Patent Publication Number: US-9418670-B2

Title: Encoding apparatus, encoding method, and program

Description:
CROSS REFERENCE TO PRIOR APPLICATION 
     This application is a continuation of U.S. patent application Ser. No. 13/285,310 (filed on Oct. 31, 2011), which claims priority to Japanese Patent Application No. 2010-250614 (filed on Nov. 9, 2010), which are all hereby incorporated by reference in their entirety. 
    
    
     BACKGROUND 
     The present disclosure relates to encoding apparatuses, encoding methods, and programs, and particularly relates to an encoding apparatus, an encoding method, and a program which are capable of accurately encoding an audio signal including noise in a certain band. 
     In general, examples of a method for encoding an audio signal include a method for performing normalization and quantization on frequency spectra obtained by performing time-frequency transform on an audio signal (refer to Japanese Unexamined Patent Application Publication No. 2006-11170, for example). 
       FIG. 1  is a block diagram illustrating a configuration of an audio encoding apparatus which performs encoding in such an encoding method. 
     An audio encoding apparatus  10  shown in  FIG. 1  includes a time-frequency transform unit  11 , a normalization unit  12 , a bit allocation calculation unit  13 , a quantization unit  14 , and a code-string encoder  15 . The audio encoding apparatus  10  encodes an audio signal input as a time-series signal and outputs a code string. 
     Specifically, the time-frequency transform unit  11  included in the audio encoding apparatus  10  performs time-frequency transform on an audio signal input as a time-series signal and outputs frequency spectra mdspec. For example, the time-frequency transform unit  11  performs time-frequency transform on a time-series signal of 2N samples using orthogonal transform such as MDCT (Modified Discrete Cosine Transform) and outputs N MDCT coefficients obtained as a result of the time-frequency transform as the frequency spectra mdspec. 
     The normalization unit  12  performs normalization on the frequency spectra mdspec supplied from the time-frequency transform unit  11  for each predetermined processing unit using normalization coefficients obtained in accordance with amplitudes of the frequency spectra mdspec. The normalization unit  12  outputs normalization information idsf which is information on integer numbers corresponding to the normalization coefficients and normalization frequency spectra nspec obtained by normalizing the frequency spectra mdspec. 
     The bit allocation calculation unit  13  performs bit allocation calculation such that the numbers of bits to be allocated to the normalization frequency spectra nspec are calculated for each predetermined processing unit in accordance with the normalization information idsf supplied from the normalization unit  12  so as to output quantization information idwl representing the numbers of bits. Furthermore, the bit allocation calculation unit  13  outputs the normalization information idsf supplied from the normalization unit  12 . 
     The quantization unit  14  quantizes the normalization frequency spectra nspec supplied from the normalization unit  12  in accordance with the quantization information idwl supplied from the bit allocation calculation unit  13 . Specifically, the quantization unit  14  quantizes the normalization frequency spectra nspec for each predetermined processing unit using quantization coefficients corresponding to the quantization information idwl. The quantization unit  14  outputs a quantization frequency spectra qspec as a result of the quantization. 
     The code-string encoder  15  encodes the normalization information idsf and the quantization information idwl which are supplied from the bit allocation calculation unit  13  and the frequency spectra qspec supplied from the quantization unit  14  and outputs a code string obtained as a result of the encoding. The output code string may be transmitted to another apparatus or may be recorded in a certain recording medium. 
     Furthermore, in recent years, an audio signal processed by audio encoding apparatuses is expanded from a PCM (Pulse Code Modulation) signal of a frequency of 44.1 kHz and a PCM word length of 16 bits and a PCM signal of a frequency of 48 kHz and a PCM word length of 16 bits to a PCM signal having high-quality multi bits such as a PCM signal of a frequency of 96 kHz and a PCM word length of 24 bits and a PCM signal of a frequency of 192 kHz and a PCM word length of 24 bits. 
     Such a high-quality multi-bit PCM signal is not generated as a multi-bit PCM signal from the beginning but is generated using a PDM (Pulse Density Modulation) signal such as a DSD (Direct Stream Digital) signal as a source in many cases. 
     This is because, in a field of an A/D converter used to convert an analog audio signal into a digital audio signal, a replacement of a successive-approximation A/D converter by a delta-sigma A/D converter has been rapidly progressed. 
     More specifically, a general successive-approximation A/D converter may directly generate a multi-bit PCM signal but conversion accuracy is considerably restricted by element accuracy. Therefore, when a PCM word length is equal to or larger than 24 bits, it is difficult to ensure linearity of the A/D conversion. On the other hand, in a delta-sigma A/D converter, A/D conversion is easily performed with high accuracy using a single threshold value. In view of such a background, as an A/D converter, the delta-sigma A/D converter has been widely used instead of the general successive-approximation A/D converter. 
       FIG. 2  is a diagram illustrating an input signal and an output signal of an 1-bit delta-sigma A/D converter. As shown in  FIG. 2 , in the 1-bit delta-sigma A/D converter, an analog audio signal serving as an input signal is converted into a 1-bit PDM signal which has amplitude represented by time density of +1 and which serves as an output signal. 
       FIG. 3  is a diagram illustrating quantization noise in the delta-sigma A/D converter. As shown in  FIG. 3 , first, in the delta-sigma A/D converter, the quantization noise included in an audio band (0 to fs/2 in the example shown in  FIG. 3 ) is dispersed in a wide band (0 to nfs/2 in the example shown in  FIG. 3 ) by performing oversampling. Next, the quantization noise is shifted out of the audio band by performing noise shaping. Accordingly, the delta-sigma A/D converter may realize a high S/N (signal/noise) ratio in the audio band. 
     As described above, when a source of a high-quality multi-bit PCM signal is a PDM signal obtained by the delta-sigma A/D converter, the multi-bit PCM signal is generated by performing a LPF (Low Pass Filter) process on the PDM signal. 
     The multi-bit PCM signal obtained as described above is represented as a delta-sigma type A as shown in  FIG. 4 . This quantization noise is undesired noise for the multi-bit PCM signal. 
     SUMMARY 
     However, in the audio encoding apparatus  10  shown in  FIG. 1 , since the bit allocation calculation is performed in accordance with normalization information idsf of an input audio signal, when the multi-bit PCM signal is input, a number of bits are allocated to normalization frequency spectra nspec out of the audio band which includes undesired quantization noise. 
     Accordingly, the number of bits which may be allocated to the normalization frequency spectra nspec in the audio band which is important in terms of acoustic sense is reduced and encoding accuracy is deteriorated. As a result, even if an audio signal to be subjected to encoding is a high-quality multi-bit PCM signal, it may be possible that an audio signal having high quality is not recorded and transmitted. 
