Towards a Generalization of Relative Transfer Functions to More Than One Source

A. Deleforge (FAU Erlangen-Nuremberg), S. Gannot (Bar-Ilan University), and W. Kellermann (FAU Erlangen-Nuremberg)
European Signal Processing Conference (EUSIPCO), Nice, France, Aug. 31 – Sept. 4, 2015.
[showhide type=”Abstract”]Abstract: We propose a natural way to generalize relative transfer functions (RTFs) to more than one source. We first prove that such a generalization is not possible using a single multichannel spectro-temporal observation, regardless of the number of microphones. We then introduce a new transform for multichannel multi-frame spectrograms, i.e., containing several channels and time frames in each time-frequency bin. This transform allows a natural generalization which satisfies the three key properties of RTFs, namely, they can be directly estimated from observed signals, they capture spatial properties of the sources and they do not depend on emitted signals. Through simulated experiments, we show how this new method can localize multiple simultaneously active sound sources using short spectro-temporal windows, without relying on source separation. [/showhide]
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