Abstract:
A method to reduce memory requirements for a packet loss concealment algorithm in the event of packet loss in a receiver of pulse code modulated voice signals. Packet losses are concealed by using the spectral analysis filter memory to smooth a signal gap and by using a technique for determining a maximum repeatable waveform range instead of using the pitch period to reproduce lost packets. The invention uses fewer processing resources and results in improved performance compared to a packet loss concealment algorithm under G.711 Appendix I standards.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
   None 
   FIELD OF THE INVENTION 
   The present invention relates generally to providing packet loss concealment in the event of packet loss over a communications network. More specifically, the present invention be used to replace the methods performed by an ITU G.711 Appendix I packet loss concealment algorithm. 
   BACKGROUND OF THE INVENTION 
   In a packet-switched network, a packet of data often traverses several network nodes as it goes across the network in “hops.” Each packet has a header that contains destination address information for the entire packet. Since each packet contains a destination address, they may travel independent of one another and occasionally become delayed or misdirected from the primary data stream. If delayed, the packets may arrive out of order. The packets are not only merely delayed relative to the source, but also have delay jitter. Delay jitter is variability in packet delay, or variation in timing of packets relative to each other due to buffering within nodes in the same routing path, and differing delays and/or numbers of hops in different routing paths. Packets may even be actually lost and never reach their destination. 
   Voice over Packet (VOP) networks and Voice over Internet Protocols (VOIP) are sensitive to delay jitter to an extent qualitatively more important than for text data files for example. Delay jitter is one of the important factors that causes packet loss in a network. Packet loss can produce interruptions, clicks, pops, hisses and blurring of the sound and/or images as perceived by the user, unless the delay jitter problem can be ameliorated or obviated. Packets that are not literally lost, but are substantially delayed when received, may have to be discarded at the destination nonetheless because they have lost their usefulness at the receiving end. Thus, packets that are discarded, as well as those that are literally lost, are all called “lost packets.” Packet loss is a common source of distortion in VOIP. 
   Packet loss causes the degradation of speech quality as perceived by a user. From an end-user&#39;s point of view, the experience of even a single click or pop during a conversation will greatly reduce the user&#39;s satisfaction level with the quality of the entire conversation period. This is true regardless of whether the speech quality is good or excellent most of the time during the call. Customers of telephony services will simply remember the once or twice during a call that degradation was perceived and rate the entire call as poor quality. Thus, from an end-user&#39;s point of view even a single instance of quality degradation has a severely damaging effect on call quality. The user can rarely tolerate as much as half a second (500 milliseconds) of delay. For real-time communication some solution to the problem of packet loss is imperative, and the packet loss problem is exacerbated in heavily-loaded packet networks. Also, even a lightly-loaded packet network with a packet loss ration of 0.1% perhaps, still requires some mechanism to deal with the circumstances of lost packets. 
   Due to packet loss in a packet-switched network employing speech encoders and decoders, a speech decoder may either fail to receive a frame or receive a frame having a significant number of missing bits. In either case, the speech decoder is presented with the same essential problem—the need to synthesize speech despite the loss of compressed speech information. Both “frame erasure” and “packet loss” concern a communication channel or network problem that causes the loss of the transmitted bits. 
   Packet loss concealment (also called frame loss concealment) algorithms hide losses that occur in packet networks by reconstructing the signal from the characteristics of the past signal. These algorithms reduce the click and pops and other artifacts that occur when a network experiences packet loss. PLC improves the overall voice quality in unreliable networks. 
   One standard recommendation to address this problem is the International Telecommunication Union (ITU) G.711 standard “Pulse Code Modulation (PCM) of Voice Frequencies. G.711 Appendix I is an international standard that uses pulse code modulation (PCM) of voice frequencies to transmit packetized voice data over a communications network. Appendix I of G.711 is a standard describing a “high quality low-complexity algorithm for packet loss concealment with G.711.” G.711 describes the PLC algorithms as “frame erasure concealment algorithms,” that “hide transmission losses in an audio system where the input signal is encoded and packetized at a transmitter, sent over a network, and received at a receiver that decodes the packet and plays out the output.” 
