Abstract
In this paper, a study addressing the task of tracking multiple concurrent speakers in reverberant conditions is presented. Since both past and future observations can contribute to the current location estimate, we propose a forward-backward approach, which improves tracking accuracy by introducing near-future data to the estimator, in the cost of an additional short latency. Unlike classical target tracking, we apply a non-Bayesian approach, which does not make assumptions with respect to the target trajectories, except for assuming a realistic change in the parameters due to natural behaviour. The proposed method is based on the recursive expectation-maximization (REM) approach. The new method is dubbed forward-backward recursive expectation-maximization (FB-REM). The performance is demonstrated using an experimental study, where the tested scenarios involve both simulated and recorded signals, with typical reverberation levels and multiple moving sources. It is shown that the proposed algorithm outperforms the regular common causal (REM).
Original language | English |
---|---|
Article number | 2 |
Journal | Eurasip Journal on Audio, Speech, and Music Processing |
Volume | 2021 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2021 |
Bibliographical note
Publisher Copyright:© 2021, The Author(s).
Funding
This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 871245.
Funders | Funder number |
---|---|
Horizon 2020 Framework Programme | 871245 |
Keywords
- Forward-backward
- Microphone arrays
- Recursive expectation-maximization
- Simultaneous speakers
- Sound source tracking
- W-disjoint orthogonality