Multiple comparison procedures
Multiple comparison procedures
On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Two-Channel Blind Deconvolution for Non-Minimum Phase Impulse Responses
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 2 - Volume 2
Binaural sound source distance learning in rooms
IEEE Transactions on Audio, Speech, and Language Processing
| Hi-index | 0.01 |
One of the principal cues believed to be used by listeners to estimate the distance to a sound source is the ratio of energies along the direct and indirect paths to the receiver. In essence this "direct-to-reverberant" energy ratio reveals the absolute distance component of the direct energy by normalizing by what is assumed to be distance-independent reverberant energy. Earlier approaches to direct-to-reverberant energy ratio calculation made use of the estimated room impulse response, but these techniques are computationally expensive and inaccurate in practice. This paper proposes and evaluates an alternative approach which uses binaural signals to segregate energy arriving from the estimated direction of the direct source from that arriving from other directions, employing a novel binaural equalization-cancellation technique. The system is integrated with a probabilistic inference framework, particle filtering, to handle the nonstationarity of energy-based measurements. The algorithm is capable of using reverberation to estimate source distance in large rooms with errors of less than 1 m for static sources and 1.5-3.5 m for sources with varying degrees of motion complexity. Model performance can be accounted for largely in terms of a competition between auditory horizon and source energy fluctuation effects.