     It is desirable to accurately encode an audio signal including noise in a certain band. 
     According to an embodiment of the present disclosure, there is provided an encoding apparatus includes a noise detector configured to detect noise included in a certain band in accordance with an audio signal, a gain controller configured to perform gain control on the audio signal so that components in the certain band of the audio signal are attenuated when the noise is detected by the noise detector, a bit allocation calculation unit configured to calculate the numbers of bits to be allocated to frequency spectra of the audio signal which have been subjected to the gain control performed by the gain controller in accordance with the frequency spectra, and a quantization unit configured to quantize the frequency spectra of the audio signal which have been subjected to the gain control in accordance with the numbers of the bits. 
     According to another embodiment of the present disclosure, there is provided an encoding method and a program corresponding to the encoding apparatus of the embodiment of the present disclosure. 
     According to a further embodiment of the present disclosure, noise included in a certain band is detected in accordance with an audio signal, gain control is performed on the audio signal so that components in the certain band of the audio signal are attenuated when the noise is detected by the noise detector, the numbers of bits to be allocated to frequency spectra of the audio signal which have been subjected to the gain control performed by the gain controller are calculated in accordance with the frequency spectra, and the frequency spectra of the audio signal which have been subjected to the gain control are quantized in accordance with the numbers of the bits. 
     The encoding apparatus according to the embodiment of the present disclosure may be independently provided or may be configured as an internal block of an apparatus. 
     Accordingly, an audio signal including noise in a certain band may be encoded with high accuracy. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram illustrating a configuration of a general audio encoding apparatus; 
         FIG. 2  is a diagram illustrating an input signal and an output signal of an 1-bit delta-sigma A/D converter; 
         FIG. 3  is a diagram illustrating quantization noise in the delta-sigma A/D converter; 
         FIG. 4  is a diagram illustrating a multi-bit PCM signal; 
         FIG. 5  is a block diagram illustrating a configuration of an audio encoding apparatus according to a first embodiment of the present disclosure; 
         FIG. 6  is a block diagram illustrating a configuration of a noise detector and a gain controller in detail; 
         FIG. 7  is a diagram illustrating the relationships between normalization information and normalization coefficients; 
         FIG. 8  is a flowchart illustrating an encoding process performed by the audio encoding apparatus shown in  FIG. 5 ; 
         FIG. 9  is a flowchart illustrating a noise reduction process shown in  FIG. 8 ; 
         FIG. 10  is a diagram illustrating another configuration of the noise detector and the gain controller shown in  FIG. 5  in detail; 
         FIG. 11  is a diagram illustrating frequency spectra; 
         FIG. 12  is a diagram illustrating a first noise detection process performed on the frequency spectra; 
         FIG. 13  is a diagram illustrating a second noise detection process performed on the frequency spectra; 
         FIG. 14  is a diagram illustrating a third noise detection process performed on the frequency spectra; 
         FIG. 15  is a diagram illustrating first gain control performed on the frequency spectra; 
         FIG. 16  is a diagram illustrating second gain control performed on the frequency spectra; 
         FIG. 17  is a diagram illustrating third gain control performed on the frequency spectra; 
         FIG. 18  is a flowchart illustrating another noise reduction process shown in  FIG. 8 ; 
         FIG. 19  is a block diagram illustrating a configuration of an audio encoding apparatus according to a second embodiment of the present disclosure; 
         FIG. 20  is a flowchart illustrating an encoding process performed by the audio encoding apparatus shown in  FIG. 19 ; 
         FIG. 21  is a block diagram illustrating a configuration of an audio encoding apparatus according to a third embodiment of the present disclosure; 
         FIG. 22  is a diagram illustrating frequency spectra output from a time-frequency transform unit; 
         FIG. 23  is a diagram illustrating a first noise detection process performed on normalization information; 
         FIG. 24  is a diagram illustrating a second noise detection process performed on normalization information; 
         FIG. 25  is a diagram illustrating a third noise detection process performed on normalization information; 
         FIG. 26  is a diagram illustrating gain control performed on normalization information; 
         FIG. 27  is a flowchart illustrating an encoding process performed by the audio encoding apparatus shown in  FIG. 21 ; 
         FIG. 28  is a block diagram illustrating a configuration of a decoding apparatus; 
         FIG. 29  is a diagram illustrating normalization information; 
         FIG. 30  is a diagram illustrating frequency spectra obtained as a result of inverse normalization; 
         FIG. 31  is a flowchart illustrating a decoding process performed by the audio encoding apparatus shown in  FIG. 28 ; and 
         FIG. 32  is a diagram illustrating a configuration of a computer according to an embodiment. 
     
    
    
     DETAILED DESCRIPTION OF EMBODIMENTS 
     First Embodiment 
     Example of Configuration of Audio Encoding Apparatus of First Embodiment 
       FIG. 5  is a block diagram illustrating a configuration of an audio encoding apparatus according to a first embodiment of the present disclosure. 
     In the configuration shown in  FIG. 5 , configurations the same as those shown in  FIG. 1  are denoted by reference numerals the same as those shown in  FIG. 1 . Redundant descriptions are appropriately omitted. 
     The configuration of an audio encoding apparatus  50  shown in  FIG. 5  is different from that shown in  FIG. 1  in that a noise detector  51  and a gain controller  52  are disposed before a time-frequency transform unit  11 . When detecting noise unique to a PDM signal in accordance with an input audio signal, the audio encoding apparatus  50  attenuates and encodes high-frequency components out of an audio band including the noise unique to a PDM signal. 
     Specifically, the noise detector  51  of the audio encoding apparatus  50  performs a noise detection process to detect the noise unique to a PDM signal in accordance with an audio signal input as a time-series signal and outputs a control signal c representing a result of the detection. Note that the noise unique to a PDM signal is quantization noise generated by a delta-sigma A/D converter. The noise is temporally continued in a high-frequency band out of the audio band, is comparatively large, and has a tendency of monotonic increase. 
     The gain controller  52  performs gain control on the audio signal input as the time-series signal in accordance with the control signal c supplied from the noise detector  51 . Specifically, when the control signal c represents detection of noise, the gain controller  52  controls gain of the audio signal such that components in the high-frequency band out of the audio band of the audio signal attenuate and supplies a resultant audio signal to the time-frequency transform unit  11 . On the other hand, when the control signal c represents that noise has not been detected, the gain controller  52  supplies the audio signal to the time-frequency transform unit  11  without change. 
     Configurations of Noise Detector and Gain Controller 
       FIG. 6  is a block diagram illustrating configurations of the noise detector  51  and the gain controller  52  in detail. 
