A Statistical Model-Based V/UV Decision under Background Noise Environments

摘要

In this letter, we propose an approach to incorporate a statistical model for the voiced/unvoiced (V/UV) speech decision under background noise environments. Our approach consists of splitting the input noisy speech into two separate bands and applying a statistical model for each band. We compute and compare the likelihood ratio (LR) for each band based on the statistical model and estimated noise statistics for the V/UV decision. According to the simulation test, the proposed V/UV decision shows a better performance compared with the selectable mode vocoder (SMV) V/UV decision algorithm, particularly in clean and white noise environments.