Abstract
The estimation of the noise power spectral density (PSD) forms
a critical component of several existing single channel speech enhancement
systems. In this paper, we evaluate one new and some of
the existing and commonly used noise PSD estimation algorithms in
terms of the spectral estimation accuracy and the enhancement performance
for different commonly encountered background noises,
which are stationary and non-stationary in nature. The evaluated algorithms
include the Minimum Statistics, MMSE, IMCRA methods
and a new model-based method.
a critical component of several existing single channel speech enhancement
systems. In this paper, we evaluate one new and some of
the existing and commonly used noise PSD estimation algorithms in
terms of the spectral estimation accuracy and the enhancement performance
for different commonly encountered background noises,
which are stationary and non-stationary in nature. The evaluated algorithms
include the Minimum Statistics, MMSE, IMCRA methods
and a new model-based method.
| Original language | English |
|---|---|
| Title of host publication | 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
| Publisher | IEEE |
| Publication date | 2018 |
| Pages | 5464-5468 |
| ISBN (Print) | 978-1-5386-4657-1 |
| ISBN (Electronic) | 978-1-5386-4658-8, 978-1-5386-4659-5 |
| DOIs | |
| Publication status | Published - 2018 |
| Event | 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Calgary, Canada Duration: 15 Apr 2018 → 20 Apr 2018 https://2018.ieeeicassp.org/ |
Conference
| Conference | 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
|---|---|
| Country/Territory | Canada |
| City | Calgary |
| Period | 15/04/2018 → 20/04/2018 |
| Internet address |
| Series | I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings |
|---|---|
| ISSN | 1520-6149 |
Keywords
- speech enhancement, noise PSD estimation, autoregressive models