     The noise detector  51  shown in  FIG. 6  includes an HPF (High Pass Filter) unit  61  and a detector  62 , and the gain controller  52  includes an LPF unit  71 . The noise detector  51  and the gain controller  52  shown in  FIG. 6  perform the noise detection process and the gain control, respectively, on a time-region signal of an audio signal. 
     Specifically, the HPF unit  61  of the noise detector  51  shown in  FIG. 6  performs the HPF process on the audio signal input as the time-series signal so as to extract and output high-frequency components out of the audio band of the audio signal. 
     The detector  62  performs the noise detection process in accordance with a power or the like of a high-frequency component out of the audio band of the audio signal supplied from the HPF unit  61  so as to output the control signal c. Specifically, when a power of a high-frequency component out of the audio band of the audio signal is equal to or larger than a threshold value, for example, the detector  62  outputs a control signal c representing detection of noise. On the other hand, when the power of the high-frequency component out of the audio band of the audio signal is smaller than the threshold value, the detector  62  outputs a control signal c representing that noise has not been detected. 
     When the control signal c represents detection of noise in accordance with the control signal c supplied from the detector  62 , the LPF unit  71  of the gain controller  52  performs an LPF process on the audio signal so as to attenuate the high-frequency component out of the audio band of the audio signal. Then, the LPF unit  71  supplies the audio signal in which the high-frequency component out of the audio band is attenuated to the time-frequency transform unit  11 . On the other hand, when the control signal c represents that noise has not been detected, the LPF unit  71  supplies the audio signal to the time-frequency transform unit  11  without change. 
     Relationship Between Normalization Information and Normalization Coefficients 
       FIG. 7  is a diagram illustrating the relationships between normalization information idsf and normalization coefficients sf(idsf). 
     As shown in  FIG. 7 , each of the normalization coefficients sf(idsf) is the power of two and the normalization information idsf is an integer number unique to each of the normalization coefficients. 
     Process of Audio Encoding Apparatus 
       FIG. 8  is a flowchart illustrating an encoding process performed by the audio encoding apparatus  50  shown in  FIG. 5 . The encoding process is started when an audio signal which is a time-series signal is supplied to the audio encoding apparatus  50 . 
     In step S 11  of  FIG. 8 , the noise detector  51  and the gain controller  52  of the audio encoding apparatus  50  performs a noise reduction process to reduce noise unique to a PDM signal. The noise reduction process will be described in detail with reference to  FIGS. 9 and 18  hereinafter. 
     In step S 12 , the time-frequency transform unit  11  performs time-frequency transform on the audio signal supplied from the gain controller  52  as a result of the noise reduction process performed in step S 11  and outputs a resultant frequency spectra mdspec. 
     In step S 13 , the normalization unit  12  performs normalization on the frequency spectra mdspec supplied from the time-frequency transform unit  11  for each predetermined processing unit using normalization coefficients sf(idsf) obtained in accordance with amplitudes of the frequency spectra mdspec. The normalization unit  12  outputs normalization information idsf corresponding to the normalization coefficients sf(idsf) and normalization frequency spectra nspec. 
     In step S 14 , the bit allocation calculation unit  13  performs bit allocation calculation for each predetermined processing unit in accordance with the normalization information idsf supplied from the normalization unit  12  and outputs quantization information idwl. Furthermore, the bit allocation calculation unit  13  outputs the normalization information idsf supplied from the normalization unit  12 . 
     In step S 15 , the quantization unit  14  performs quantization on the normalization frequency spectra nspec supplied from the normalization unit  12  for each processing unit using the quantization coefficients corresponding to the quantization information idwl supplied from the bit allocation calculation unit  13 . The quantization unit  14  outputs quantization frequency spectra qspec obtained as a result of the quantization. 
     In step S 16 , the code-string encoder  15  encodes the normalization information idsf and the quantization information idwl which are supplied from the bit allocation calculation unit  13  and the frequency spectra qspec output from the quantization unit  14  and outputs a code string obtained as a result of the encoding. Then, the process is terminated. 
       FIG. 9  is a flowchart illustrating the noise reduction process performed in step S 11  of  FIG. 8 . 
     In step S 31  of  FIG. 9 , the HPF unit  61  of the noise detector  51  shown in  FIG. 6  performs an HPF process on an audio signal input as a time-series signal so as to extract and output high-frequency components out of the audio band of the audio signal. 
     In step S 32 , the detector  62  performs the noise detection process in accordance with powers or the like of high-frequency components out of the audio band of the audio signal supplied from the HPF unit  61  so as to output a control signal c. 
     In step S 33 , the LPF unit  71  of the gain controller  52  determines whether noise unique to a PDM signal has been detected through the noise detection process performed in step S 32  in accordance with the control signal c supplied from the detector  62 . When the control signal c represents detection of noise, it is determined that the noise unique to a PDM signal has been detected in step S 33 , and the process proceeds to step S 34 . 
     In step S 34 , the LPF unit  71  performs the LPF process on the audio signal so as to attenuate the high-frequency components out of the audio band of the audio signal and supplies the components to the time-frequency transform unit  11  (shown in  FIG. 5 ). Then, the process returns to step S 11  shown in  FIG. 8  and proceeds to step S 12 . 
     On the other hand, when the control signal c represents that the noise has not been detected, it is determined that the noise unique to a PDM signal has not been detected in step S 33  and the LPF unit  71  supplies the audio signal to the time-frequency transform unit  11  without change. Then, the process returns to step S 11  shown in  FIG. 8  and proceeds to step S 12 . 
     Detailed Examples of Configurations of Noise Detector and Gain Controller 
       FIG. 10  is a block diagram illustrating other configurations of the noise detector  51  and the gain controller  52  in detail. 
     The noise detector  51  shown in  FIG. 51  includes a time-frequency transform unit  101  and a detector  102  and the gain controller  52  includes a controller  111  and a frequency-time transform unit  112 . The noise detector  51  and the gain controller  52  shown in  FIG. 10  perform a noise detection process and gain control, respectively, on a frequency-region signal of an audio signal. 
     Specifically, the time-frequency transform unit  101  of the noise detector  51  shown in  FIG. 10  performs time-frequency transform such as FFT (Fast Fourier Transform) or MDCT on the audio signal input as a time-series signal and outputs resultant frequency spectra. 
     The detector  102  performs the noise detection process in accordance with powers or the like of high-frequency components out of the audio band of the frequency spectra supplied from the time-frequency transform unit  101  so as to output a control signal c. 
     The controller  111  of the gain controller  52  performs gain control on the frequency spectra supplied from the time-frequency transform unit  101  in accordance with the control signal c supplied from the detector  102 . Specifically, when the control signal c represents detection of noise, the controller  111  performs the gain control on the frequency spectra such that the powers of the high-frequency components out of the audio band are monotonically reduced with certain inclination. Then, the controller  111  outputs the frequency spectra obtained after the gain control. On the other hand, when the control signal represents that the noise has not been detected, the controller  111  outputs the frequency spectra without change. 
