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.
Original language | English |
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Title of host publication | 2015 23rd European Signal Processing Conference, EUSIPCO 2015 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 419-423 |
Number of pages | 5 |
ISBN (Electronic) | 9780992862633 |
DOIs | |
State | Published - 22 Dec 2015 |
Event | 23rd European Signal Processing Conference, EUSIPCO 2015 - Nice, France Duration: 31 Aug 2015 → 4 Sep 2015 |
Publication series
Name | 2015 23rd European Signal Processing Conference, EUSIPCO 2015 |
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Conference
Conference | 23rd European Signal Processing Conference, EUSIPCO 2015 |
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Country/Territory | France |
City | Nice |
Period | 31/08/15 → 4/09/15 |
Bibliographical note
Publisher Copyright:© 2015 EURASIP.
Keywords
- Grassmannian manifolds
- Multiple sound sources localization
- Plucker Embedding
- Relative Transfer Function