| Paper: | SP-P1.11 | ||
| Session: | Speech Coding for Networks / Single-Channel Speech Enhancement | ||
| Time: | Tuesday, May 18, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Speech Processing: Speech Enhancement | ||
| Title: | A NOISE ESTIMATION ALGORITHM WITH RAPID ADAPTATION FOR HIGHLY NON-STATIONARY ENVIRONMENTS | ||
| Authors: | Sundarrajan Rangachari; University of Texas, Dallas | ||
| Philipos Loizou; University of Texas, Dallas | |||
| Yi Hu; University of Texas, Dallas | |||
| Abstract: | A noise estimation algorithm is proposed for highly non-stationary noise environments. The noise estimate is updated by averaging the noisy speech power spectrum using a time and frequency dependent smoothing factor, which is adjusted based on signal presence probability in subbands. Signal presence is determined by computing the ratio of the noisy speech power spectrum to its local minimum, which is computed by averaging past values of the noisy speech power spectra with a look-ahead factor. The local minimum estimation algorithm adapts very quickly to highly non-stationary noise environments. This was confirmed with formal listening tests that indicated that our noise estimation algorithm when integrated in speech enhancement was preferred over other noise estimation algorithms. | ||
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