     The frequency-time transform unit  112  performs frequency-time transform such as IFFT (Inverse Fast Fourier Transform) or IMDCT (Inverse Modified Discrete Cosine Transform) on the frequency spectra supplied from the controller  111 . By this, when the noise unique to a PDM signal is detected, an audio signal in which high-frequency components out of the audio band are attenuated is obtained whereas when the noise unique to a PDM signal is not detected, an original audio signal input to the audio encoding apparatus  50  is obtained. The frequency-time transform unit  112  supplies the audio signal obtained as a result of the frequency-time transform to the time-frequency transform unit  11  shown in  FIG. 5 . 
     Noise Detection Process 
       FIGS. 11 to 14  are diagrams illustrating first to third examples of the noise detection process performed by the detector  102  shown in  FIG. 10 . Note that, in  FIGS. 11 to 14 , an axis of abscissa denotes an index of a frequency spectrum and an axis of ordinate denotes a power of a frequency spectrum. The same is true to  FIGS. 15 to 17  which will be described hereinafter. 
       FIG. 11  is a diagram illustrating frequency spectra output from the time-frequency transform unit  101 . 
     In the example shown in  FIG. 11 , a sampling frequency of an audio signal input as a time-series signal is 96 kHz, and among N frequency spectra having indices of 0 to N−1, N/2 frequency spectra having indices of N/2 to N−1 correspond to frequency spectra having high frequency components out of the audio band. 
       FIG. 12  is a diagram illustrating the first noise detection process performed on the frequency spectra shown in  FIG. 11 . Note that, in  FIG. 12 , solid lines represent powers of the frequency spectra shown in  FIG. 11 , a middle-thick line represents a total power of the frequency spectra out of the audio band, and a bold line represents a predetermined threshold value. 
     As shown in  FIG. 12 , in the first example of the noise detection process, when the total power of the frequency spectra out of the audio band is equal to or larger than the predetermined threshold value, noise unique to a PDM signal is detected. 
       FIG. 13  is a diagram illustrating the second noise detection process performed on the frequency spectra shown in  FIG. 11 . Note that, in  FIG. 13 , solid lines represent the powers of the frequency spectra shown in  FIG. 11 , middle-thick lines represent total powers of groups of the frequency spectra, and a bold line represents the predetermined threshold value. 
     As shown in  FIG. 13 , in the second example of the noise detection process, when all the total powers of the groups of the frequency spectra out of the audio band are equal to or larger than the predetermined threshold value, noise unique to a PDM signal is detected. 
       FIG. 14  is a diagram illustrating the third noise detection process performed on the frequency spectra shown in  FIG. 11 . Note that, in  FIG. 14 , solid lines represent the powers of the frequency spectra shown in  FIG. 11 , and middle-thick lines represent the total powers of groups of the frequency spectra. 
     As shown in  FIG. 14 , in the third example of the noise detection process, when the total powers of the groups of the frequency spectra out of the audio band are monotonically increased, noise unique to a PDM signal is detected. 
     Note that, in the second and third examples of the noise detection process, the determinations are made on the basis of the total powers of the groups. However, a determination may be made in accordance with the powers of the individual frequency spectra. 
     Furthermore, the noise detection process performed by the detector  102  may be one of the first to third examples or may be a combination of the first to third examples. Furthermore, the noise detection process performed by the detector  102  is not limited to the first to third examples described above. 
     Gain Control 
       FIGS. 15 to 17  are diagrams illustrating first and second examples of the gain control performed by the controller  111  on the frequency spectra shown in  FIG. 11 . 
       FIG. 15  is a diagram illustrating the first example of the gain control. Note that, in  FIG. 15 , dotted lines denote the frequency spectra shown in  FIG. 11  which have not been subjected to the gain control, solid lines denote frequency spectra which have been subjected to the gain control, and a bold line denotes inclination of the gain control. 
     As shown in  FIG. 15 , in the first example of the gain control, gains of the frequency spectra are controlled so that powers of the frequency spectra out of the audio band are monotonically reduced in a predetermined inclination. 
       FIGS. 16 and 17  are diagrams illustrating the second example of the gain control. Note that, in  FIGS. 16 and 17 , dotted lines denote the frequency spectra shown in  FIG. 11  which have not been subjected to the gain control and a bold line denotes inclination of the gain control. Furthermore, middle-thick lines shown in  FIG. 16  denote total powers of groups including a plurality of frequency spectra, and solid lines shown in  FIG. 17  denote frequency spectra which have been subjected to the gain control. 
     As shown in  FIG. 16 , in the second example of the gain control, the frequency spectra out of the audio band are divided into groups each of which includes some of the frequency spectra. Then, as shown in  FIG. 17 , gains of the frequency spectra are controlled so that total powers of the groups are monotonically reduced in a predetermined inclination. 
     Note that the gain control performed by the controller  111  is not limited to the first and second examples described above. 
     Another Noise Reduction Process 
       FIG. 18  is a flowchart illustrating a noise reduction process performed in step S 11  of  FIG. 8  by the noise detector  51  and the gain controller  52  shown in  FIG. 10 . 
     In step S 51  shown in  FIG. 18 , the time-frequency transform unit  101  of the noise detector  51  shown in  FIG. 10  performs time-frequency transform on an audio signal input as a time-series signal and outputs resultant frequency spectra. 
     In step S 52 , the detector  102  performs the noise detection process described with reference to  FIGS. 11 to 14  in accordance with the powers or the like of the high-frequency components out of the audio band of the frequency spectra supplied from the time-frequency transform unit  101  so as to output a control signal c. 
     In step S 53 , the controller  111  of the gain controller  52  determines whether noise unique to a PDM signal has been detected through the noise detection process performed in step S 52  in accordance with the control signal c supplied from the detector  102 . When the control signal c represents detection of noise, it is determined that the noise unique to a PDM signal has been detected in step S 53 , and the process proceeds to step S 54 . 
     In step S 54 , the controller  111  performs the gain control on the frequency spectra output from the time-frequency transform unit  101  so that the powers of the high-frequency components out of the audio band are monotonically reduced in the predetermined inclination as shown in  FIGS. 15 to 17 . Then, the controller  111  outputs the frequency spectra obtained after the gain control, and the process proceeds to step S 55 . 
     On the other hand, when the control signal c represents that the noise has not been detected, it is determined that the noise unique to a PDM signal has not been detected in step S 53  and the LPF unit  111  supplies the frequency spectra supplied from the time-frequency transform unit  101  without change. Then, the process proceeds to step S 55 . 
