On the difference-to-sum power ratio of speech and wind noise based on the Corcos model
This work addresses wind noise detection in speech processing, which is an incremental improvement for audio enhancement applications.
The authors tackled the problem of detecting wind noise in speech by generalizing the difference-to-sum power ratio using the Corcos model for convective turbulence, and they validated it with real data, showing improved detection performance compared to an existing multi-channel approach.
The difference-to-sum power ratio was proposed and used to suppress wind noise under specific acoustic conditions. In this contribution, a general formulation of the difference-to-sum power ratio associated with a mixture of speech and wind noise is proposed and analyzed. In particular, it is assumed that the complex coherence of convective turbulence can be modelled by the Corcos model. In contrast to the work in which the power ratio was first presented, the employed Corcos model holds for every possible air stream direction and takes into account the lateral coherence decay rate. The obtained expression is subsequently validated with real data for a dual microphone set-up. Finally, the difference-to- sum power ratio is exploited as a spatial feature to indicate the frame-wise presence of wind noise, obtaining improved detection performance when compared to an existing multi-channel wind noise detection approach.