Patent Publication Number: US-8971522-B2

Title: Noise reduction

Description:
RELATED APPLICATION 
     This application claims priority under 35 USC 119 or 365 to Great Britain Application No. 1308247.4 filed May 8, 2013, the disclosure of which is incorporate in its entirety. 
     BACKGROUND 
     Communication systems allow users to communicate with each other over a network. The network may be, for example, the Internet or public switched telephone network (PSTN). Audio signals can be transmitted between nodes of the network, to thereby allow users to transmit and receive audio data (such as speech data) to each other in a communication session over the communication system. 
     A user device may have audio input means such as a microphone that can be used to receive audio signals such as speech from a user. The user may enter into a communication session with another user, such as a private call (with just two users in the call) or a conference call (with more than two users in the call). The user&#39;s speech is received at the microphone, processed and is then transmitted over a network to the other users in the call. The user device may also have audio output means such as speakers for outputting audio signals to nearend user that are received over the network from a farend user during a call. Such speakers can also be used to output audio signals from other applications which are executed at the user device, and which can be picked up by the microphone as unwanted audio signals which would disturb the speech signals from the nearend user. 
     As well as the audio signals from the user, the microphone may also receive other audio signals, such as background noise, which are unwanted and which may disturb the audio signals received from the user. The background noise can contribute to disturbance to the audio signal received at the microphone from the nearend user for transmission in the call to a farend user. Another difficulty that can arise in an acoustic system is “howling”. Howling is an unwanted effect which arises from acoustic feedback in the system. It can be caused by a number of factors and arises when system gain is high. 
     SUMMARY 
     This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. 
     There is provided a method of reducing noise in an acoustic system comprising a first user terminal and at least one further user terminal. The first user terminal receives an audio signal from the at least one further user terminal over a communications network. The first user terminal comprises a processing unit on which is executed a communication client application. The communication client application is configured so as when executed on the processing unit to supply the audio signal to an audio signal processing module of the first user terminal, wherein the audio signal processing module processes the audio signal, whereby a level of gain is applied to the audio signal, and outputs a processed audio signal to audio output means of the first user terminal. The communication client application is configured so as when executed on the processing unit to estimate a noise level of the audio signal and the processed audio signal and estimate the gain applied by the audio signal processing module based on a ratio of the noise level estimates. The communication client application is also configured so as when executed on the processing unit to selectively apply a system gain reduction step to at least one of the audio signal and a near-end audio signal received via audio input means of the first user terminal, based on at least the estimated gain applied by the audio signal processing module. 
     The method may be used in a call (e.g. a call implementing voice over internet protocol (VoIP) to transmit audio data between user devices) in which case the audio signal may be a far-end signal received from the far-end of the call, and the received signal includes the resulting echo and a near-end signal for transmission to the far-end of the call. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       For a better understanding of the described embodiments and to show how the same may be put into effect, reference will now be made, by way of example, to the following drawings in which: 
         FIG. 1   a  shows a schematic illustration of a communication system; 
         FIG. 1   b  is a schematic function diagram of a gain estimation technique; 
         FIG. 2  is a schematic block diagram of a user device; 
         FIG. 3  is a schematic function diagram of a gain estimation technique; and 
         FIG. 4  is a flow chart for a process of selectively applying system gain reduction. 
     
    
    
     DETAILED DESCRIPTION 
     Embodiments will now be described by way of example only. 
       FIG. 1   a  shows a communication system  100  comprising a first user  102  (“User A”) who is associated with a first user device  104  and a second user  108  (“User B”) who is associated with a second user device  110 . In other embodiments the communication system  100  may comprise any number of users and associated user devices. The user devices  104  and  110  can communicate over the network  106  in the communication system  100 , thereby allowing the users  102  and  108  to communicate with each other over the network  106 . The communication system  100  shown in  FIG. 1  is a packet-based communication system, but other types of communication system could be used. The network  106  may, for example, be the Internet. Each of the user devices  104  and  110  may be, for example, a mobile phone, a tablet, a laptop, a personal computer (“PC”) (including, for example, Windows™, Mac OS™ and Linux™ PCs), a gaming device, a television, a personal digital assistant (“PDA”) or other embedded device able to connect to the network  106 . The user device  104  is arranged to receive information from and output information to the user  108  of the user device  110 . The user device  104  comprises output means such as a display and speakers. The user device  104  also comprises input means such as a keypad, a touch-screen, a microphone for receiving audio signals and/or a camera for capturing images of a video signal. The user device  104  is connected to the network  106 . 
     The user device  104  executes an instance of a communication client, provided by a software provider associated with the communication system  100 . The communication client is a software program executed on a local processor in the user device  104 . The client performs the processing required at the user device  104  in order for the user device  104  to transmit and receive data over the communication system  100 . 
