Abstract: A method implemented during a communication event conducted between a user device and at least one further user device over a communications network, the method comprising: receiving an audio signal that is to be output from a speaker of said user device, said audio signal comprising at least one microphone signal transmitted from the at least one further user device; detecting that said audio signal comprises at least one audio component of a microphone signal transmitted from one or more of one of said at least one further user device that is co-located with said user device; and based on this detection, removing said at least one audio component from said audio signal to produce an output audio signal for output from said speaker.

Abstract: A method of echo cancellation in an acoustic system, comprising a first user device and at least one further user device, the method comprising, at the first user device: detecting an audio signal received from the at least one further user device over a communications network; supplying the audio signal when received to an audio signal processing module of the first user device, wherein the audio signal processing module processes the audio signal and outputs a processed audio signal to audio output means of the first user device; and controlling an echo cancellation process for cancelling echo from an audio signal received via audio input means of the first user device based on a loopback signal provided by the processed audio signal and selectively based on the received audio signal when detected.

Abstract: Echo removal techniques are described. As part of the echo removal, an adaptive model estimate of the echo in a received audio signal is determined using an adaptive model based on an outputted audio signal and the received audio signal. The adaptive model executes an algorithm comprising a convergence parameter to determine filter coefficients and uses said filter coefficients to filter the outputted audio signal to determine the adaptive model estimate of the echo. An accuracy value of the adaptive model is determined according to an echo return loss enhancement metric. The convergence parameter is updated based on the accuracy value. The adaptive model estimate of the echo is used to remove the echo in the received audio signal.

Abstract: Echo removal techniques are described. An echo path of the echo in a received audio signal is modelled using a first model to determine a first model estimate of the echo. The first model estimate is used to determine a first performance value according to a performance metric. The first performance value is compared with a threshold value. It is determined if the echo path can be deemed linear based on the comparison. If so, the first model estimate of the echo is used to remove the echo in the received audio signal. Otherwise, the echo path of the echo is switched to be modelled using a second model to determine a second model estimate of the echo, and the second model estimate of the echo is used to remove the echo in the received audio signal.

Abstract: Echo removal techniques are described. As part of the echo removal, a first model estimate of the echo in the received audio signal is determined using a first model and a second model estimate of the echo is determined using a second model. A first accuracy value of the first model is determined according to a model accuracy measure, and a second accuracy value of the second model is determined according to the model accuracy measure. It is then determined if the first model is more accurate than the second model based on a comparison of the first accuracy value and the second accuracy value and the second model is selectively updated based on said comparison. Echo removal is applied to the received audio signal using only the second model estimate of the echo.

Abstract: A method implemented during a communication event conducted between a user device and at least one further user device over a communications network, the method comprising: receiving an audio signal that is to be output from a speaker of said user device, said audio signal comprising at least one microphone signal transmitted from the at least one further user device; detecting that said audio signal comprises at least one audio component of a microphone signal transmitted from one or more of one of said at least one further user device that is co-located with said user device; and based on this detection, removing said at least one audio component from said audio signal to produce an output audio signal for output from said speaker.

Abstract: An echo path of the echo in a received audio signal is modelled using an adaptive model to determine an adaptive model estimate of the echo. The adaptive model estimate is used to determine an estimate of the echo power of the echo in the received audio signal. The power of the received audio signal is determined. The estimate of the echo power and the determined power of the received audio signal are used to determine echo suppression gains. Temporal smoothing is applied to one or more of the echo suppression gains and the one or more smoothed echo suppression gains are used to apply echo suppression to the received audio signal, thereby suppressing the echo in the received audio signal, wherein the amount of smoothing applied to the echo suppression gains is varied according to a non-decreasing function of the frequency of the received audio signal.

Abstract: Method, user device and computer program product for suppressing echo. An audio signal is output from a speaker. A microphone receives an audio signal, wherein the received audio signal includes an echo resulting from said outputted audio signal. A Finite Impulse Response filter estimate ?(t) is dynamically adapted in the time domain based on the outputted audio signal and the received audio signal to model an echo path h(t) of the echo in the received audio signal. At least one power response is determined from the filter estimate ?(t) and used to estimate the echo power of the echo in the received audio signal. The estimated echo power is used to apply echo suppression to the received audio signal, thereby suppressing the echo in the received audio signal.

Abstract: Method, user device and computer program product for suppressing echo. An audio signal is outputted from a speaker. A microphone receives an audio signal which includes echo resulting from said outputted audio signal. An echo path of the echo is modelled using a plurality of models. A first of the models is a FIR based model and a second of the models is different to the first model. The first model is used to determine a first model estimate of the echo power of a first component of the echo. The second model is used to determine a second model estimate of the echo power of a second component of the echo. The first and second model estimates of the echo power are combined. The combined estimate of the echo power is used to apply echo suppression to the received audio signal, thereby suppressing the echo.

Abstract: The present invention relates to an echo canceller (300) for estimating a model of an echo signal and a method thereof. The echo canceller comprises at least an adaptive main filter (301) for modeling the echo signal and an adaptive shadow filter (302) for modeling the echo signal. The adaptive main filter is an adaptive filter for which the adaptation speed is proportional to a system noise estimate and the adaptation speed of the shadow filter (302) is faster than the adaptation speed of the adaptive main filter (301). The echo canceller (300) comprises a processor (303) for determining whether the adaptive shadow filter models the echo signal better than the adaptive main filter and an updater (304) for updating the system noise estimate of the adaptive main filter (301) if the adaptive shadow filter models (302) the echo signal better than the adaptive main filter (301).

Abstract: A method of reducing noise in an acoustic system, the method comprising at a first user terminal: receiving an audio signal from at least one further user terminal over a network; executing a communication client on a processing unit, the client configured so as when executed to: supply the audio signal to an audio signal processing module of the first user terminal, wherein the processing module processes the audio signal, whereby a level of gain is applied to the audio signal, and outputs a processed audio signal to a speaker; estimate a noise level of the audio signal and the processed audio signal and estimate the gain applied by the processing module taking into account both the noise level estimates; selectively apply a system gain reduction step to at least one of the audio signal and an audio signal received via a microphone, based on at least the estimated gain.

Abstract: An echo path of the echo in a received audio signal is modelled using an adaptive model to determine an adaptive model estimate of the echo. The adaptive model estimate is used to determine an estimate of the echo power of the echo in the received audio signal. The power of the received audio signal is determined. The estimate of the echo power and the determined power of the received audio signal are used to determine echo suppression gains. Temporal smoothing is applied to one or more of the echo suppression gains and the one or more smoothed echo suppression gains are used to apply echo suppression to the received audio signal, thereby suppressing the echo in the received audio signal, wherein the amount of smoothing applied to the echo suppression gains is varied according to a non-decreasing function of the frequency of the received audio signal.

Abstract: Echo removal techniques are described. As part of the echo removal, a first model estimate of the echo in the received audio signal is determined using a first model and a second model estimate of the echo is determined using a second model. A first accuracy value of the first model is determined according to a model accuracy measure, and a second accuracy value of the second model is determined according to the model accuracy measure. It is then determined if the first model is more accurate than the second model based on a comparison of the first accuracy value and the second accuracy value and the second model is selectively updated based on said comparison. Echo removal is applied to the received audio signal using only the second model estimate of the echo.

Abstract: Echo removal techniques are described. An echo path of the echo in a received audio signal is modelled using a first model to determine a first model estimate of the echo. The first model estimate is used to determine a first performance value according to a performance metric. The first performance value is compared with a threshold value. It is determined if the echo path can be deemed linear based on the comparison. If so, the first model estimate of the echo is used to remove the echo in the received audio signal. Otherwise, the echo path of the echo is switched to be modelled using a second model to determine a second model estimate of the echo, and the second model estimate of the echo is used to remove the echo in the received audio signal.

Abstract: Echo removal techniques are described. As part of the echo removal, an adaptive model estimate of the echo in a received audio signal is determined using an adaptive model based on an outputted audio signal and the received audio signal. The adaptive model executes an algorithm comprising a convergence parameter to determine filter coefficients and uses said filter coefficients to filter the outputted audio signal to determine the adaptive model estimate of the echo. An accuracy value of the adaptive model is determined according to an echo return loss enhancement metric. The convergence parameter is updated based on the accuracy value. The adaptive model estimate of the echo is used to remove the echo in the received audio signal.

Abstract: A method of echo cancellation in an acoustic system, comprising a first user device and at least one further user device, the method comprising, at the first user device: detecting an audio signal received from the at least one further user device over a communications network; supplying the audio signal when received to an audio signal processing module of the first user device, wherein the audio signal processing module processes the audio signal and outputs a processed audio signal to audio output means of the first user device; and controlling an echo cancellation process for cancelling echo from an audio signal received via audio input means of the first user device based on a loopback signal provided by the processed audio signal and selectively based on the received audio signal when detected.

Abstract: A method of reducing noise in an acoustic system, the method comprising at a first user terminal: receiving an audio signal from at least one further user terminal over a network; executing a communication client on a processing unit, the client configured so as when executed to: supply the audio signal to an audio signal processing module of the first user terminal, wherein the processing module processes the audio signal, whereby a level of gain is applied to the audio signal, and outputs a processed audio signal to a speaker; estimate a noise level of the audio signal and the processed audio signal and estimate the gain applied by the processing module taking into account both the noise level estimates; selectively apply a system gain reduction step to at least one of the audio signal and an audio signal received via a microphone, based on at least the estimated gain.

Abstract: Method, user device and computer program product for suppressing echo. An audio signal is outputted from a speaker. A microphone receives an audio signal which includes echo resulting from said outputted audio signal. An echo path of the echo is modelled using a plurality of models. A first of the models is a FIR based model and a second of the models is different to the first model. The first model is used to determine a first model estimate of the echo power of a first component of the echo. The second model is used to determine a second model estimate of the echo power of a second component of the echo. The first and second model estimates of the echo power are combined. The combined estimate of the echo power is used to apply echo suppression to the received audio signal, thereby suppressing the echo.

Abstract: Method, user device and computer program product for suppressing echo. An audio signal is output from a speaker. A microphone receives an audio signal, wherein the received audio signal includes an echo resulting from said outputted audio signal. A Finite Impulse Response filter estimate ?(t) is dynamically adapted in the time domain based on the outputted audio signal and the received audio signal to model an echo path h(t) of the echo in the received audio signal. At least one power response is determined from the filter estimate ?(t) and used to estimate the echo power of the echo in the received audio signal. The estimated echo power is used to apply echo suppression to the received audio signal, thereby suppressing the echo in the received audio signal.

Abstract: A harmonic echo power estimator estimates power of echo generated by harmonic loudspeaker nonlinearities in a user equipment having an echo path between a loudspeaker input and a microphone output. The estimator includes a frequency band mapper that maps each frequency band in a set of loudspeaker output signal frequency bands into a corresponding array of loudspeaker input signal frequency bands, where each frequency band in the set is mapped into several frequency bands in the corresponding array. A power estimator determines a power estimate of each input signal in each array of frequency bands. A power estimate combiner combines determined power estimates in each array of frequency bands into a corresponding estimate of loudspeaker input power generating harmonic loudspeaker nonlinearities. A power estimate transformer transforms the estimates of loudspeaker input power across the echo path into power estimates of the echo generated by the harmonic loudspeaker nonlinearities.