Additionally, the masking may also include consideration of audio that was in a previous audio block. As noted above, the masking evaluation may be carried out in accordance with the MPEG-AAC audio compression standard ISO/IEC 13818-7:1997, for example. The result of the masking evaluation is a determination of the amplitudes or energies of the code frequencies that are to be added to the audio block, while such code frequencies remain inaudible or substantially inaudible to human hearing. 
         [0049]    Having determined the amplitudes or energies at which the code frequencies should be generated (block  410 ), the example process  400  synthesizes one or more sine waves having the code frequencies (block  412 ). The synthesis may result in actual sine waves or may result in digital data equivalent representative of sine waves. In one example, the sine waves may be synthesized with amplitudes specified by the masking evaluation. Alternatively, the code frequencies may be synthesized with fixed amplitudes and then amplitudes of the code frequencies may be adjusted subsequent to synthesis. 
         [0050]    The example process  400  then combines the synthesized code frequencies with the audio block (block  414 ). The combination may be carried out through addition of data representing the audio block and data representing the synthesized sine waves, or may be carried out in any other suitable manner. 
         [0051]    In another example, the code frequency synthesis (block  412 ) and the combination (block  414 ) may be carried out in the frequency domain, wherein frequency coefficients representative of the audio block in the frequency domain are adjusted per the frequency domain coefficients of the synthesized sine waves. 
         [0052]    As explained above, the code frequencies are redundantly encoded into consecutive audio blocks. In one example, a particular set of code frequencies is encoded into 36 consecutive blocks. Thus, the example process  400  monitors whether it has completed the requisite number of iterations (block  416 ) (e.g., the process  400  determines whether the example process  400  has been repeated 36 times to redundantly encode the code frequencies). If the example process  400  has not completed the requisite iterations (block  416 ), the example process  400  samples audio (block  404 ), analyses the masking properties of the same (block  410 ), synthesizes the code frequencies (block  412 ) and combines the code frequencies with the newly acquired audio block (block  414 ), thereby encoding another audio block with the code frequencies. 
         [0053]    However, when the requisite iterations to redundantly encode the code frequencies into audio blocks have completed (block  416 ), the example process  400  obtains the next code to be included in the audio (block  402 ) and the example process  400  iterates. Thus, the example process  400  encodes a first code into a predetermined number of audio blocks, before selecting the next code to encode into a predetermined number of audio blocks, and so on. It is, however, possible, that there is not always a code to be embedded in the audio. In that instance, the example process  400  may be bypassed. Alternatively, if no code to be included is obtained (block  402 ), no code frequencies will by synthesized (block  412 ) and, thus, there will be no code frequencies to alter an audio block. Thus, the example process  400  may still operate, but audio blocks may not always be modified—especially when there is no code to be included in the audio. 
       Audio Decoding 
       [0054]    In general, the decoder  116  detects the code signal that was inserted into the audio to form encoded audio at the encoder  102 . That is, the decoder  116  looks for a pattern of emphasis in code frequencies it processes. Once the decoder  116  has determined which of the code frequencies have been emphasized, the decoder  116  determines, based on the emphasized code frequencies, the symbol present within the encoded audio. The decoder  116  may record the symbols, or may decode those symbols into the codes that were provided to the encoder  102  for insertion into the audio. 
         [0055]    As shown in  FIG. 5 , an example decoder  116  includes a sampler  502 , which may be implemented using an A/D or any other suitable technology, to which encoded audio is provided in analog format. As shown in  FIG. 1 , the encoded audio may be provided by a wired or wireless connection to the receiver  110 . The sampler  502  samples the encoded audio at, for example, a sampling frequency of 48,000 Hz. Of course, lower sampling frequencies may be advantageously selected in order to reduce the computational load at the time of decoding. For example, at a sampling frequency of 8 kHz the Nyquist frequency is 4 kHz and therefore all the embedded code signal is preserved because its spectral frequencies are lower than the Nyquist frequency. The 18,432-sample DFT block length at 48 kHz sampling rate is reduced to 3072 samples at 8 kHz sampling rate. However even at this modified DFT block size the code frequency indices are identical to the original and range from 360 to 1367. 
         [0056]    The samples from the sampler  502  are provided to a time to frequency domain converter  504 . The time to frequency domain converter  504  may be implemented using a discrete Fourier transformation (DFT), or any other suitable technique to convert time-based information into frequency-based information. In one example, the time to frequency domain converter  504  may be implemented using a sliding DFT in which a spectrum is calculated each time a new sample is provided to the example time to frequency converter  504 . In one example, the time to frequency domain converter  504  uses 18,432 samples of the encoded audio and determines a spectrum therefrom. The resolution of the spectrum produced by the time to frequency domain converter  504  increases as the number of samples used to generate the spectrum. Thus, the number of samples processed by the time to frequency domain converter  504  should match the resolution used to select the indices in the charts of  FIG. 3A ,  3 B, or  3 C. 