     The user device  110  corresponds to the user device  104  and executes, on a local processor, a communication client which corresponds to the communication client executed at the user device  104 . The client at the user device  110  performs the processing required to allow the user  108  to communicate over the network  106  in the same way that the client at the user device  104  performs the processing required to allow the user  102  to communicate over the network  106 . The user devices  104  and  110  are endpoints in the communication system  100 .  FIG. 1  shows only two users ( 102  and  108 ) and two user devices ( 104  and  110 ) for clarity, but many more users and user devices may be included in the communication system  100 , and may communicate over the communication system  100  using respective communication clients executed on the respective user devices. 
     Both the first user device  104  and a second user device  110  may perform acoustic echo cancellation. There are two main ways to achieve acoustic echo cancellation, one being echo subtraction and the other being echo suppression. Often these two approaches are combined. 
     One of the challenges in echo cancellation systems is to reduce howling. Howling is a symptom of having feedback with a system gain higher than 1 somewhere in the frequency spectrum. By reducing the system gain at this frequency, the howling will stop. A typical scenario where the risk of howling is high is during a call between hands-free devices. Under such a scenario, the system gain (the sum of all the gains in the closed-loop communication setup) can be higher than unity and therefore a signal that is being passed through the echo cancellers may circulate the system and at each loop be amplified. 
     The howling problem is more relevant for echo cancellation systems based on suppression than for echo cancellation systems based on subtraction. Even so, if an echo cancellation system based on subtraction does not manage to remove all the echo it can also suffer from howling. 
     The audio signal captured by the microphone of the first user device  104  is transmitted over the network  106  for playing out by the second user device  110 . The microphone of the second user device  110  captures an echo of the audio signal that was transmitted by the first user device  104 , if that echo is not fully cancelled, then the second user device  110  transmits it back to the first user device  104 . That received signal is played-out through the speakers of the first user device  104  and, an echo is captured by the microphone of the first user device  104 . If the echo canceller in the first user device  104  is not able to completely remove that echo, the echo signal is transmitted again to the second user device  110 . If during that loop, any frequency content of the original audio signal has suffered a gain higher than one, a howling condition will occur. The term system gain used herein refers to the gain that is applied to an audio signal during this loop i.e. the combination of the gain at first user device  104  and the gain at the second user device  110 . 
     Devices typically have a dedicated audio signal processing module (such as a sound card) in addition to a local processor on the device. This audio signal processing module performs audio processing functions for the user device such as analogue to digital conversion (ADC) of audio signals captured at a microphone and digital to analogue conversion (DAC) of audio signals for playing out of a speaker. To use the audio signal processing module an operating system (OS) executed on the local processor on the device typically requires specific software. For example, to use a sound card, an OS typically requires a specific sound card driver (a software program that handles the data connections between the physical hardware of the sound card and the operating system). 
     It is common that this software (i.e. sound card drivers) introduce effects on the play out signal (i.e. the signal to be output from a speaker) in order to maximize the user experience (e.g. loudness enhancement effects included in the drivers). Those effects are achieved by signal processing modules on the audio signal processing module the functionality of which is unknown to the applications (i.e. a communication client) executed on a local processor on the device that use the play out system available in the OS. However, some operating systems include functionality for feeding back the signal that is going to be played out, to the application executed on the local processor. Examples of operating systems including this functionality are Microsoft&#39;s Windows 7, 8, XP and Vista Windows Phone 8 operating systems. This signal that is fed back to the application executed on the local processor is referred to herein after as a “loopback signal”. 
     The use of such a dedicated audio signal processing module in combination with an echo cancellation system introduces certain problems. Specifically, the dedicated audio signal processing module changes the gain that is applied to an audio signal that is output by an application executed on the local processor before it is played out at a speaker. This change in gain is unknown to the application executed on the local processor and thus may affect the system gain and increase the risk that the echo canceller enters into a howling condition. 
     Reference is now made to  FIG. 1   b  shows a simplified scheme of a user device in a communication system where an audio signal is processed by dedicated audio signal processing hardware before it is played out at a speaker signal. 
     In order to avoid howling, the system gains in the closed-loop communication setup needs to be tracked and kept below one. In order to do that, a user device estimates the gain that is introduced by signal processing functionality implemented at the user device on a local processor. The signal processing functionality implemented by executing a communication client on the local processor of a device is shown contained in the dashed box in  FIG. 1   b . As shown in  FIG. 1   b , signal processing functionality implemented by executing a communication client on the local processor of a device may include digital gain control, echo suppression and noise reduction. Each signal processing component introduces gain which contributes to the total system gain. The gain introduced by each signal processing component is represented by φ and used for system gain estimation. The system gain estimation also takes into account echo path gains modelled using the received audio signal y(t) and a reference signal. 
     To model the echo path gains and estimate the echo captured by a microphone, a reference signal is needed. With reference to  FIG. 1   b  (where the OS includes functionality for feeding back the signal that is going to be played out, to a communication client executed on the user device) it can be seen that two possible signals can be considered as reference signals. 
     The first signal that can be considered a reference signal is the signal labelled as “far-end signal”. This signal represents the audio signal that a communication client sends for playing out from a speaker. Using the far-end signal as a reference has the advantage that any processing performed by the audio signal processing module is taken into account when the echo path is estimated. However, as the processing that is implemented by the audio signal processing module is often highly nonlinear and signal dependent it is extremely difficult to get good estimates for the echo paths that are valid. 
     The second signal that can be considered a reference signal is the signal labelled as “loopback signal”. As described above, this is the signal that the OS feedbacks to the communication client and that has been affected by the processing that the audio signal processing module applies to the signal before playing it out from a speaker. Using the loopback signal as the reference signal avoids the problem of forcing the echo path estimation to attempt estimating the processing done by the audio signal processing module. The drawback is however, that the signal has often been modified in a nonlinear manner such that low-level (i.e. low amplitude) signals are boosted more than high-level (i.e. high amplitude) signals, making it extremely difficult to use this signal for estimating the system gain. 
     In accordance with methods described herein the gain introduced by the audio signal processing module is estimated by using the noise levels of the far-end signal before and after processing. This information is used by the echo cancellation system for ensuring that the system gain is below one, and therefore reduce the risk of howling. 
     By estimating the gain applied by the audio signal processing module for at least one frequency, a system gain reduction step may be selectively applied by the communication client at that frequency. 
     Although it is possible to obtain a reduction in howling by attenuating only one frequency which is likely to predispose the acoustic system to howling, it is particularly advantageous if a respective local gain or system gain of the acoustic system is calculated for each of a plurality of frequencies in the received signal. This is because a howling effect will be introduced into the acoustic system if any frequency component of an audio signal in the closed-loop communication setup has a system gain exceeding one. 
     In embodiments described herein, the gain applied by the audio signal processing module is estimated for each of a plurality of frequencies, and a system gain reduction step may be selectively applied by the communication client at each of the plurality of frequencies. Thus howling is avoided by ensuring the system gains for all frequency components of an audio signal in the closed-loop communication setup are tracked and kept below one. 
       FIG. 2  illustrates a detailed view of the user device  104  on which is executed a communication client instance  206  for communicating over the communication system  100 . The user device  104  comprises a central processing unit (“CPU”) or “processing module”  202 , to which is connected: output devices such as a display  208 , which may be implemented as a touch-screen, and a speaker (or “loudspeaker”)  210  for outputting audio signals; input devices such as a microphone  212  for receiving audio signals, a camera  216  for receiving image data, and a keypad  218 ; a memory  214  for storing data; and a network interface  220  such as a modem for communication with the network  106 . The user device  104  may comprise other elements than those shown in  FIG. 2 . The display  208 , speaker  210 , microphone  212 , memory  214 , camera  216 , keypad  218  and network interface  220  may be integrated into the user device  104  as shown in  FIG. 2 . In alternative user devices one or more of the display  208 , speaker  210 , microphone  212 , memory  214 , camera  216 , keypad  218  and network interface  220  may not be integrated into the user device  104  and may be connected to the CPU  202  via respective interfaces. One example of such an interface is a USB interface. If the connection of the user device  104  to the network  106  via the network interface  220  is a wireless connection then the network interface  220  may include an antenna for wirelessly transmitting signals to the network  106  and wirelessly receiving signals from the network  106 . 
       FIG. 2  also illustrates an operating system (“OS”)  204  executed on the CPU  202 . Running on top of the OS  204  is the software of the client instance  206  of the communication system  100 . The operating system  204  manages the hardware resources of the computer and handles data being transmitted to and from the network  106  via the network interface  220 . The client  206  communicates with the operating system  204  and manages the connections over the communication system. The client  206  has a client user interface which is used to present information to the user  102  and to receive information from the user  102 . In this way, the client  206  performs the processing required to allow the user  102  to communicate over the communication system  100 . 
     With reference to  FIGS. 3 and 4  there is now described a method of selectively applying system gain reduction.  FIG. 3  is a functional diagram of a part of the user device  104  showing how a system gain reduction process is implemented. 
     As shown in  FIG. 3 , the user device  104  comprises the speaker  210 , the microphone  212 , and a signal processing module  300 . The signal processing module  300  (shown as the dashed box in  FIG. 3 ) represents the signal processing functionality implemented by executing communication client application  206  on the CPU  202  of device  104 . The signal processing module  300  may comprise digital gain modules module  302 / 312 , a modelling module  304  comprising a filter module, a noise level estimation module  306 , a noise reduction module  308 , an echo suppression module  310  and a system gain estimation module  314 . The signal processing functionality implemented by executing communication client application  206  may include more, or less functionality, than that shown in  FIG. 3 . The user device  104  further comprises an audio signal processing module  209 . 
       FIG. 4  is a flow chart for the process of selectively applying system gain reduction. 
     A signal to be output from the speaker  210  is coupled to an input of the digital gain module  302 . An output of the digital gain module  302  (denoted “far-end signal”) is coupled to an input of the audio signal processing module  209 . An output of the audio signal processing module  209  is coupled to the speaker  210 . It should be noted that in the embodiments described herein there is just one speaker (indicated by reference numeral  210  in the figures) but in other embodiments there may be more than one speaker to which the signal to be outputted is coupled (for outputting therefrom). Similarly, in the embodiments described herein there is just one microphone (indicated by reference numeral  212  in the figures) but in other embodiments there may be more than one microphone which receives audio signals from the surrounding environment. The output of the audio signal processing module  209  is also coupled to a first input of the modelling module  304  and to a first input of the noise level estimation module  306 . The output of the digital gain module  302  is coupled to a second input of the noise level estimation module  306 . An output of the microphone  212  is coupled to the signal processing module  300 . In particular, the output of the microphone  212  is coupled to an input of the noise reduction module  308 . The output of the microphone  212  is also coupled to a second input of the modelling module  304 . An output of the modelling module  304  is coupled to a first input of the system gain estimation module  314 . An output of the noise level estimation module  306  is coupled to a second input of the system gain estimation module  314 . An output of the modelling module  304  is coupled to a first input of the echo suppression module  310 . An output of the noise reduction module  308  is coupled to a second input of the echo suppression module  310 . An output of the echo suppression module  310  is coupled to an input of the gain control module  312 . An output of the gain control module  312  is used to provide the received signal (with echo cancellation having been applied) for further processing in the user device  104 . 
     In step S 402  a signal is received which is to be outputted from the speaker  210 . For example, the signal to be outputted may be a far-end signal that has been received at the user device  104  at network interface  220  from the user device  110  during a call between the users  102  and  108  over the communication system  100 . In other embodiments, the signal to be outputted may be received from somewhere other than over the communication system  100  in a call. For example, the signal to be outputted may have been stored in the memory  214  and step S 402  may comprise retrieving the signal from the memory  214 . 
     Digital gain module  302  may apply a level of gain to the far-end signal before the far-end signal is supplied to audio signal processing module  209 . 
     In step S 404 , the far-end signal is processed by the audio signal processing module  209 . That is, the audio signal processing module  209  performs digital to analogue conversion (DAC) of the far-end signal and processes the far-end signal in accordance with effects introduced by software executed on CPU  204  before outputting the processed audio signal to speaker  210 . The processing that is applied by the audio signal processing module  209  may be time variant and may be different for speech regions to noisy regions of the far-end signal. The processing that is implemented by the audio signal processing module  209  may include compression whereby different gains are applied to the far-end signal depending on the input level of the far-end signal. 
     In step S 406  the audio signal that has been processed by the audio signal processing module  209  is outputted from the speaker  210 . In this way the audio signal that has been processed by the audio signal processing module  209  is outputted to the user  102 . 
     In step S 408  the microphone  212  receives an audio signal. As shown in  FIG. 3  the received audio signal may include a near-end signal which is a desired signal or “primary signal”. The near-end signal is the signal that the user  102  intends the microphone  212  to receive. However, the received audio signal also includes an echo signal resulting from the audio signals outputted from the speaker  210  in step S 406 . The received audio signal may also include noise, such as background noise. Therefore, the total received audio signal y(t) can be given by the sum of the near-end signal, the echo and the noise. The echo and the noise act as interference for the near-end signal. Although not shown in  FIG. 3 , analogue to digital (ADC) conversion is applied to the signal captured by the microphone  212  to arrive at the digital signal y(t). 
     The modelling module  304  takes as inputs the outputted audio signal (denoted “loopback signal”) and the received audio signal y(t). In step S 410 , the modelling module  304  is used to model the echo path of the echo in the received audio signal y(t). 
     The echo path describes the effects of the acoustic paths travelled by the audio signals output from the speaker  210  to the microphone  212 . The audio signal may travel directly from the speaker  210  to the microphone  212 , or it may be reflected from various surfaces in the environment of the nearend terminal. The echo path traversed by the audio signal output from the speaker  210  may be regarded as a system having a frequency and a phase response which may vary over time. 
     In order to remove the acoustic echo s(t) from the signal y(t) recorded at the near-end microphone  212  it is necessary to estimate how the echo path changes the desired far-end speaker output signal to an undesired echo component in the input signal. 
     The echo path h(t) describes how the echo in the received audio signal y(t) relates to the loopback signal x(t) output from the speaker  201 , e.g. for a linear echo path represented by the impulse response h(t) or its counterpart in the frequency domain H(ω), the following equation describes the relation between the echo and the loopback signal: S(ω)=H(ω)X(ω) where S(ω) refers to the frequency response of the echo signal, s(t), and X(ω) refers to the frequency response of the loopback signal, x(t). The echo path might also vary over time and, therefore, different frequency responses, H(ω), can be found at different time instances. The echo path h(t), or its counterpart H(ω), may depend upon (i) the current environmental conditions surrounding the speaker  210  and the microphone  212  (e.g. whether there are any physical obstructions to the passage of the audio signal from the speaker  210  to the microphone  212 , the air pressure, temperature, wind, etc), (ii) characteristics of the speaker  210  and/or the microphone  212  which may alter the signal as it is outputted and/or received, and (iii) any other process of the signal that might not be reflected in the loopback signal, e.g., buffer delays. 
     The filter module  304  models the echo path h(t) of the echo path in the received audio signal y(t). This is typically done by either making an estimation of the filter in the time domain or in the frequency domain. Using that estimate and the current loopback signal, it is possible to estimate the parameters that will be used by the echo canceller. Those parameters could be, for example, the suppression gains that are applied to the near-end spectrum in order to remove the echo (echo cancellers based on suppression) or the filter parameters that produce the echo estimate that needs to be subtracted from the near-end signal in order to remove the echo (echo cancellers based on subtraction). The current embodiment is specially tailored for echo canceller based on suppression, however, it is also possible to use it in echo cancellers based on subtraction given that the frequency gain introduced by the echo subtractor can be estimated. 
     In either case, echo cancellers based on suppression, subtraction or an hybrid version of both, the filter parameters that are modelled by the filter module  304  are better trained when the echo is the dominant part of the received audio signal, that is when y(t)≅s(t). 
     Estimation of the echo path is done during far-end activity, the far-end activity is detected by a Voice Activity Detector (VAD) (a component of the signal processing module  300  not shown in  FIG. 3 ) which detects speech like qualities in the far-end signal. The estimation of the echo path is therefore mainly based on high energy signals as these are the signals that trigger the VAD. Typically, the VAD maintains a threshold, and the high energy signals are those with energy above the threshold amount above the background noise i.e. the threshold that determines whether the current frame has enough energy to trigger the VAD depends on the background noise present in the far-end signal. For the sake of using known terminology, we refer as VAD to the module that detects activity. However, it should be noted that this module is not limited to detect speech signals but any signal whose expected echo would be annoying if it passes through the echo canceller. As pointed out above, that module is often based on detecting signals with a higher energy than the background noise. The system gain estimation module  314  is arranged to receive the estimated echo path from the modelling module  304 . 
     By identifying the gain introduced by the audio signal processing module  209  it is possible for the echo cancellation system to ensure that the system gain is below one, and therefore reducing the risk of howling. This process is now described. 
     As the signal processing that is applied to the far-end signal in the audio signal processing module  209  is usually time variant and level dependent, it is important to select the appropriate type of signals for estimating the contribution of the audio signal processing module  209  to the system gain. For howling reduction, it is the gain applied over low energy signals that are the most relevant as these are the signals that are typically amplified by the systems that suffer from howling. By low energy signals, we refer to the signals with an energy comparable to the background noise present in the far-end signal. Because the low energy signals have an energy comparable to the background noise level in the far-end signal, the VAD at the far-end is not triggered (the low energy signals are not detected as speech) and the echo suppressor is inactive during those regions. 
     The noise level estimation module  306  receives the far-end signal and the loopback signal as inputs. In step S 412  the noise level estimation module  306  determines a noise level estimate (NL Farend (f)) of the far-end signal (i.e. prior to signal processing by the external signalling processing module  209 ). In step S 414  the noise level estimation module  306  determines a noise level estimate (NL Loopback (f)) of the loopback signal (i.e. after the signal processing by the external signalling processing module  209 ). Possible techniques implemented by noise level estimation module  306  to determine noise level estimates NL Farend (f) and NL Loopback (f) are well known to persons skilled in the art and are therefore not discussed in detail herein. 
