Sorry, you need to enable JavaScript to visit this website.

Improved Noise Characterization for Relative Impulse Response Estimation

Citation Author(s):
Bhaskar D. Rao, Ritwik Giri, Tao Zhang
Submitted by:
Tharun Adithya ...
Last updated:
12 April 2018 - 4:38pm
Document Type:
Poster
Document Year:
2018
Event:
Presenters:
Tharun Adithya Srikrishnan
Paper Code:
ICASSP18001
 

Relative Impulse Responses (ReIRs) have several applications in speech enhancement, noise suppression and source localization for multi-channel speech processing in reverberant environments. Noise is usually assumed to be white Gaussian during the estimation of the ReIR between two microphones. We show that the noise in this system identification problem is instead dependent upon the microphone measurements and the ReIR itself. We then present modifications that incorporate this new noise model into three prevalent methods: Least Squares, Non-Stationary Frequency Domain and Sparse Bayesian Learning based approaches. We demonstrated improvements with an experimental study using real-world measurements in various noise environments.

up
0 users have voted: