Title
Speech Reinforcement Based On Soft Decision Under Far-End Noise Environments
Abstract
In this letter, we propose a speech reinforcement technique based on soft decision under both the far-end and near-end noise environments. We amplify the estimated clean speech signal at the far-end based on the estimated ambient noise spectrum at the near-end, as opposed to reinforcing the noisy far-end speech signal, so that it can be heard more intelligibly in far-end noisy environments. To obtain an effective reinforcement technique, we adopt the soft decision scheme incorporating a speech absence probability (SAP) in the frequency dependent signal-to-noise ratio (SNR) recovery method where the clean speech spectrum is estimated and the reinforcement gain is inherently derived and modified within the unified framework. Performance of the proposed method is evaluated by a subjective testing under various noisy environments. This is an improvement over previous approaches.
Year
DOI
Venue
2009
10.1587/transfun.E92.A.2116
IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES
Keywords
Field
DocType
soft decision, SAP, speech reinforcement, SNR recovery, masking effect, near-end ambient noise estimation
Transmission quality,Speech spectrum,Background noise,Noise (signal processing),Noise measurement,Voice activity detection,Psychology,Speech recognition,Reinforcement,Intelligibility (communication)
Journal
Volume
Issue
ISSN
E92A
8
0916-8508
Citations 
PageRank 
References 
0
0.34
4
Authors
3
Name
Order
Citations
PageRank
Jae-Hun Choi1295.57
Woo-Sang Park200.34
Joon-Hyuk Chang326321.87