     In step S 416  the noise level estimation module  306  estimates the loopback gain, LG(f), which is an estimate of the gain introduced by the audio signal processing module  209  taking into account the noise level estimates NL Farend (f) and NL Loopback (f). For example the noise level estimation module  306  may determine a ratio between the noise level estimates NL Farend (f) and NL Loopback (f) in order to estimate a value for the loopback gain, LG(f). That is: 
     
       
         
           
             
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     Thus, the estimation of the gain introduced by the audio signal processing module  209  is based on the ratio between the noise level estimates of the loopback signal and of the audio signal that the communication client sends for playing out at speaker  210 . 
     Signal processing may be performed on a per frame basis. Frames can, for example, be between 5 and 20 milliseconds in length and be divided into spectral frequency bins, for example, between 64 and 256 bins per frame. Each bin contains information about a signal component at a certain frequency, or in a certain frequency band. Ideally, for speech, each frame of the far-end signal is processed in real time and the gain introduced by the audio signal processing module for each frequency bin is estimated to control the level of gain applied by the signal processing functionality for that frequency bin implemented by executing a communication client application 
     A noise estimator typically estimates the noise from the periods of silence on the speech signal and, therefore, the noise level estimate NL Farend (f) represents the portions of the far-end signal that has lowest amplitude values which will have a high gain introduced by any compressor functionality in the audio signal processing module  209 , and the noise level estimate NL Loopback (f) represents the portions of the loopback signal that have the lowest amplitude values and thus have had a high gain applied to them in any compressor functionality in the audio signal processing module  209 . 
     In particular, the estimation of the loopback gain applied by the audio signal processing module  209  is implemented using portions of the far-end audio signal which have an energy that does not trigger the VAD i.e. that have an energy that does not exceed a threshold amount above the estimated noise level of the audio signal. 
     By identifying the gain introduced by the audio signal processing module  209  based on the ratio of these noise levels, the system gain, which can be used for controlling the howling reduction, may be tracked even during regions with no active far-end. Furthermore the audio signal processing module  209  may have a gain that is dependent on the signal level, by tracking the noise levels ratio, it is possible to estimate the gain that is applied to the low level signals, which is the gain that is more relevant for preventing howling conditions. 
     The noise level of the far-end signal is typically also used by echo suppression based echo cancellers in the VAD module in order to determine whether they should cancel the echo, or let through the noisy echo (cancelling all echoes consisting only of noise typically causes excessive fading). Hence it is of particular importance that the system gain, and in this case particularly the loopback gain, is correctly estimated for low level signals, as this noisy echo will typically by echo canceller design never be cancelled by the echo canceller. 
     Even though the noise level based loopback gain estimate is not a good estimate of the maximum loopback gain, it is nevertheless sufficient for ensuring that the system gain is correctly estimated for the noise, which in turn ensures that the noise does not result in howling. Should the actual gain applied by audio signal processing module  209  be higher for lower level audio signals, this is acceptable since the noise in these lower level audio signals will occur rarely as, otherwise, the noise estimator would change its estimate toward those low levels. 
     Furthermore, should the gain be higher for higher level audio signals this is also acceptable since the howling buildup for these signals levels will be handled by the echo suppressor  310 . That is, high input level audio signals will be suppressed by echo suppressor  310 , therefore the high input level audio signals will not be able to trigger howling. However, the echo suppressor  310  will not perform echo suppression on the low level input signals if they are not detected as speech and, therefore, it is this kind of signals that are more likely to introduce howling. 
     The noise level estimation module  306  may perform noise level estimation needed by other modules in the signal processing module  300 , for example, in the VAD referred to above. Therefore the embodiments described herein have a low computational cost. Furthermore the levels of stationary noise are typically fairly straightforward and robust to estimate and thus the embodiments described herein are also robust. 
     The system gain estimation module  314  is arranged to receive the estimated value for the loopback gain LG(f), from the noise level estimation module  306 . 
     In step S 418  the system gain estimation module  314  is arranged to control the level of gain applied in the signal processing functionality implemented by executing communication client application  206 . 
     In particular, the system gain estimation module  314  may be arranged to estimate the total gain introduced at the user device  104  side of the closed-loop communication setup. That is, the system gain estimation module  314  is arranged to the estimate the total gain introduced at the user device  104  based on the estimated echo path gains received from the modelling module  304 , the value for the loopback gain, LG(f), received from the noise level estimation module  306  and a signal φ 1 . The signal φ 1  represents the total gain that is introduced by signal processing functionality implemented at the user device  104  (for example the gains introduced by digital gain control blocks  302 / 312 , noise reduction block  308 , and echo suppression module  310 ). The total gain introduced at the user device  104  side of the closed-loop communication setup can be estimated by multiplying all gains that are applied at the user device  104  side of the closed-loop communication setup. 
