Patent Publication Number: US-7584096-B2

Title: Method and apparatus for encoding speech

Description:
FIELD OF INVENTION 
   The present invention relates to speech encoding in a communication system. 
   BACKGROUND TO THE INVENTION 
   Cellular communication networks are commonplace today. Cellular communication networks typically operate in accordance with a given standard or specification. For example, the standard or specification may define the communication protocols and/or parameters that shall be used for a connection. Examples of the different standards and/or specifications include, without limiting to these, GSM (Global System for Mobile communications), GSM/EDGE (Enhanced Data rates for GSM Evolution), AMPS (American Mobile Phone System), WCDMA (Wideband Code Division Multiple Access) or 3 rd  generation (3G) UMTS (Universal Mobile Telecommunications System), IMT 2000 (International Mobile Telecommunications 2000) and so on. 
   In a cellular communication network, voice data is typically captured as an analogue signal, digitised in an analogue to digital (A/D) converter and then encoded before transmission over the wireless air interface between a user equipment, such as a mobile station, and a base station. The purpose of the encoding is to compress the digitised signal and transmit it over the air interface with the minimum amount of data whilst maintaining an acceptable signal quality level. This is particularly important as radio channel capacity over the wireless air interface is limited in a cellular communication network. The sampling and encoding techniques used are often referred to as speech encoding techniques or speech codecs. 
   Often speech can be considered as bandlimited to between approximately 200 Hz and 3400 Hz. The typical sampling rate used by a A/D converter to convert an analogue speech signal into a digital signal is either 8 kHz or 16 kHz. The sampled digital signal is then encoded, usually on a frame by frame basis, resulting in a digital data stream with a bit rate that is determined by the speech codec used for encoding. The higher the bit rate, the more data is encoded, which results in a more accurate representation of the input speech frame. The encoded speech can then be decoded and passed through a digital to analogue (D/A) converter to recreate the original speech signal. 
   An ideal speech codec will encode the speech with as few bits as possible thereby optimising channel capacity, while producing decoded speech that sounds as close to the original speech as possible. In practice there is usually a trade-off between the bit rate of the codec and the quality of the decoded speech. 
   In today&#39;s cellular communication networks, speech encoding can be divided roughly into two categories: variable rate and fixed rate encoding. 
   In variable rate encoding, a source based rate adaptation (SBRA) algorithm is used for classification of active speech. Speech of differing classes are encoded by different speech modes, each operating at a different rate. The speech modes are usually optimised for each speech class. An example of variable rate speech encoding is the enhanced variable rate speech codec (EVRC). 
   In fixed rate speech encoding, voice activity detection (VAD) and discontinuous transmission (DTX) functionality is utilised, which classifies speech into active speech and silence periods. During detected silence periods, transmission is performed less frequently to save power and increase network capacity. For example, in GSM during active speech every speech frame, typically 20 ms in duration, is transmitted, whereas during silence periods, only every eighth speech frame is transmitted. Typically, active speech is encoded at a fixed bit rate and silence periods with a lower bit rate. 
   Multi-rate speech codecs, such as the adaptive multi-rate (AMR) codec and the adaptive multi-rate wideband (AMR-WB) codec were developed to include VAD/DTX functionality and are examples of fixed rate speech encoding. The bit rate of the speech encoding, also known as the codec mode, is based on factors such as the network capacity and radio channel conditions of the air interface. 
   AMR was developed by the 3 rd  Generation Partnership Project (3GPP) for GSM/EDGE and WCDMA communication networks. In addition, it has also been envisaged that AMR will be used in future packet switched networks. AMR is based on Algebraic Code Excited Linear Prediction (ACELP) coding. The AMR and AMR WB codecs consist of 8 and 9 active bit rates respectively and also include VAD/DTX functionality. The sampling rate in the AMR codec is 8 kHz. In the AMR WB codec the sampling rate is 16 kHz. 
   ACELP coding operates using a model of how the signal source is generated, and extracts from the signal the parameters of the model. More specifically, ACELP coding is based on a model of the human vocal system, where the throat and mouth are modelled as a linear filter and speech is generated by a periodic vibration of air exciting the filter. The speech is analysed on a frame by frame basis by the encoder and for each frame a set of parameters representing the modelled speech is generated and output by the encoder. The set of parameters may include excitation parameters and the coefficients for the filter as well as other parameters. The output from a speech encoder is often referred to as a parametric representation of the input speech signal. The set of parameters is then used by a suitably configured decoder to regenerate the input speech signal. 
