MSGLA is an iterative phase reconstruction framework that combines STFT consistency with geometric constraints; its noise-phase variant achieves small but consistent gains in background suppression metrics.
Enhancement of speech corrupted by acoustic noise,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
eess.AS 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
support 1representative citing papers
citing papers explorer
-
An Investigation on Combining Geometry and Consistency Constraints into Phase Estimation for Speech Enhancement
MSGLA is an iterative phase reconstruction framework that combines STFT consistency with geometric constraints; its noise-phase variant achieves small but consistent gains in background suppression metrics.