Abstract
A method for recovering the LPC spectrum from a microphone array input signal corrupted by less directional ambient noise is proposed. This method is based on the subspace method, in which directional signal and non-directional noise is classified in the subspace domain using eigenvalue analysis of the spatial correlation matrix. In this paper, the coherent subspace (CSS) method, a broadband extension of the subspace method, is employed. The advantage of this method is that it requires a much smaller number of averages in the time domain for estimating subspace, suitable feature for frame processing such as speech recognition. To enhance the performance of noise reduction, elimination of noise-dominant subspace using projection is further proposed, which is effective when the SNR is low and classification of noise and signals using eigenvalue analysis is difficult.
Original language | English |
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Pages (from-to) | 2276-2285 |
Number of pages | 10 |
Journal | IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences |
Volume | E80-A |
Issue number | 11 |
Publication status | Published - 1997 |
Externally published | Yes |
Keywords
- Array signal processing
- Coherent subspace method
- Eigenvalue analysis
- LPC spectrum
- Spatial correlation matrix
- Speech enhancement
ASJC Scopus subject areas
- Signal Processing
- Computer Graphics and Computer-Aided Design
- Electrical and Electronic Engineering
- Applied Mathematics