   Details of the AMR and AMR-WB codecs can be found in the 3GPP TS 26.090 and 3GPP TS 26.190 technical specifications. Further details of the AMR-WB codec and VAD can be found in the 3GPP TS 26.194 technical specification. All the above documents are incorporated herein by reference. 
   Both AMR and AMR-WB codecs are multi rate codecs with independent codec modes or bit rates. In both the AMR and AMR-WB codecs, the mode selection is based on the network capacity and radio channel conditions. However, the codecs may also be operated using a variable rate scheme such as SBRA where the codec mode selection is further based on the speech class. The codec mode can then be selected independently for each analysed speech frame (at 20 ms intervals) and may be dependent on the source signal characteristics, average target bit rate and supported set of codec modes. The network in which the codec is used may also limit the performance of SBRA. For example, in GSM, the codec mode can be changed only once every 40 ms. 
   By using SBRA, the average bit rate may be reduced without any noticeable degradation in the decoded speech quality. The advantage of lower average bit rate is lower transmission power and hence higher overall capacity of the network. 
   Typical SBRA algorithms determine the speech class of the sampled speech signal based on speech characteristics. These speech classes may include low energy, transient, unvoiced and voice sequences. The subsequent speech encoding is dependent on the speech class. Therefore, the accuracy of the speech classification is important as it determines the speech encoding and associated encoding rate. In previously known systems, the speech class is determined before speech encoding begins. 
   However, absolute speech quality degrades as a function of bit rate in a multi-rate speech codec. This is especially true when strong environmental background noise (for example car, street, cafeteria) is present during the call. This makes the operation of source based rate adaptation challenging, because when there is no active speech present (that is the callers are not talking), the codec is only coding background noise and will probably select quite low bit rate modes in order to save system capacity. Users may hear the degradation even if it happens during non-active speech. For this reason, the AMR and AMR-WB codecs may utilise SBRA together with VAD/DTX functionality to lower the bit rate of the transmitted data during silence periods. During periods of normal speech, standard SBRA techniques are used to encode the data. During silence periods, VAD detects the silence and interrupts transmission (DTX) thereby reducing the overall bit rate of the transmission. In this case, background noise parameters are transmitted less often and then averaged in the receiving end to produce “comfort” noise, which sounds quite good. 
   However, not all systems have DTX functionality, and therefore they have to code background noise using the normal speech codec modes. In these systems, when the bit rate decreases to a very low rate, the speech codec starts to produce audible artefacts to the coded background noise, which are perceived as annoying at the receiving end. 
   A paper published in the IEEE Workshop of 1999, authored by Hagen and Ekudden proposes a solution to this problem. In an existing ACELP speech coder, waveform matching LPAS structures are employed which provide high quality for speech signals, but have performance limitations for background noise. According to the paper authored by Hagen and Ekudden, a novel adaptive gain coding technique is used in the ACELP coder in which energy matching is used in combination with the traditional waveform matching criteria to provide high quality for both speech and background noise. The solution offered in that paper however requires a more complex coding to be implemented, which is implemented both across speech and across background noise. 
   It is an aim of the present invention to find a simpler solution to improve background noise. 
   SUMMARY OF THE INVENTION 
   According to one aspect of the present invention there is provided a method of encoding speech in a communications system comprising the steps of: receiving a speech signal including voice signals and background signals; detecting voice activity and providing an indicator when no voice activity is detected; encoding the speech signal to generate a plurality of parameters representing the signal; and when said indicator is not present, outputting a first parametric representation of the speech signal comprising said plurality of parameters, and, when the indicator is present, modifying at least one of the parameters and outputting a second parametric representation of the speech signal including the modified parameter. 
   According to another aspect of the invention there is provided a communications system arranged to encode speech, the system comprising: an input adapted to receive a speech signal including voice signals and background signals; a voice activity detector arranged to detect voice activity and to provide an indicator when no voice activity is detected; an encoder adapted to encode the speech signal to generate a plurality of parameters representing the signal; modifying circuitry operable when the indicator is present to modify at least one of the parameters; and an output at which a first parametric representation of the speech signal is output when the indicator is not present, the first parametric representation comprising said plurality of parameters, and at which a second parametric representation of the speech signal is output when the indicator is present, the second parametric representation including the modified parameter. 

   
     BRIEF DESCRIPTION OF DRAWINGS 
     For a better understanding of the present invention reference will now be made by way of example only to the accompanying drawings, in which: 
       FIG. 1  illustrates a communication network in which embodiments of the present invention can be applied; 
       FIG. 2  illustrates a block diagram of a prior art arrangement; 
       FIG. 3  illustrates a block diagram of an embodiment of the invention; and 
       FIG. 4  illustrates test results. 
   

   DETAILED DESCRIPTION OF EMBODIMENTS 
   The present invention is described herein with reference to particular examples. The invention is not, however, limited to such examples. 
     FIG. 1  illustrates a typical cellular telecommunication network  100  that supports an AMR speech codec. The network  100  comprises various network elements including a mobile station (MS)  101 , a base transceiver station (BTS)  102  and a transcoder (TC)  103 . The MS communicates with the BTS via the uplink radio channel  113  and the downlink radio channel  126 . The BTS and TC communicate with each other via communication links  115  and  124 . The BTS and TC form part of the core network. For a voice call originating from the MS, the MS receives speech signals  110  at a multi-rate speech encoder module  111 . 
   In this example, the speech signals are digital speech signals converted from analogue speech signals by a suitably configured analogue to digital (A/D) converter (not shown). The multi-rate speech encoder module encodes the digital speech signal  110  into a speech encoded signal on a frame by frame basis, where the typical frame duration is 20 ms. The speech encoded signal is then transmitted to a multi-rate channel encoder module  112 . The multi-rate channel encoder module further encodes the speech encoded signal from the multi-rate speech encoder module. The purpose of the multi-rate channel encoder module is to provide coding for error detection and/or error correction purposes. The encoded signal from the multi-rate channel encoder is then transmitted across the uplink radio channel  113  to the BTS. The encoded signal is received at a multi-rate channel decoder module  114 , which performs channel decoding on the received signal. The channel decoded signal is then transmitted across communication link  115  to the TC  103 . In the TC  103 , the channel decoded signal is passed into a multi-rate speech decoder module  116 , which decodes the input signal and outputs a digital speech signal  117  corresponding to the input digital speech signal  110 . 
   A similar sequence of steps to that of a voice call originating from a MS to a TC occurs when a voice call originates from the core network side, such as from the TC via the BTS to the MS. When the voice calls starts from the TC, the speech signal  122  is directed towards a multi-rate speech encoder module  123 , which encodes the digital speech signal  122 . The speech encoded signal is transmitted from the TC to the BTS via communication link  124 . At the BTS, it is received at a multi-rate channel encoder module  125 . The multi-rate channel encoder module  125  further encodes the speech encoded signal from the multi-rate speech encoder module  123  for error detection and/or error correction purposes. The encoded signal from the multi-rate channel encoder module is transmitted across the downlink radio channel  126  to the MS. At the MS, the received signal is fed into a multi-rate channel decoder module  127  and then into a multi-rate speech decoder module  128 , which perform channel decoding and speech decoding respectively. The output signal from the multi-rate speech decoder is a digital speech signal  129  corresponding to the input digital speech signal  122 . 
   Link adaptation may also take place in the MS and BTS. Link adaptation selects the AMR multi-rate speech codec mode according to transmission channel conditions. If the transmission channel conditions are poor, the number of bits used for speech encoding can be decreased (lower bit rate) and the number of bits used for channel encoding can be increased to try and protect the transmitted information. However, if the transmission channel conditions are good, the number of bits used for channel encoding can be decreased and the number of bits used for speech encoding increased to give a better speech quality. 
   The MS may comprise a link adaptation module  130 , which takes data  140  from the downlink radio channel to determine a preferred downlink codec mode for encoding the speech on the downlink channel. The data  140  is fed into a downlink quality measurement module  131  of the link adaptation module  130 , which calculates a quality indicator message for the downlink channel, QI d . QI d  is transmitted from the downlink quality measurement module  131  to a mode request generator module  132  via connection  141 . Based on QI d , the mode request generator module  132  calculates a preferred codec mode for the downlink channel  126 . The preferred codec mode is transmitted in the form of a codec mode request message for the downlink channel MR d  to the multi-rate channel encoder  112  module via connection  142 . The multi-rate channel encoder  112  module transmits MR d  through the uplink radio channel to the BTS. 
   In the BTS, MR d  may be transmitted via the multi-rate channel decoder module  114  to a link adaptation module  133 . Within the link adaptation module in the BTS, the codec mode request message for the downlink channel MR d  is translated into a codec mode request message for the downlink channel MC d . This function may occur in the downlink mode control module  120  of the link adaptation module  133 . The downlink mode control module transmits MC d  via connection  146  to communications link  115  for transmission to the TC. 
   In the TC, MC d  is transmitted to the multi-rate speech encoder module  123  via connection  147 . The multi-rate speech encoder module  123  can then encode the incoming speech  122  with the codec mode defined by MC d . The encoded speech, encoded with the adapted codec mode defined by MC d , is transmitted to the BTS via connection  148  and onto the MS as described above. Furthermore, a codec mode indicator message for the downlink radio channel MI d  is transmitted via connection  149  from the multi-rate speech encoder module  123  to the BTS and onto the MS, where it is used in the decoding of the speech in the multi-rate speech decoder  127  at the MS. 
   A similar sequence of steps to link adaptation for the downlink radio channel may also be utilised for link adaptation of the uplink radio channel. The link adaptation module  133  in the BTS may comprise an uplink quality measurement module  118 , which receives data from the uplink radio channel and determines a quality indicator message, QI u , for the uplink radio channel. QI u  is transmitted from the uplink quality measurement module  118  to the uplink mode control module  119  via connection  150 . The uplink mode control module  119  receives QI u  together with network constraints from the network constraints module  121  and determines a preferred codec mode for the uplink encoding. The preferred codec mode is transmitted from the uplink control module  119  in the form of a codec mode command message for the uplink radio channel MC u  to the multi-rate channel encoder module  125  via connection  151 . The multi-rate channel encoder module  125  transmits MC u  together with the encoded speech signal over the downlink radio channel to the MS. 
   In the MS, MC u  is transmitted to the multi-rate channel decoder module  127  and then to the multi-rate speech encoder  111  via connection  153 , where it is used to determine a codec mode for encoding the input speech signal  110 . As with the speech encoding for the downlink radio channel, the multi-rate speech coder module for the uplink radio channel generates a codec mode indicator message for the uplink radio channel MI u . MI u  is transmitted from the multi-rate speech encoder control module  111  to the multi-rate channel encoder module  112  via connection  154 , which in turn transmits MI u  via the uplink radio channel to the BTS and then to the TC. MI u  is used at the TC in the multi-rate speech decoder module  116  to decode the received encoded speech with a codec mode determined by MI u . 
     FIG. 2  illustrates a block diagram of the multi-rate speech encoder module  111  and  123  of  FIG. 1  in the prior art. The multi-rate speech encoder module  200  may operate according to an AMR-WB codec and comprise a voice activity detection (VAD) module  202 , which is connected to both a source based rate adaptation (SBRA) algorithm module  203  and a discontinuous transmission (DTX) module  205 . The VAD module receives a digital speech signal  201  and determines whether the signal comprises active speech or silence periods. During a silence period, the DTX module is activated and transmission interrupted for the duration of the silence period. During periods of active speech, the speech signal may be transmitted to the SBRA algorithm module. The SBRA algorithm module is controlled by the RDA module  204 . The RDA module defines the used average bit rate in the network and sets the target average bit rate for the SBRA algorithm module. The SBRA algorithm module receives speech signals and determines a speech class for the speech signal based on its speech characteristics. The SBRA algorithm module is connected to a speech encoder  206 , which encodes the speech signal received from the SBRA algorithm module with a codec mode based on the speech class selected by the SBRA algorithm module. The speech encoder operates using Algebraic Code Excited Linear Prediction (ACELP) coding. 
   The codec mode selection may depend on many factors. For example, low energy speech sequences may be classified and coded with a low bit rate codec mode without noticeable degradation in speech quality. On the other hand, during transient sequences, where the signal fluctuates, the speech quality can degrade rapidly if codec modes with lower bit rates are used. Coding of voiced and unvoiced speech sequences may also be dependent on the frequency content of the sequence. For example, a low frequency speech sequence can be coded with a lower bit rate without speech quality degradation, whereas high frequency voice and noise-like, unvoiced sequences may need a higher bit rate representation. 
   The speech encoder  206  in  FIG. 2  comprises a linear prediction coding (LPC) calculation module  207 , a long term prediction (LTP) calculation module  208  and a fixed code book excitation module  209 . The speech signal is processed by the LPC calculation module, LTP calculation module and fixed code book excitation module on a frame by frame basis, where each frame is typically 20 ms long. The output of the speech encoder consists of a set of parameters representing the input speech signal. 
   Specifically, the LPC calculation module  207  determines the LPC filter corresponding to the input speech frame by minimising the residual error of the speech frame. Once the LPC filter has been determined, it can be represented by a set of LPC filter coefficients for the filter. 
   The LPC filter coefficients are quantized by the LPC calculation module before transmission. The main purpose of quantization is to code the LPC filter coefficients with as few bits as possible without introducing additional spectral distortion. Typically, LPC filter coefficients, {a 1 , . . . , a p }, are transformed into a different domain, before quantization. This is done because direct quantization of the LPC filter, specifically an infinite impulse response (IIR) filter, coefficients may cause filter instability. Even slight errors in the IIR filter coefficients can cause significant distortion throughout the spectrum of the speech signal. 
   The LPC calculation module coverts the LPC filter coefficients into the immitance spectral pair (ISP) domain before quantization. However, the ISP domain coefficients may be further converted into the immitance spectral frequency (ISF) domain before quantization. 
   The LTP calculation module  208  calculates an LTP parameter from the LPC residual. The LTP parameter is closely related to the fundamental frequency of the speech signal and is often referred to as a “pitch-lag” parameter, “pitch delay” parameter or “lag”, which describes the periodicity of the speech signal in terms of speech samples. The pitch-delay parameter is calculated by using an adaptive codebook by the LTP calculation module. 
   A further parameter, the LTP gain is also calculated by the LTP calculation module and is closely related to the fundamental periodicity of the speech signal. The LTP gain is an important parameter used to give a natural representation of the speech. Voiced speech segments have especially strong long-term correlation. This correlation is due to the vibrations of the vocal cords, which usually have a pitch period in the range from 2 to 20 ms. 
   The fixed codebook excitation module  209  calculates the excitation signal, which represents the input to the LPC filter. The excitation signal is a set of parameters represented by innovation vectors with a fixed codebook combined with the LTP parameter. In a fixed codebook, algebraic code is used to populate the innovation vectors. The innovation vector contains a small number of nonzero pulses with predefined interlaced sets of potential positions. The excitation signal is sometimes referred to as index to algebraic codebook. 
   The output from the speech encoder  210  in  FIG. 2  is an encoded speech signal represented by the parameters determined by the LPC calculation module, the LTP calculation module and the fixed code book excitation module, which include:
     1. LPC parameters quantised in ISP domain describing the spectral content of the speech signal (spectral parameters);   2. LTP parameters describing the periodic structure of the speech signal (including open-loop lag);   3. ACELP excitation quantisation describing the residual signal after the linear predictors (residual vector);   4. Signal gain.   

