Title | A Probabilistic Approach For Phase Estimation in Single-Channel Speech Enhancement Using Von Mises Phase Priors |
Publication Type | Conference Paper |
Year of Publication | 2014 |
Authors | Kulmer, J., Mowlaee P., & Watanabe M. |
Conference Name | IEEE Workshop on Machine Learning for Signal Processing |
Date Published | Sept. |
Abstract | In many artificial intelligence systems human voice is considered as the medium for information transmission. Human-machine communication by voice becomes difficult when speech is mixed with some background noise. As a remedy, a single-channel speech enhancement is indispensable for reducing background noise from noisy speech to make it suitable for automatic speech recognition and telephony speech. While the conventional techniques for single-channel speech enhancement incorporate noisy phase in both amplitude estimation and signal reconstruction stages, in this paper we propose a probabilistic method to estimate the clean speech phase from noisy observation. Our proposed method consists of phase unwrapping followed by threshold-based temporal smoothing using von Mises phase priors. The proposed phase enhancement method leads to improved speech quality and intelligibility predicted by instrumental measures without explicit incorporation of amplitude enhancement.
|
URL | https://ieeexplore.ieee.org/document/6958861/ |
Citation Key | MLSP2014 |