     In step S 55 , the frequency-time transform unit  112  performs frequency-time transform on the frequency spectra supplied from the controller  111 . The frequency-time transform unit  112  supplies a resultant audio signal to the time-frequency transform unit  11  shown in  FIG. 5 . Then, the process returns to step S 11  shown in  FIG. 8  and proceeds to step S 12 . 
     As described above, the audio encoding apparatus  50  performs the noise detection process in accordance with an audio signal before performing the bit allocation calculation. Furthermore, when the noise unique to a PDM signal is detected through the noise detection process, the audio signal is subjected to the gain control so that the high frequency components out of the audio band of the audio signal attenuate. By this, the number of bits allocated to the noise unique to a PDM signal may be reduced and the number of bits allocated to the audio band which is important in terms of acoustic sense may be increased. As a result, high-accuracy encoding may be performed on a multi-bit PCM signal generated from a PDM signal including noise unique to a PDM signal. Accordingly, a high-quality multi-bit PCM signal may be recorded and transmitted with high quality. 
     Second Embodiment 
     Example of Configuration of Audio Encoding Apparatus of Second Embodiment 
       FIG. 19  is a block diagram illustrating a configuration of an audio encoding apparatus according to a second embodiment of the present disclosure. 
     In  FIG. 19 , components the same as those shown in  FIG. 1  are denoted by reference numerals the same as those shown in  FIG. 1 . Redundant descriptions are appropriately omitted. 
     A configuration of an audio encoding apparatus  150  shown in  FIG. 19  is different from the configuration shown in  FIG. 1  in that a noise detector  151  and a gain controller  152  are disposed between a time-frequency transform unit  11  and a normalization unit  12 . The audio encoding apparatus  150  performs a noise detection process and gain control on frequency spectra mdspec obtained by the time-frequency transform unit  11 . 
     Specifically, the noise detector  151  of the audio encoding apparatus  150  is configured similarly to the detector  102  shown in  FIG. 10 . The detector  151  performs a noise detection process as shown in  FIGS. 11 to 14  in accordance with powers or the like of high-frequency components out of an audio band of frequency spectra supplied from the time-frequency transform unit  11  so as to output a control signal c. 
     The gain controller  152  is configured similarly to the controller  111  shown in  FIG. 10 . The gain controller  152  performs gain control on the frequency spectra supplied from the time-frequency transform unit  11  in accordance with the control signal c supplied from the noise detector  151 . Specifically, when the control signal c represents detection of noise, the gain controller  152  performs the gain control described with reference to  FIGS. 15 to 17  on the frequency spectra such that the powers of the high-frequency components out of the audio band are monotonically reduced with certain inclination. Then, the gain controller  152  outputs frequency spectra mdspec′ obtained after the gain control. On the other hand, when the control signal represents that the noise has not been detected, the gain controller  152  outputs the frequency spectra mdspec without change as the frequency spectra mdspec′. The frequency spectra mdspec′ output from the gain controller  152  are supplied to the normalization unit  12 . 
     Processing of Audio Encoding Apparatus 
       FIG. 20  is a flowchart illustrating an encoding process performed by the audio encoding apparatus  150  shown in  FIG. 19 . The encoding process is started when an audio signal which is a time-series signal is supplied to the audio encoding apparatus  150 . 
     In step S 71  of  FIG. 20 , the time-frequency transform unit  11  performs time-frequency transform on the audio signal input as the time-series signal and outputs resultant frequency spectra mdspec. 
     In step S 72 , the detector  151  performs the noise detection process as described in  FIGS. 11 to 14  on the basis of powers or the like of high-frequency components out of the audio band of the frequency spectra mdspec supplied from the time-frequency transform unit  11  so as to output a control signal c. 
     In step S 73 , the gain controller  152  determines whether noise unique to a PDM signal has been detected through the noise detection process performed in step S 72  in accordance with the control signal c supplied from the noise detector  151 . When the control signal c represents detection of noise, it is determined that the noise unique to a PDM signal has been detected in step S 73 , and the process proceeds to step S 74 . 
     In step S 74 , the controller  152  performs gain control on the frequency spectra mdspec output from the time-frequency transform unit  11  so that the powers of the high-frequency components out of the audio band are monotonically reduced in predetermined inclination as shown in  FIGS. 15 to 17 . Then, the gain controller  152  outputs frequency spectra mdspec′ obtained after the gain control, and the process proceeds to step S 75 . 
     On the other hand, when the control signal c represents that the noise has not been detected, it is determined that the noise unique to a PDM signal has not been detected in step S 73  and the gain controller  152  outputs the frequency spectra mdspec as frequency spectra mdspec′ without change. Then, the process proceeds to step S 75 . 
     In step S 75 , the normalization unit  12  performs normalization on the frequency spectra mdspec′ supplied from the gain controller  152  for each predetermined processing unit using normalization coefficients sf(idsf) corresponding to amplitudes of the frequency spectra mdspec′. The normalization unit  12  outputs normalization information idsf corresponding to the normalization coefficients sf(idsf) and normalization frequency spectra nspec obtained as a result of the normalization. 
     The process from step S 76  to step S 78  is the same as the process from step S 14  to step S 16  shown in  FIG. 8 , and therefore, a description thereof is omitted. 
     As described above, the audio encoding apparatus  150  performs the noise detection process in accordance with the frequency spectra of the audio signal before performing the bit allocation calculation. Furthermore, when the noise unique to a PDM signal is detected through the noise detection process, the frequency spectra are subjected to the gain control so that the high frequency components out of the audio band of the audio signal attenuate. By this, the number of bits allocated to the noise unique to a PDM signal may be reduced and the number of bits allocated to the audio band which is important in terms of acoustic sense may be increased. As a result, high-accuracy encoding may be performed on a multi-bit PCM signal generated from a PDM signal including the noise unique to a PDM signal. Accordingly, a high-quality multi-bit PCM signal may be recorded and transmitted with high quality. 
     Furthermore, since the audio encoding apparatus  150  performs the noise detection process and the gain control using the frequency spectra mdspec obtained by the time-frequency transform unit  11 , the number of modules to be added to the general audio encoding apparatus  10  may be reduced when compared with the audio encoding apparatus  50 . Specifically, for example, unlike the audio encoding apparatus  50 , the time-frequency transform unit  101  and the frequency-time transform unit  112  may not be additionally used. Accordingly, the audio encoding apparatus  150  may be easily obtained by converting the general audio encoding apparatus  10 . 
     Furthermore, since the audio encoding apparatus  150  performs the noise detection process and the gain control in the course of the encoding process, processing delay may be reduced when compared with the audio encoding apparatus  50 . 
