DYNAMIC RELATIVE TRANSFER FUNCTION ESTIMATION USING STRUCTURED SPARSE BAYESIAN LEARNING

摘要

The use of a dynamic Relative Transfer Function (RTF) between two or more microphones may be used to improve multi-microphone speech processing applications. The dynamic RTF may improve speech intelligibility and speech quality in the presence of environmental changes, such as variations in head or body movements, variations in hearing device characteristics or wearing positions, or variations in room or environment acoustics. The use of an efficient and fast dynamic RTF estimation algorithm using short burst of noisy, reverberant mic recordings, which will be robust to head movements may provide more accurate RTFs which may lead to a significant performance increase.

主权项

1. A hearing device for processing signals, the system comprising:
a first transducer to transduce a first audio source into a first signal; a second transducer to transduce a first audio source into a second signal; and a processor configured to execute instructions to:
determine an estimated Relative Transfer Function (RTF) based on the first signal and the second signal using a hierarchical Bayesian framework;determine a target signal based on the estimated RTF; andgenerate a noise reference signal based on the first signal, the second signal, and a cancellation of the target signal.