Name
Title | ||
|---|---|---|
Noise Estimation For Speech Enhancement Based On Quasi-Gaussian Distributed Power Spectrum Series By Radical Root Transformation |
Abstract | ||
|---|---|---|
This contribution presents and analyzes the statistical regularity related to the noise power spectrum series and the speech spectrum series. It also undertakes a thorough inquiry of the quasi-Gaussian distributed power spectrum series obtained using the radical root transformation. Consequently, a noise-estimation algorithm is proposed for speech enhancement. This method is effective for separating the noise power spectrum from the noisy speech power spectrum. In contrast to standard noise-estimation algorithms, the proposed method requires no speech activity detector. It was confirmed to be conceptually simple and well suited to real-time implementations. Practical experiment tests indicated that our method is preferred over previous methods. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1587/transfun.E100.A.1306 | IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES |
Keywords | Field | DocType |
power spectrum series, quasi-Gaussian distribution, speech activity detector, radical root transformation | Speech enhancement,Distributed power,Speech recognition,Gaussian,Mathematics | Journal |
Volume | Issue | ISSN |
E100A | 6 | 1745-1337 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ye Tian | 1 | 418 | 36.84 |
| Yasunari Yokota | 2 | 3 | 3.82 |