     Third Embodiment 
     Example of Configuration of Audio Encoding Apparatus of Third Embodiment 
       FIG. 21  is a block diagram illustrating a configuration of an audio encoding apparatus according to a third embodiment of the present disclosure. 
     In  FIG. 21 , components the same as those shown in  FIG. 1  are denoted by reference numerals the same as those shown in  FIG. 1 . Redundant descriptions are appropriately omitted. 
     The configuration of an audio encoding apparatus  200  shown in  FIG. 21  is different from the configuration shown in  FIG. 1  in that a noise detector  201  and a gain controller  202  are disposed between a normalization unit  12  and a normalization unit  13 . The audio encoding apparatus  200  performs a noise detection process and gain control on normalization information idsf of an input audio signal. 
     Specifically, the noise detector  201  of the audio encoding apparatus  200  performs a noise detection process in accordance with normalization information idsf supplied from the normalization unit  12  and outputs a control signal c. 
     The gain controller  202  performs gain control on the normalization information idsf supplied from the normalization unit  12  in accordance with the control signal c supplied from the noise detector  201 . Specifically, when the control signal c represents detection of noise, the gain controller  202  performs the gain control on the normalization information idsf such that powers of high-frequency components out of an audio band are monotonically reduced with certain inclination. Then, the gain controller  202  outputs normalization information idsf′ obtained after the gain control. On the other hand, when the control signal c represents that the noise has not been detected, the gain controller  202  outputs the normalization information idsf without change as normalization information idsf′. The normalization information idsf′ output from the gain controller  202  is supplied to the bit allocation calculation unit  13 . 
     Noise Detection Process 
       FIGS. 22 to 25  are diagrams illustrating first to third noise detection processes performed by the noise detector  201  shown in  FIG. 21 . Note that, in  FIG. 22 , an axis of abscissa denotes an index of a frequency spectrum and an axis of ordinate denotes a power of a frequency spectrum. Note that, in  FIGS. 23 to 25 , an axis of abscissa denotes an index of normalization information and an axis of ordinate denotes normalization information. 
       FIG. 22  is a diagram illustrating frequency spectra mdspec output from the time-frequency transform unit  11 . Note that, in  FIG. 22 , solid lines denote powers of the frequency spectra mdspec. 
     In the example shown in  FIG. 22 , as with the case of  FIG. 11 , a sampling frequency of an audio signal input as a time-series signal is 96 kHz, and among N frequency spectra having indices of 0 to N−1, N/2 frequency spectra having indices of N/2 to N−1 correspond to frequency spectra having high frequency components out of an audio band. 
     Furthermore, normalization and quantization are performed on the frequency spectra mdspec for individual so-called critical band widths denoted by bold lines in  FIG. 22 . Each of the critical band widths is generally narrower in a lower band and wider in a higher band taking an audio-sense characteristic into consideration. For example, in  FIG. 22 , the lowest critical band width including the index number 0 includes two frequency spectra mdspec and the highest critical band width including the index number N−1 includes eight frequency spectra mdspec. 
     Note that, here, a critical band width which is a processing unit for normalization and quantization is referred to as a quantization unit, and N frequency spectra mdspec are divided into M quantization units as groups. 
       FIG. 23  is a diagram illustrating the first noise detection process performed on the normalization information idsf which is a quantization unit of the frequency spectra mdspec shown in  FIG. 22 . Note that, in  FIG. 23 , solid lines represent the normalization information idsf, a middle thick line represents a sum of the normalization information idsf out of the audio band, and a bold line represents a threshold value. 
     As shown in  FIG. 23 , in the first example of the noise detection process, when the sum of the normalization information idsf of the frequency spectra mdspec out of the audio band is equal to or larger than the predetermined threshold value, noise unique to a PDM signal is detected. 
       FIG. 24  is a diagram illustrating the second noise detection process performed on the normalization information idsf of the frequency spectra mdspec shown in  FIG. 22 . Note that, in  FIG. 24 , solid lines represent the normalization information idsf and a bold line represents a threshold value. 
     As shown in  FIG. 24 , in the second example of the noise detection process, when all the normalization information idsf of the frequency spectra mdspec out of the audio band is equal to or larger than the predetermined threshold value, the noise unique to a PDM signal is detected. 
       FIG. 25  is a diagram illustrating the third noise detection process performed on the normalization information idsf of the frequency spectra mdspec shown in  FIG. 22 . Note that, in  FIG. 25 , solid lines represent the normalization information idsf. 
     As shown in  FIG. 25 , in the example of the third noise detection process, when the normalization information idsf of the frequency spectra mdspec out of the audio band is monotonically increased, the noise unique to a PDM signal is detected. 
     Note that in the second and third examples of the noise detection process, the determinations are made in accordance with the normalization information idsf. However, the plurality of normalization information idsf may be divided into groups and determination may be made in accordance with the normalization information idsf for individual groups. 
     Furthermore, the noise detection process performed by the noise detector  201  may be one of the first to third examples or may be a combination of the first to third examples. Furthermore, the noise detection process performed by the noise detector  201  is not limited to the first to third examples described above. 
     Gain Control 
       FIG. 26  is a diagram illustrating the gain control performed by the gain controller  202  on the normalization information idsf of the frequency spectra mdspec shown in  FIG. 22 . Note that, in  FIG. 26 , an axis of abscissa denotes an index of normalization information and an axis of ordinate denotes normalization information. Furthermore, in  FIG. 26 , dotted lines represent the normalization information idsf which has not been subjected to the gain control, solid lines represent normalization information idsf′ obtained through the gain control, and a bold line represents inclination of the gain control. 
     As shown in  FIG. 26 , in the gain control performed by the gain controller  202 , gains of the normalization information idsf are controlled so that the normalization information idsf of the frequency spectra mdspec out of the audio band are monotonically reduced with certain inclination. 
     Note that the gain control performed by the gain controller  202  is not limited to the example shown in  FIG. 26 . 
     Process of Audio Encoding Apparatus 
       FIG. 27  is a flowchart illustrating an encoding process performed by the audio encoding apparatus  200  shown in  FIG. 21 . The encoding process is started when an audio signal which is a time-series signal is supplied to the audio encoding apparatus  200 . 
     In step S 101  of  FIG. 27 , the time-frequency transform unit  11  performs time-frequency transform on the audio signal input as the time-series signal and outputs resultant frequency spectra mdspec. 
     In step S 102 , the normalization unit  12  performs normalization on the frequency spectra mdspec supplied from the time-frequency transform unit  11  for each predetermined processing unit using normalization coefficients sf(idsf) corresponding to amplitudes of the frequency spectra mdspec. The normalization unit  12  outputs normalization information idsf corresponding to the normalization coefficients sf(idsf) and normalization frequency spectra nspec obtained as a result of the normalization. 
