3 accepted papers
Most Bayesian clean speech estimators, like the Wiener filter or Ephraim and Malah's amplitude estimators, are derived under the assumption that the true power spectral density (PSD) of speech is known. In practice, however, only estimates are available. When the PSD estimation errors are neglected,…
We present in this paper two loss functions tailored for rare audio event detection in audio streams. The weighted loss is designed to tackle the common issue of imbalanced data in background/foreground classification while the multi-task loss enables the networks to simultaneously model the class d…
For the enhancement of speech degraded by noise, accurate estimation of the noise power spectral density (PSD) is indispensable, especially if only a single microphone signal is available. Fast and accurate tracking of the noise PSD is particularly challenging in highly non-stationary noise types, s…