     FIG. 1  illustrates a block flow diagram of an implementation of a receiver and decoder that uses features from ITU G.711 Appendix I. The figure shows a receiver  10  that maintains two data buffers that are used by a PLC module  22 , history buffer  24  and pitch buffer  26 . A data stream  12  is normally processed through the voice playout unit  14  in a receiver  10 . If there are no lost packets in packet stream  12 , then the VPU  14  sends its output data stream to voice decoder  16 , which decodes the voice payload from each received packet  12 . After the decoder  16 , decoded voice data is sent through a switch  18  to and through various processes that are understood in the art to produce an audio output at audio port  20 . Whether or not there is packet loss, the VPU  14  output is also saved into history buffer  24  on an ongoing basis. The history buffer  24  has a length of 48.75 ms worth of voice data samples. This length is equivalent to 390 samples for a 8 KHz sample rate. The history buffer  24  is constantly updated from samples from the VPU  14 . 
   Pitch buffer  26  is the same length as the history buffer  24  and is used as a working buffer during a period of packet loss. Pitch buffer  26  is updated from the history buffer  24  at the occurrence of the first packet loss and is maintained for a period of consecutive losses. During the packet loss, the PLC algorithm generates a synthesized signal from the last received pitch period with no attenuation into the pitch buffer  26 , which can then be added to the decoded stream from  16  through switch  18  or other device for playout at audio port  22 . The history buffer is updated through each loss with the synthesized output as the erasure progresses. 
   The G.711 PLC algorithm adds a 3.75 ms delay, which is equivalent to 30 samples at 8 KHz. This delay is used for an Overlap Add (OLA) at the start of an erasure and at the end of the erasure. This allows the algorithm to perform smooth transitions between real and synthetic generated speech, and vice-versa. The synthesized speech from the pitch buffer is continued beyond the end of the erasure and then the generated speech is mixed with the real speech using OLA. The delay is to provide a smooth transition from a good frame to the first reconstructed frame. This avoids clicks in the audio caused by discontinuity between the good frames and the reconstructed frames, output that is unpleasant to the listener. 
   For some applications, however, the aspects of delay, memory consumption, and processing resources (e.g., MIPS) consumption associated with the G.711 Appendix I PLC algorithm are not acceptable. G.711 Appendix I standards can achieve high voice quality but require 3.75 ms of delay and a 48.75 ms history buffer that consumes approximately 1 MIPS per channel. Under the standards of G.711 Appendix I, the packet loss concealment algorithm reduces channel density by up to 30% while actual packet losses in a stable network usually occur less in less than one percent of all data transmissions. Even though a single incident of degradation of quality caused by packet loss can subjectively cause significant problems to the perceived call quality by an end user, a significant amount of MIPS are consumed by the prior art PLC algorithm to address a very low packet loss rate. 
   SUMMARY OF THE INVENTION 
   The present invention improves over the prior art packet loss concealment (PLC) algorithms, such as the ITU G711 Appendix I PLC algorithm that uses the pitch period to reproduce lost packets, by using the spectral analysis filter to determine a maximum repeatable waveform range to reproduce lost packets. The present invention also uses the filter memory to smooth a signal gap, which removes the 3.75 ms delay that is necessary in the G.711 Appendix I PLC algorithm and thereby uses fewer processing resources. The present invention provides similar or better objective and subjective speech quality as the G.711 Appendix I standard. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     For a better understanding of the nature of the present invention, its features and advantages, the subsequent detailed description is presented in connection with accompanying drawings in which: 
       FIG. 1  is an illustration a receiver with a voice playout unit and buffers used by a packet loss concealment algorithm; 
       FIG. 2  is a flowchart of the preferred embodiment of the packet loss concealment method; 
       FIG. 3  is an block diagram of the of a spectral analysis filter; 
       FIG. 4  is a flowchart of determining thresholds for determining peak positions of a residual signal; and 
       FIG. 5  is a flowchart of defining a repeatable waveform period. 
       FIG. 6  is an illustration of an exemplary residual waveform. 
       FIG. 7  is a flow diagram for generation of reconstructed voice samples. 
   

