Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.
Segfault while running the following command on macos 12.3.1 with Python 3.9.12
WAV file size: 81MB
Note:
With smaller file sizes (e.g. 2MB) denoising works and the enhanced files are generated successfully.
Hardware
Model Name: MacBook Pro Model Identifier: MacBookPro16,1 Processor Name: 8-Core Intel Core i9 Processor Speed: 2.4 GHz Number of Processors: 1 Total Number of Cores: 8 L2 Cache (per Core): 256 KB L3 Cache: 16 MB Hyper-Threading Technology: Enabled Memory: 32 GB System Firmware Version: 1731.100.130.0.0 (iBridge: 19.16.14243.0.0,0) OS Loader Version: 540.100.7~23 Graphics: AMD Radeon Pro 5300M
OS Crashlog