         [0057]    The spectrum produced by the time to frequency domain converter  504  passes to a code frequency monitor  506 , which monitors all the frequencies or spectral lines corresponding to the frequency indices that can potentially carry codes inserted by the example encoder  102 . For example, if the example encoder  102  sends data based on the chart of  FIG. 3A , the code frequency monitor  506  monitors the frequencies corresponding to indices  360 - 1366 . 
         [0058]    The monitoring of the code frequencies includes evaluating the spectral energies at each of the code frequencies. Thus, the code frequency monitor  506  normalizes the energies for a specific row of the chart of  FIG. 3A  to a maximum energy in that row of the chart. For example, considering the frequency indices corresponding to Code Band  0  of the chart of  FIG. 3A , if the frequency corresponding to frequency index  360  has the maximum energy of the other frequencies in the row representing Code Band  0  (e.g., frequency indices  361 ,  362 , . . .  503 ) each of the energies at the other frequencies corresponding to the indices in Code Band  0  divided by the energy of the frequency corresponding to frequency index  360 . Thus, the normalized energy for frequency index  360  will have a value of 1 and all of the remaining frequencies corresponding to frequency indices in Code Band  0  will have values smaller than 1. This normalization process is repeated for each row of the chart  300 . That is, each Code Band in the chart of  FIG. 3A  will include one frequency having its energy normalized to 1, with all remaining energies in that Code Band normalized to something less than 1. 
         [0059]    Based on the normalized energies produced by the code frequency monitor  506 , a symbol determiner  508  to determines the symbol that was present in the encoded audio. In one example, the symbol determiner  508  sums all of the normalized energies corresponding to each state. That is, the symbol determiner  508  creates 144 sums, each corresponding to a column, or state, in the chart  300 . The column or state having the highest sum of normalized energies is determined to be the symbol that was encoded. The symbol determiner may use a lookup table similar to the lookup table of  FIG. 3A  that can be used to map emphasized frequencies to the symbols to which they correspond. For example, if state S 1  was encoded into the audio, the normalized energies will generally result in a value of one for each frequency index representing state S 1 . That is, in general, all other frequencies in the Code Bands that do not correspond to state S 1  will have a value less than one. However, while this is generally true, not every frequency index corresponding to state S 1  will have a value of one. Thus, a sum of the normalized energies is calculated for each state. In this manner, generally, the normalized energies corresponding to the frequency indices representing state S 1  will have a greater sum than energies corresponding to the frequency indices representing other states. If the sum of normalized energies corresponding to the frequency indices representing state S 1  exceeds a threshold of 4.0 for detection, state S 1  is determined to be the most probable symbol that was embedded in the encoded audio. If, however, the sum does not exceed the threshold, there is insufficient confidence that state S 1  was encoded, and no state is determined to be the most probable state. Thus, the output of the symbol determiner  508  is a stream of most probable symbols that were encoded into the audio. Under ideal conditions, the code frequencies of S 1  will yield a normalized score of 7.0 
         [0060]    The most probable symbols are processed by the validity checker  510  to determine if the received symbols correspond to valid data. That is, the validity checker  510  determines if bits corresponding to the most probable symbol are valid given the encoding scheme used to convert the code into a symbol at the code frequency selector  206  of the encoder  102 . The output of the validity checker  510  is the code, which corresponds to the code provided to the code frequency selector  206  of  FIG. 2 . 
         [0061]    An example decoding process  600  is shown in  FIG. 6 . The example process  600  may be carried out by the example decoder  116  shown in  FIG. 5 , or by any other suitable decoder. The example process  600  begins by sampling audio (block  602 ). The audio may be obtained via an audio sensor, a hardwired connection, via an audio file, or through any other suitable technique. As explained above the sampling may be carried out at 48,000 Hz, or any other suitable frequency. 
         [0062]    As each sample is obtained, a sliding time to frequency conversion is performed on a collection of samples including numerous older samples and the newly added sample obtained at block  602  (block  604 ). In one example, a sliding DFT may be used to process streaming input samples including 18,431 old samples and the one newly added sample. In one example, the DFT using 18,432 samples results in a spectrum having a resolution of 2.6 Hz. 
         [0063]    After the spectrum is obtained through the time to frequency conversion (block  604 ), the energies of the code frequencies are determined (block  606 ). In one example, the energies may be obtained by taking the magnitude of the result of the time to frequency conversion (block  604 ) for the frequency components that may be emphasized to encode the audio. Importantly, to save processing time and minimize memory consumption, only frequency information corresponding to the code frequencies may be retained and processed further, because those frequencies are the only frequencies at which encoded information may be located. Of course, the example process  600  may use other information that the energies. For example, the example process  600  could retain both magnitude and phase information and process the same. 
         [0064]    Additionally, the frequencies that are processed in the process  600  may be further reduced by considering a previously-received synchronization symbol. For example, if a particular synchronization symbol is always followed by one of six different symbols, the frequencies that are processed may be reduced to those of the six different symbols after that particular synchronization symbol is received. 