   The bit rate of the codec mode used by the speech encoder may affect the parameters determined by the speech encoder. Specifically, the number of bits used to represent each parameter varies according to the bit rate used. The higher the bit rate, the more bits may be used to represent some or all of the parameters, which may result in a more accurate representation of the input speech signal. 
     FIG. 3  illustrates an embodiment of the present invention with a modified speech encoder  206 ′. In addition to the LPC calculation block  207 , LTP calculation block  208  and fixed code book excitation block  209  of the prior art, the modified speech encoder  206 ′ includes a number of respective smoothing blocks which are shown in dotted lines. The smoothing blocks act to modify parameters to have the effect of smoothing background noise in the parameterised signal. Although these are illustrated as separate blocks in the speech encoder, it will be understood that they will be implemented in practice as part of the module to which they belong, by appropriate software, firmware or hardware modifications to that module. Thus, there is a first smoothing module  210  associated with the LPC calculation module  207  which acts to modify the LSP vector for the current frame to generate a modified LSP vector LspNew which is transmitted from the speech encoder as part of the parametrical representation  210  in place of the unmodified LSP vector. 
   In the LTP module both lag (pitch delay) and gain are produced. The first lag is calculated in open loop and then in closed loop around the open loop lag value. The open loop search for the lag gives a rough value, which is refined by the closed loop calculation. The LTP gain is related to the LTP lag (pitch) value. The gain and lag parameters are denoted generally as lag parameters in  FIG. 3 . 
   A second smoothing module  211  is associated with the LTP calculation module  208  for the purpose of modifying the open-loop lag value to generate a modified gain parameter for transmission as part of the parametrical representation. A third smoothing module  212  is associated with the fixed code book excitation module  209  for the purpose of generating a modified residual vector NewRes for transmission as part of the parametrical representation  210 . 
   The Vad module  202  which detects voice activity includes a flag  202   a  which indicates whether or not there is voice activity. If the Vad flag is set to zero, this indicates that there is no voice activity and this causes the smoothing modules  210 ,  211  and  212  to become active. With the Vad flag set to one, i.e. when speech activity is detected, the smoothing modules  210 ,  211  and  212  do not operate, and the parametrical representation  210  is transmitted with the original parameters from the modules  207 ,  208  and  209  without smoothing or modification. 
   As illustrated in  FIG. 3 , the first smoothing module  210  is associated with a counter  213  which is named VadOfCountLspBuff in the following description. Similarly, the third smoothing module  212  is associated with a counter  214  which is labelled LspNoiseFact in the following description. 
   A description of the operation of each of the smoothing modules  210 ,  211  and  212  is given below. 
   Spectral Parameters Modification (LSP—Module  210 )
         VadOffCountLspBuf is the counter  213 , which is set to −1, when VAD flag is set to zero. Otherwise the counter is updated as follows, based on a count of incoming frames.       

