In general terms voice communication can be said to involve the transmission of a near-end speech signal to a far-end or distant user, where a speech enhancement problem consists in the estimation of a relatively clean speech signal from a captured noisy signal. There are a number of single-microphone configurations which allow for improvements when considering the suppression of noise.
Use of two distinct microphones to simultaneously capture a sound field allows for a possible usage of spatial information and characteristics of the sound source(s) from which a sound field captured by the microphones originates. These characteristics may relate to the relative placement of the microphones on a mobile communication device as well as the design and usage of the communication device. A proper estimation of the noise characteristics forms a basis for an efficient use of noise suppression algorithms, such as e.g. algorithms which are based on spectral subtraction, which is commonly used in this particular technical field.
Different methods for executing dual-microphone noise suppression have been suggested based on the assumption that the signals received by the microphones have a relatively similar power level for the near-end signal generated by the user of the communication device.
In WO 2007/059255 noise suppression is performed by generating a ratio of power difference and sum signals from input signals captured by two microphones, after which the input signals are being processed such as to suppress the estimated noise from one of the two input signals.
A drawback with WO 2007/059255, which is relying on the assumption of small or even no gain difference between signals captured by a microphone pair is that, in practice, dual-microphones mounted side-by-side on mobile devices will present an arbitrary gain difference. This difference is both inherent to the high variation of the manufactured microphone gains and to the variation in the near-field signal received levels with small changes in the position of the mobile device relative to the speaker's mouth, when the device is used in handheld mode.
Other methods, such as e.g. the one presented in US 2007/0154031 exploit the level differences between received microphone signals to discriminate speech and noise in the time-frequency domain and to suppress the noise accordingly.
However, while the use of a microphone for capturing noise, typically referred to as a reference microphone, in conjunction with a microphone used for capturing basically speech, typically referred to as a primary microphone, and the exploitation of a resulting signal level difference at the two microphones can allow for a fairly good detection of the speech and noise signals in the time-frequency domain, noise suppression based on a masking approach, such as the one described in US 2007/0154031 normally results in a high distortion of the extracted speech signal and introduces also often musical noise.
A spectral subtraction based method applicable for dual-microphone noise suppression has been suggested in WO2000/062579, where spectral processors are used for producing separate noise reduced and noise estimated signals.
Spectral subtraction techniques, such as the one described in WO2000/062579, have generally proven to be relatively robust to speech cancellation and to provide a relatively good suppression of stationary noise. The filtering process which is normally used in association with spectral subtraction usually relies on estimates of the spectrum of the noise and the spectrum of the noisy speech. The noise spectrum is preferably estimated during speech pauses and is based on the estimation of the stationary part of the noise only. Many background noise environments, such as e.g. restaurants, airports, streets and other public places, are however characterized by the presence of a high level of non-stationary noise which is not taken into consideration in known implementations, which are based on spectral subtraction techniques, and hence when applying these techniques the non-stationary noise component remains unfiltered in the signal transmitted to the far-end user of the communication link.