         [0065]    After the energies are determined (block  606 ), the example process  600  normalizes the code frequency energies of each Code Block based on the largest energy in that Code Block (block  608 ). That is, the maximum energy of a code frequency in a Code Block is used as a divisor against itself and all other energies in that Code Block. The normalization results in each Code Block having one frequency component having a normalized energy value of one, with all other normalized energy values in that Code Block having values less than one. Thus, with reference to  FIG. 3A , each row of the chart  300  will have one entry having a value of one and all other entries will have values less than one. 
         [0066]    The example process  600  then operates on the normalized energy values to determine the most likely symbol based thereon (block  610 ). As explained above, this determination includes, for example, summing the normalized energy values corresponding to each symbol, thereby resulting in the same number of sums as symbols (e.g., in consideration of the chart of  FIG. 3A , there would be 144 sums, each of which corresponds to one of the 144 symbols). The largest sum is then compared to a threshold (e.g., 4.0) and if the sum exceeds the threshold, the symbol corresponding to the largest sum is determined to be the received symbol. If the largest sum does not exceed the threshold, no symbol is determined to be the received symbol. 
         [0067]    After having determining the received symbol (block  610 ), the example process  600  determines the code corresponding to the received symbol (block  612 ). That is, the example process  600  decodes the encoding of a code into a symbol that was carried out by the example encoding process  400  (e.g., the encoding performed by block  408 ). 
         [0068]    After the decoding is complete and codes are determined from symbols (block  612 ), the example process  600  analyzes the code for validity (block  614 ). For example, the received codes may be examined to determine if the code sequence is valid based on the encoding process by which codes are sent. Valid codes are logged and may be sent back to a central processing facility at a later time, along with a time and date stamp indicating when the codes were received. 
         [0069]    While example manners of implementing any or all of the example encoder  102  and the example decoder  116  have been illustrated and described above one or more of the data structures, elements, processes and/or devices illustrated in the drawings and described above may be combined, divided, re-arranged, omitted, eliminated and/or implemented in any other way. Further, the example encoder  102  and example decoder  116  may be implemented by hardware, software, firmware and/or any combination of hardware, software and/or firmware. Thus, for example, the example encoder  102  and the example decoder  116  could be implemented by one or more circuit(s), programmable processor(s), application specific integrated circuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)) and/or field programmable logic device(s) (FPLD(s)), etc. For example, the decoder  116  may be implemented using software on a platform device, such as a mobile telephone. If any of the appended claims is read to cover a purely software implementation, at least one of the example sampler  202 , the example masking evaluator  204 , the example code frequency selector  206 , the example code synthesizer  208 , and the example combiner  210  of the encoder  102  and/or one or more of the example sampler  502 , the example time to frequency domain converter  504 , the example code frequency monitor  506 , the example statistical processor  508 , the example symbol determiner  510  and/or the example validity checker  512  of the example decoder  116  are hereby expressly defined to include a tangible medium such as a memory, DVD, CD, etc. Further still, the example encoder  102  and the example decoder  116  may include data structures, elements, processes and/or devices instead of, or in addition to, those illustrated in the drawings and described above, and/or may include more than one of any or all of the illustrated data structures, elements, processes and/or devices. 
         [0070]      FIG. 7  is a schematic diagram of an example processor platform  700  that may be used and/or programmed to implement any or all of the example encoder  102  and the decoder  116 , and/or any other component described herein. For example, the processor platform  700  can be implemented by one or more general purpose processors, processor cores, microcontrollers, etc. Additionally, the processor platform  700  may be implemented as a part of a device having other functionality. For example, the processor platform  700  may be implemented using processing power provided in a mobile telephone, or any other handheld device. 
         [0071]    The processor platform  700  of the example of  FIG. 7  includes at least one general purpose programmable processor  705 . The processor  705  executes coded instructions  710  and/or  712  present in main memory of the processor  705  (e.g., within a RAM  715  and/or a ROM  720 ). The processor  705  may be any type of processing unit, such as a processor core, a processor and/or a microcontroller. The processor  705  may execute, among other things, example machine accessible instructions implementing the processes described herein. The processor  705  is in communication with the main memory (including a ROM  720  and/or the RAM  715 ) via a bus  725 . The RAM  715  may be implemented by DRAM, SDRAM, and/or any other type of RAM device, and ROM may be implemented by flash memory and/or any other desired type of memory device. Access to the memory  715  and  720  may be controlled by a memory controller (not shown). 
         [0072]    The processor platform  700  also includes an interface circuit  730 . The interface circuit  730  may be implemented by any type of interface standard, such as a USB interface, a Bluetooth interface, an external memory interface, serial port, general purpose input/output, etc. One or more input devices  735  and one or more output devices  740  are connected to the interface circuit  730 . 
         [0073]    Although certain example apparatus, methods, and articles of manufacture are described herein, other implementations are possible. The scope of coverage of this patent is not limited to the specific examples described herein. On the contrary, this patent covers all apparatus, methods, and articles of manufacture falling within the scope of the invention.