   
     
       
         
           VadOffCountLspBuf 
           = 
           
             { 
             
               
                 
                   
                     VadOffCountLspBuf 
                     &lt; 
                     5 
                   
                 
                 
                   
                     VadOffCountLspBuf 
                     ++ 
                   
                 
               
               
                 
                   
                     VadOffCountLspBuf 
                     ≥ 
                     5 
                   
                 
                 
                   
                     VadOffCountLspBuf 
                     = 
                     5 
                   
                 
               
             
           
         
       
     
       
       
         
           If VAD flag is set to zero and VadOffCountLspBuf counter is greater than zero, the following modification is done for LSP vector LSP of the current frame.
 
LspTemp=average(LspBuf(1) . . . LspBuf(VadOffCountLspBuf))
 
         
       
     
  
   
     
       
         
           
             
               
                 LspNew 
                 = 
                   
                 ⁢ 
                 
                   
                     Lsp 
                     
                       VadOffCountLspBuf 
                       + 
                       1 
                     
                   
                   + 
                 
               
             
           
           
             
               
                   
                 ⁢ 
                 
                   
                     LspTemp 
                     * 
                     VadOffCountLspBuf 
                   
                   
                     VadOffCountLspBuf 
                     + 
                     1 
                   
                 
               
             
           
         
       
     
       
       
         
           LspBuf is a buffer  215  including LSP vectors of last 5 frames. LspBuf is updated only when VAD flag is set to zero. LspBuf(1) is the LPC vector of last frame, LspBuf(2) is the LPC vector of second last frame, etc. LspTemp is the average of last frames depending on the count, VadOffCountLspBuf. LspNew is the average of current and past frames also depending on VadOffCountLspBuf and represents the smoothed vector which is transmitted as part of the parametrical representation  210 . 
         