     As described above, in order to avoid howling, the system gains in the closed-loop communication setup needs to be tracked and kept below one. By using the estimated echo path gains received from the modelling module  304 , the value for the loopback gain, LG(f), received from the noise level estimation module  306  and the signal φ 1 , the system gain estimation module  314  is able to determine an estimate of the gain introduced at the user device  104  side of the closed-loop communication setup. 
     The estimate of the gain introduced at the user device  104  side of the closed-loop communication setup will vary with frequency. 
     The system gain estimation module  314  may be arranged to selectively control the gain applied at a signal processing module of user device  104  which contributes to the system gain based on the determined estimate of the gain introduced at the user device  104  side of the closed-loop communication setup in order to keep the system gain below one. That is, even without an indication of the gain introduced at the user device  110  side of the closed-loop communication setup, the determined estimate of the gain introduced at the user device  104  side of the closed-loop communication setup provides an indication as to the risk of a howling condition occurring. 
     The system gain estimation module  314  may estimate the gain introduced at the user device  104  side of the closed-loop communication setup and compare it to a predetermined threshold level and if it exceeds the predetermined threshold then the system gain estimation module  314  is able to determine that the risk of a howling condition occurring is high and control the gain applied at one or more signal processing modules of user device  104  which contributes to the system gain. This predetermined threshold level may for example be a value greater than or equal to 0.5. 
     The user device  104  may also receive via network interface  220  a signal φ 2  providing an estimate of the gain introduced at the user device  110  side of the closed-loop communication setup transmitted over the communication network  106  from user device  110 . The signal φ 2  may be supplied to the system gain estimation module  314 . By receiving the estimated echo path from the modelling module  304 , the value for the loopback gain, LG(f), from the noise level estimation module  306  and the signals φ 1  and φ 2 , the system gain estimation module  314  is able to determine an estimate of the system gain of the closed-loop communication setup. The system gain can be estimated by multiplying all gains that are applied in the system. 
     The estimate of the system gain of the closed-loop communication setup will vary with frequency. 
     The system gain estimation module  314  may estimate the system gain of the closed-loop communication setup and compare it to a predetermined threshold level and if it exceeds the predetermined threshold then the system gain estimation module  314  is able to control the gain applied at one or more signal processing modules of user device  104  which contributes to the system gain. This predetermined threshold level would ideally be equal to 1. However, it may be convenient to lower it in order to take into account potential inaccuracies on the estimation of each block gains. 
     The system gain estimation module  314  may control the amount of gain applied at the digital gain control module  302  based on its estimate of the gain introduced at the user device  104  side of the closed-loop communication setup or its estimate of the system gain of the closed-loop communication setup. 
     The system gain estimation module  314  may control the amount of gain applied at the noise reduction module  308  based on its estimate of the gain introduced at the user device  104  side of the closed-loop communication setup or its estimate of the system gain of the closed-loop communication setup. 
     The noise reduction module  308  is arranged to lower the noise level of the microphone signal y(t) without affecting the speech signal quality of the microphone signal y(t). Various noise reduction techniques are known to persons skilled in the art for the purpose of eliminating noise. Spectral subtraction is one of these methods to enhance speech in the presence of noise. Spectral subtraction, uses estimates of the noise spectrum and the noisy speech spectrum to form a signal-to-noise (SNR) based gain function which is multiplied with the input spectrum to suppress frequencies having a low SNR. Additionally, that gain is limited in order to avoid speech distortions when the noise is over suppress. The aim of this process is to obtain an audio signal which contains less noise than the original. The system gain estimation module  314  may control the amount of gain applied to the microphone signal y(t) in the spectral subtraction process based on its estimate of the gain introduced at the user device  104  side of the closed-loop communication setup or its estimate of the system gain of the closed-loop communication setup. 
     The system gain estimation module  314  may control the amount of gain applied at the echo suppression module  310  based on its estimate of the gain introduced at the user device  104  side of the closed-loop communication setup or its estimate of the system gain of the closed-loop communication setup. 
     A filter module in the modelling module  304  estimates, based on the loopback signal and the echo path, the contributions of the echo component to the near-end signal y(t). In one example implementation, the filter module in the modelling module  304  filters the loopback signal x(t) to generate an estimate of the echo component in the near-end signal y(t) in accordance with the estimate of the echo path. 
     The echo suppression module  310  is arranged to apply echo suppression to the time-frequency regions of the of the received audio signal y(t) that are dominated by echo. The purpose of the echo suppressor  310  is to suppress the loudspeaker echo present in the microphone signal, e.g. in a VoIP client, to a level sufficiently low for it not to be noticeable/disturbing in the presence of the near-end sounds (non-echo sounds) picked up by the microphone  212 . Echo suppression methods are known in the art. Furthermore, the echo suppression method applied by the echo suppression module  310  may be implemented in different ways. As such, the exact details of the echo suppression method are therefore not described in detail herein. 