     In step S 103 , the noise detector  201  performs the noise detection process described with reference to  FIGS. 22 to 25  in accordance with high-frequency components out of the audio band of the normalization information idsf supplied from the normalization unit  12  so as to output a control signal c. 
     In step S 104 , the gain controller  202  determines whether noise unique to a PDM signal has been detected through the noise detection process performed in step S 103  in accordance with the control signal c supplied from the noise detector  201 . When the control signal c represents detection of noise, it is determined that the noise unique to a PDM signal has been detected in step S 103 , and the process proceeds to step S 105 . 
     In step S 105 , the gain controller  202  performs the gain control described with reference to  FIG. 26  on the normalization information idsf output from the normalization unit  12  so that the high-frequency components out of the audio band are monotonically reduced with certain inclination. Then, the gain controller  202  outputs normalization information idsf′ obtained after the gain control, and the process proceeds to step S 106 . 
     On the other hand, when the control signal c represents that the noise has not been detected, it is determined that the noise unique to a PDM signal has not been detected in step S 104  and the gain controller  202  outputs the normalization information idsf as normalization information idsf′ without change. Then, the process proceeds to step S 106 . 
     In step S 106 , the bit allocation calculation unit  13  performs bit allocation calculation for each predetermined processing unit in accordance with the normalization information idsf′ supplied from the gain controller  202  and supplies quantization information idwl to a code-string encoder  15 . Furthermore, the bit allocation calculation unit  13  outputs the normalization information idsf′ supplied from the gain controller  202  to the code-string encoder  15 . 
     The process from step S 107  and step S 108  is the same as the process from step S 15  and step S 16  shown in  FIG. 8 , and therefore, a description thereof is omitted. 
     As described above, the audio encoding apparatus  200  performs the noise detection process in accordance with the normalization information of the audio signal before performing the bit allocation calculation. Furthermore, when the noise unique to a PDM signal is detected through the noise detection process, the normalization information is subjected to the gain control so that high frequency components out of the audio band of the normalization information attenuate. By this, the number of bits allocated to the noise unique to a PDM signal may be reduced and the number of bits allocated to the audio band which is important in terms of acoustic sense may be increased. As a result, high-accuracy encoding may be performed on a multi-bit PCM signal generated from a PDM signal including the noise unique to a PDM signal. Accordingly, a high-quality multi-bit PCM signal may be recorded and transmitted with high quality. 
     Furthermore, since the audio encoding apparatus  200  performs the noise detection process and the gain control using the normalization information idsf obtained by the normalization unit  12 , as with the audio encoding apparatus  150 , the number of modules to be added to the general audio encoding apparatus  10  may be reduced when compared with the audio encoding apparatus  50 . Accordingly, the audio encoding apparatus  200  may be easily obtained by converting the general audio encoding apparatus  10 . 
     Furthermore, since the audio encoding apparatus  200  performs the noise detection process and the gain control in the course of the encoding process, processing delay may be reduced when compared with the audio encoding apparatus  50 . 
     Furthermore, since the normalization information idsf is integer numbers, the audio encoding apparatus  200  may perform the noise detection process and the gain control with the small number of calculations when compared with the audio encoding apparatus  150  which performs the noise detection process and the gain control using the frequency spectra which are real numbers. On the other hand, since the audio encoding apparatus  150  performs the noise detection process and the gain control using the frequency spectra mdspec, the audio encoding apparatus  150  may perform encoding with higher accuracy when compared with the audio encoding apparatus  200 . 
     Example of Configuration of Audio Decoding Apparatus 
       FIG. 28  is a block diagram illustrating a configuration of an audio decoding apparatus  250  which decodes a code string encoded by the audio encoding apparatus  200  shown in  FIG. 21 . 
     The audio decoding apparatus  250  shown in  FIG. 28  includes a code-string decoding unit  251 , an inverse quantization unit  252 , an inverse normalization unit  253 , and a frequency-time transform unit  254 . The audio decoding apparatus  250  decodes a code string supplied from the audio encoding apparatus  200  so as to obtain an audio signal which is a time-series signal. 
     Specifically, the code-string decoding unit  251  of the audio decoding apparatus  250  performs decoding on the code string supplied from the audio encoding apparatus  200  so as to obtain normalization information idsf′, quantization information idwl, and quantization frequency spectra qspec to be output. 
     The inverse quantization unit  252  performs quantization on the quantization frequency spectra qspec supplied from the code-string decoding unit  251  for each processing unit using inverse quantization coefficients corresponding to the quantization information idwl supplied from the bit allocation calculation unit  251 . The inverse quantization unit  252  outputs normalization frequency spectra nspec obtained as a result of the inverse quantization. 
     The inverse normalization unit  253  performs inverse normalization on the normalization frequency spectra nspec supplied from the inverse quantization unit  252  for each processing unit using inverse normalization coefficients corresponding to the normalization information idsf′ supplied from the code-string decoding unit  251 . The inverse normalization unit  253  outputs frequency spectra mdspec″ obtained as a result of the inverse normalization. 
     The frequency-time transform unit  254  performs frequency-time transform on the frequency spectra mdspec″ supplied from the inverse normalization unit  253  and outputs an audio signal which is a time-series signal obtained as a result of the frequency-time transform. For example, the frequency-time transform unit  254  performs frequency-time transform by inverse orthogonal transform such as IMDCT on N MDCT coefficients serving as the frequency spectra mdspec″ and outputs a time-series signal of 2N samples. 
     Inverse Normalization 
       FIGS. 29 and 30  are diagrams illustrating the inverse normalization performed by the inverse normalization unit  253 . Note that, in  FIGS. 29 and 30 , an axis of abscissa denotes an index of a frequency spectrum and an axis of ordinate denotes a power of the frequency spectrum. 
       FIG. 29  is a diagram illustrating the normalization information idsf′ supplied to the inverse normalization unit  253 . Note that, in  FIG. 29 , dotted lines represent the frequency spectra mdspec of the audio signal supplied to the audio encoding apparatus  200  and bold lines represent powers of frequency spectra for each quantization unit corresponding to the normalization information idsf′. 
     In  FIG. 29 , the normalization information idsf′ is obtained when the code-string decoding unit  251  restores the normalization information idsf′ which has been subjected to the gain control described with reference to  FIG. 26 . 
       FIG. 30  is a diagram illustrating the frequency spectra mdspec″ obtained as a result of the inverse normalization performed on the normalization information idsf′ shown in  FIG. 29 . Note that, in  FIG. 30 , dotted lines represent the frequency spectra mdspec of the audio signal supplied to the audio encoding apparatus  200  and solid lines represent the frequency spectra mdspec″ output from the inverse normalization unit  253 . 