       
     
  
   Open-Loop LTP Lag Modification (Module  211 )
         If VAD flag is set to zero, the open-loop LTP lag parameter is randomised. Randomised open-loop LTP lag can get values from 20 to 120 (samples in time domain).
 
LP Residual Modification (Res—Module  212 )
   Res(0) is the residual vector of the current frame. Modified residual vector of the current frame, NewRes(0), is calculated as follows:
 
New Res (0)= C *((1−Coef)* Res (0)+Coef* Res Max(0)*Rand Res )
   where RandRes is random vector including values between {−1 . . . 1}. ResMax(0) is the maximum absolute value of the current residual vector Res(0).   Coef is the noise contribution for the residual vector and it is increased in steps after VAD flag is set to zero as follows:
 
Coef= lsp NoiseFact*0.0625
   where lspNoiseFact is the counter  214 . The counter is set to 0, when voice activity detection flag is set to zero. Otherwise it is updated as follows, based on a count of incoming frames.       

   
     
       
         
           lspNoiseFact 
           = 
           
             { 
             
               
                 
                   
                     lspNoiseFact 
                     &lt; 
                     8 
                   
                 
                 
                   
                     lspNoiseFact 
                     ++ 
                   
                 
               
               
                 
                   
                     lspNoiseFact 
                     ≥ 
                     8 
                   
                 
                 
                   
                     lspNoiseFact 
                     = 
                     8. 
                   
                 
               
             
           
         
       
     
       
       
         
           Therefore Coef value will be 0.5 after 8 frames and then noise contribution will be 50% of the LP residual. C is the scaling factor which is calculated as follows: 
         
       
     
  
   
     
       
         
           C 
           = 
           
             
               
                 ResEnergyEst 
                 ⁡ 
                 
                   ( 
                   0 
                   ) 
                 
               
               NewResEnergy 
             
           
         
       
     
       
       
         
           where NewResEnergy is the energy of the modified residual vector. ResEnergyEst(0) is the residual energy estimate of the current frame and it is calculated as follows: 
         
       
     
  
   
     
       
         
           
             ResEnergyEst 
             ⁡ 
             
               ( 
               0 
               ) 
             
           
           = 
           
             { 
             
               
                 
                   
                     
                       
                         0.9 
                         * 
                         
                           ResEnergyEst 
                           ⁡ 
                           
                             ( 
                             
                               - 
                               1 
                             
                             ) 
                           
                         
                       
                       + 
                       
                         0.1 
                         * 
                         
                           ResEnergy 
                           ⁡ 
                           
                             ( 
                             0 
                             ) 
                           
                         
                       
                     
                     , 
                   
                 
                 
                   
                     
                       when 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       VAD 
                     
                     = 
                     0 
                   
                 
               
               
                 
                   
                     
                       
                         0.66 
                         * 
                         
                           ResEnergyEst 
                           ⁡ 
                           
                             ( 
                             
                               - 
                               1 
                             
                             ) 
                           
                         
                       
                       + 
                       
                         0.33 
                         * 
                         
                           ResEnergy 
                           ⁡ 
                           
                             ( 
                             0 
                             ) 
                           
                         
                       
                     
                     , 
                   
                 
                 
                   
                     
                       when 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       VAD 
                     
                     = 
                     1 
                   
                 
               
             
           
         
       
     
       
       
         
           where ResEnergyEst(−1) is the residual energy estimate of the last frame and ResEnergy(0) is the energy of residual vector Res(0) of the current frame. 
         
       
     
  
   A listening test was conducted with two experiments: car noise test with SNR 10 db and street noise test with SNR 20 db. As can be seen from  FIG. 4 , in both experiments the implementation of the smoothing function increased the overall speech quality. In fact, it was determined that by using the smoothing functions at 4.75 kbps, the speech quality could be improved to the level of AMR 12.2 kbps. 
   In the above-described embodiment the randomised open loop LTP lag value is used to generate the modified gain parameter output as part of the second parametric representation of the speech signal. It will be appreciated however that that gain parameter itself could be modified by randomisation or in some other way.