   DETAILED DESCRIPTION OF THE INVENTION 
   The present invention includes a method to reduce the memory and processing resources requirements for a packet loss concealment (PLC) algorithm. The method of the preferred embodiment is applied to an ITU G.711 PLC algorithm and is illustrated by the flowchart in  FIG. 2 . When a receiver  10  determines that a packet from the incoming packet stream is lost  28 , the preferred algorithm analyzes 20 ms of samples that have been saved into the history buffer through a spectral analysis filter  30 . A spectral analysis filter filters samples for parameters of audible speech that produce the inflections of sound encoded in voice data such as impulse and excitations.  FIG. 4  illustrates a block diagram of a spectral analysis filter A(z)  42  that receives input samples  40 . The spectral analysis filter A(z)  42  is a linear predictor with prediction coefficients, a i , that is defined as a system whose output is 
             r   ⁡     (   n   )       =       ∑     i   =   0     n     ⁢       a   i     ⁢     s   ⁡     (     n   -   i     )                 
where r(n) is the sample index of the residual samples in time domain. A filter of an n th  order linear predictor is the polynomial
 
   
     
       
         
           
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   Residual, or prediction error, samples R(z) are obtained from applying the spectral analysis filter to the incoming voice samples using the formula R(z)=A(z)S(z), where S(z) are the voice samples  12  that are used to determine if a bad frame  28  has occurred in the packet flow stream. The output  44  of spectral analysis filter  42  are 20 ms of residual samples r(x)  44  from the filtered input speech samples  40 . The spectral analysis filter  42  calculates spectral analysis coefficients of the input samples  40 . It is these coefficients which will be later fed into an inverse spectral analysis filter that filters a reconstructed residual sample in order to provide a synthesized packet that replaces or “conceals” the packet that was lost. 
   The next step is illustrated in block  32  of  FIG. 2 , which describes a process to calculate a maximum repeatable range T within the 20 ms of residual samples r(x)  44  in the residual waveform. This method is illustrated using the flowchart diagrams in  FIGS. 4 and 5  and an exemplary residual waveform in  FIG. 6 . The method first  46  analyzes each individual samples x(i) of residual r(x) from step  30  to determine the first maximum amplitude and the second maximum amplitude of samples x(i)  48 . The first maximum amplitude is labeled x 1  and the second maximum amplitude is labeled x 2 . Next, in step  48  a ratio α of the two maximum amplitudes are calculated. The formula divides x 2  by x 1  and subtracts 0.1 according to: 
           α   =         x   2       x   1       -   0.1           
The ratio is then used to determine a threshold formula  50  for the amplitude. The threshold th is calculated by finding the product of the ratio α and the first maximum amplitude x 1  according to the equation th=α·x 1 .
 
Once the threshold formula is determined, then in step  52  two thresholds are defined. Referring contemporaneously to  FIG. 6 , the concept of the positive and negative thresholds are defined on an exemplary waveform  64 . The threshold formula in  50  is used in step  52  to define a positive threshold t_p and a negative threshold t_n for the waveform  64 . In step  54 , a positive threshold t_p  66  and a negative threshold t_n  68  are then calculated using the maximum positive amplitude and the minimum negative amplitude of x(i), respectively.
 
   Based on the positive and negative thresholds, the next step  56  is to determine all positions of residual samples whose amplitudes are above the positive threshold t_p  66  and all positions of residual samples whose amplitudes are below negative threshold t_n  68 . After these positions are determined, the next step  58  is to determine a maximum time period duration between consecutive positions of the waveform  64  that are above positive threshold t_p  66 . In  FIG. 6 , the duration between positive amplitudes above positive threshold t_p  66  are shown as T p1  and T p2 . The maximum duration T max, p  from these two durations is calculated from choosing the largest time period out of all durations measured and is shown as:
 
T max, p ={T p1 , T p2 }.
 