     As shown in  FIG. 30 , powers of the frequency spectra for each quantization unit corresponding to the normalization information idsf′ shown in  FIG. 29  are changed for individual frequency spectra due to normalization frequency spectra nspec of the corresponding frequency spectra. Note that the powers of the frequency spectra mdspec″ included in each quantization unit is limited within the powers of the frequency spectra corresponding to the normalization information idsf′ of the quantization unit. 
     Accordingly, an effect of the gain control of the normalization information idsf in the audio encoding apparatus  200  is the same as an effect of the gain control performed for each quantization unit of the frequency spectra mdspec. 
     Process of Audio Decoding Apparatus 
       FIG. 31  is a flowchart illustrating a decoding process performed by the audio encoding apparatus  250  shown in  FIG. 28 . The decoding process is started when a code string output from the audio encoding apparatus  200  is supplied to the audio decoding apparatus  250 . 
     In step S 121  of  FIG. 31 , the code-string decoding unit  251  of the audio decoding apparatus  250  performs decoding on the code string supplied from the audio encoding apparatus  200  so as to obtain normalization information idsf′, quantization information idwl, and quantization frequency spectra qspec to be output. 
     In step S 122 , the inverse quantization unit  252  performs inverse quantization on the quantization frequency spectra qspec supplied from the code-string decoding unit  251  for each processing unit using inverse quantization coefficients corresponding to the quantization information idwl supplied from the code-string decoding unit  251 . The inverse quantization unit  252  outputs normalization frequency spectra nspec obtained as a result of the inverse quantization. 
     In step S 123 , the inverse normalization unit  253  performs inverse normalization on the normalization frequency spectra nspec supplied from the inverse quantization unit  252  for each processing unit using inverse normalization coefficients corresponding to the normalization information idsf′ supplied from the code-string decoding unit  251 . The inverse normalization unit  253  outputs frequency spectra mdspec″ obtained as a result of the inverse normalization. 
     In step S 124 , the frequency-time transform unit  254  performs frequency-time transform on frequency spectra mdspec″ supplied from the inverse normalization unit  253  and outputs an audio signal which is a time-series signal obtained as a result of the frequency-time transform. Then, the process is terminated. 
     As described above, the audio decoding apparatus  250  decodes the code string supplied from the audio encoding apparatus  200  and performs the inverse normalization on the normalization frequency spectra nspec using the inverse normalization coefficients corresponding to the normalization information idsf′ obtained as a result of the decoding. By this, when the normalization information idsf′ corresponds to attenuated high-frequency components out of the audio band, the frequency spectra mdspec″ having attenuated high-frequency components out of the audio band may be obtained as a result of inverse normalization. As a result, a high-accuracy multi-bit PCM signal in which high-frequency components out of the audio band including noise unique to a PDM signal are attenuated may be output. 
     Note that, although not shown, an audio decoding apparatus which decodes a code string output from the audio encoding apparatuses  50  and  150  is configured similarly to the audio decoding apparatus  250  and performs similar processes. Consequently, when the audio encoding apparatus  50 ( 150 ) detects noise unique to a PDM signal, frequency spectra in which high-frequency components out of the audio band are attenuated may be obtained similarly to the audio decoding apparatus  250 . 
     Furthermore, although a sampling frequency of an input audio signal is 96 kHz in the examples shown in  FIGS. 11 and 22 , the sampling frequency is not limited to this and the number of frequency spectra of high-frequency components out of the audio band is also not limited to N/2. For example, the sampling frequency may be 192 kHz. In this case, among N frequency spectra having indices 0 to N−1, 3N/4 frequency spectra having the indices N/4 to N−1 correspond to frequency spectra of high-frequency components out of the audio band. 
     Furthermore, although the noise unique to a PDM signal is detected in this embodiment, the noise detector may detect other noise as long as noise is included in a predetermined band. In this case, the band to be subjected to the gain control includes noise to be detected by the noise detector. 
     Fourth Embodiment 
     Computer to which Technology is Applied 
     Next, the series of processes described above may be performed by hardware or software. When the series of processes is performed by software, programs included in the software are installed in a general-purpose computer or the like. 
     Then,  FIG. 32  illustrates a configuration of a computer to which the programs used to execute the series of processes described above are installed according to an embodiment. 
     The programs may be stored in a storage unit  308  or a ROM (Read Only Memory)  302  serving as a recording medium incorporated in the computer. 
     Alternatively, the programs may be stored (recorded) in a removable medium  311 . The removable medium  311  may be provided as package software. Here, examples of the removable medium  311  include a flexible disk, a CD-ROM (Compact Disc Read Only Memory), an MO (Magneto Optical) disc, a DVD (Digital Versatile Disc), a magnetic disk, and a semiconductor memory. 
     Note that the programs may be installed in the computer from the removable medium  311  through a drive  310  or may be downloaded to the computer through a communication network or a broadcast network and installed in the incorporated storage unit  308 . Specifically, the programs may be transferred from a downloading site to the computer through an artificial satellite for a digital satellite broadcast in a wireless manner or through a network such as a LAN (Local Area Network) or the Internet in a wired manner. 
     The computer includes a CPU (Central Processing Unit)  301  and the CPU  301  is connected to an input/output interface  305  through a bus  304 . 
     When the user inputs an instruction by operating an input unit  306  through the input/output interface  305 , the CPU  301  executes the programs stored in the ROM  302  in accordance with the instruction. Alternatively, the CPU  301  loads the programs stored in the storage unit  308  in a RAM (Random Access Memory)  303  and executes the programs. 
     By this, the CPU  301  performs the processes in accordance with the flowcharts described above or the processes performed by the configurations in the block diagrams described above. Then, the CPU  301  outputs results of the processes from an output unit  307  through the input/output interface  305 , transmits results of the processes from a communication unit  309 , or causes the storage unit  308  to store results of the processes. 
     Note that the input unit  306  includes a keyboard, a mouse, and a microphone. Furthermore, the output unit  307  includes an LCD (Liquid Crystal Display) and a speaker. 
     Here, in this specification, it is not necessarily the case that the processes are performed by the computer in accordance with the programs in time series in the order described in the flowcharts. Specifically, the processes may be performed by the computer in accordance with the programs in parallel or individually (for example, a parallel process or a process using an object). 
     Furthermore, the programs may be processed by a single computer (processor) or may be processed by a plurality of computers in a distribution manner. Furthermore, the programs may be transferred to a remote computer which executes the programs. 
     Embodiments of the present disclosure are not limited to the foregoing embodiments and various modifications may be made without departing from the scope of the present disclosure.