     The echo suppression module  310  is arranged to receive as input the estimate of the echo component in the near-end signal y(t) and the microphone signal y(t) following noise reduction implemented by noise reduction module  308 . The echo suppression module  310  is arranged to determine the power of the estimated echo and the power of the microphone signal y(t)) following noise reduction. In the echo suppression module  310  the estimated echo power is used together with the determined power of the microphone signal y(t), and possible other measures, to form echo suppression gains G (t, f) for time t and frequency f. The possible other measures may include but are not limited to information about the accuracy of the filter, and information about nonlinearities. An echo suppression gain G (t, f) for time t and frequency f is the ratio of the power of the output signal to the power of the input signal of the echo suppression module  310 . These echo suppression gains have the purpose of suppressing any echo s(t) in the microphone signal y(t) to such a level that they are not noticeable in the presence of the near-end signal in the microphone input. 
     The system gain estimation module  314  may control the level of the echo suppression gains based on its estimate of the gain introduced at the user device  104  side of the closed-loop communication setup or its estimate of the system gain of the closed-loop communication setup. 
     The echo suppression module  310  outputs the received signal, with the echo having been suppressed, for further processing at the digital gain control module  312   
     The system gain estimation module  314  may control the amount of gain applied at the digital gain control module  312  based on its estimate of the gain introduced at the user device  104  side of the closed-loop communication setup or its estimate of the system gain of the closed-loop communication setup. 
     The signal output from the digital gain control module  312  may be processed by the client  206  (e.g. encoded and packetized) and then transmitted over the network  106  to the user device  110  in a call between the users  102  and  108 . Additionally or alternatively, the signal output from the digital gain control module  312  may be used for other purposes by the user device  104 , e.g. the signal may be stored in the memory  214  or used as an input to an application which is executing at the user device  104 . 
     In the embodiments described above, the echo removal is implemented in a VoIP system (e.g. the received audio signal may include speech of the user  102  for transmission to the user device  110  during a call between the users  102  and  108  over the communication system  100 ). However, the loopback gain estimation method described herein can be applied in any suitable system in which howling reduction is to be applied. 
     In the embodiments described above, the acoustic system  100  comprises just two user devices. However it will be appreciated that the howling reduction method based on loopback gain estimation described herein can be applied in acoustic systems comprising more than two user devices 
     The methods described herein may be implemented by executing a computer program product (e.g. the client  206 ) at the user device  104 . That is, a computer program product may be configured to reduce noise in an acoustic system comprising the user device  104  and at least one further user device wherein the computer program product is embodied on a computer-readable storage medium (e.g. stored in the memory  214 ) and configured so as when executed on the CPU  202  of the device  104  to perform the operations of any of the methods described herein. 
     Generally, any of the functions described herein (e.g. the functional modules shown in  FIG. 3  and the functional steps shown in  FIG. 4 ) can be implemented using software, firmware, hardware (e.g., fixed logic circuitry), or a combination of these implementations. The modules and steps shown separately in  FIGS. 3 and 4  may or may not be implemented as separate modules or steps. The terms “module,” “functionality,” “component” and “logic” as used herein generally represent software, firmware, hardware, or a combination thereof. In the case of a software implementation, the module, functionality, or logic represents program code that performs specified tasks when executed on a processor (e.g. CPU or CPUs). The program code can be stored in one or more computer readable memory devices. The features of the techniques described herein are platform-independent, meaning that the techniques may be implemented on a variety of commercial computing platforms having a variety of processors. For example, the user devices may also include an entity (e.g. software) that causes hardware of the user devices to perform operations, e.g., processors functional blocks, and so on. For example, the user devices may include a computer-readable medium that may be configured to maintain instructions that cause the user devices, and more particularly the operating system and associated hardware of the user devices to perform operations. Thus, the instructions function to configure the operating system and associated hardware to perform the operations and in this way result in transformation of the operating system and associated hardware to perform functions. The instructions may be provided by the computer-readable medium to the user devices through a variety of different configurations. 
     One such configuration of a computer-readable medium is signal bearing medium and thus is configured to transmit the instructions (e.g. as a carrier wave) to the computing device, such as via a network. The computer-readable medium may also be configured as a computer-readable storage medium and thus is not a signal bearing medium. Examples of a computer-readable storage medium include a random-access memory (RAM), read-only memory (ROM), an optical disc, flash memory, hard disk memory, and other memory devices that may us magnetic, optical, and other techniques to store instructions and other data. 
     Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.