   In step  60 , a similar procedure is used to determine a maximum time period duration between consecutive positions of the waveform  64  that are below negative threshold t_n  68 . In  FIG. 6 , the duration between negative amplitudes below negative threshold t_p  66  are shown as T n1 , T n2 , and T n3 . The maximum duration T max, n  from these three durations is calculated from choosing the largest time period out of all durations measured and is shown as:
 
T max, n ={T n1 , T n2 , T n3 }.
 
   Finally, in step  62 , a duration T is determined as the maximum duration of either one of T max, p  and T max, n . The maximum duration is calculated as:
 
T max ={T max, p , T max, n }
 
The result of calculating T max  is the definition of the time period T.
 
   Referring again to  FIG. 2 , once T is known the next step  34  generates frame samples (f size ) by repeating T samples. This step generates a new set of residual samples of 20 ms buffer time denominated r_new(x) made of multiple samples of T samples. 
   In step  36 , the spectral synthesis filter  42  memory r_m (x) is set to r(x) for cases where the filter may require more memory for an expanded r(x). Then, the reconstructed voice sample is generated s_rec(x) using 
             1     A   ⁡     (   z   )         ⁢   72.           FIG. 7  is an exemplary flow diagram illustrating this procedure. In  FIG. 7 , the generated f size  samples (r_new(x)) that were created from repeating T samples are used as input  70  into an synthesis filter
 
             1     A   ⁡     (   z   )         ⁢   72.         
The output  74  of the synthesis filter  72  is reconstructed voice samples  74 . These synthesized signals are then used to replace the lost packet in the voice data stream.
 
   Since the frames are synthesized using the maximum repeatable waveform determination spectral analysis filter memory is used to smooth the signal gap and the recreated frame does not need the overlap and add (OLA) operation specified in G.711 Appendix I to smoothly transition into the real voice signal. Thus, the preferred embodiment does not require a delay, such as the 3.75 ms specified in G.711 Appendix I, for the synthetic signal to transition into the real signal. 
   Referring again to  FIG. 2 , if after packets  12  are received into the VPU  14  there are no bad frames  28 , then the packet reconstruction method of the present invention is bypassed and the VPU moves on to analyze the next frame  38 . 
   The present invention lower MIPS costs for equivalent or better PLC performance. Generally, the higher the order of spectral analysis filter polynomials, the higher the MIPS costs rise to process the voice samples. The preferred embodiment provides for lower-order filter equations that have a lower MIPS cost and do not negatively impact the overall performance of the PLC algorithm. Table 1 below shows PESQ MOS (Perceptual Evaluation of Speech Quality Mean Opinion Scores) results for various I p  polynomial order of filter equations run against different durations of total signal loss in milliseconds. The MOS scores are based upon ITU-T Recommendation P.862, “Perceptual Evaluation of Speech Quality, an Objective Method for End-to-End Speech Quality Assessment of Narrow-Band Telephone Networks and Speech Codecs.” 
   
     
       
             
             
             
             
             
           
             
             
             
             
             
           
         
             
                 
             
             
               I p   
               10 ms 
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               10 
               3.99 
               3.94 
               3.78 
               3.49 
             
             
               4 
               4.02 
               3.94 
               3.76 
               3.46 
             
             
               3 
               3.74 
               3.76 
               3.46 
               3.20 
             
             
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               3.52 
               3.53 
               3.66 
               3.19 
             
             
                 
             
           
        
       
     
   
   The above results show that using a 4th order filter in the present invention will result in nearly the same speech quality as using a 10th order filter. This clearly results in the present invention saving processing resources with lower order filters that result in the same speech quality as much higher order filters. 
   One skilled in the art will appreciate that the present invention can be practiced by other than the described embodiments, which are presented for purposes of illustration and not limitation, and the present invention is limited only by the claims that follow.