Denoiser 2 settings5/5/2023 It is optimized on both time and frequency domains, using multiple loss functions.Įmpirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb.Īdditionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities. ![]() The proposed model is based on an encoder-decoder architecture with skip-connections. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. We provide a PyTorch implementation of the paper: Real Time Speech Enhancement in the Waveform Domain. Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)
0 Comments
Leave a Reply.AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |