Comments (2)
- The
Container
is quite limited for now and I'm not sure it makes sense to try and fit allforward
into one class. Probably the solution will be to subclass it (but I'll try to find something clever to keep the saving and loading practical as it is now). - For the masking, a
'mag'
mask is a magnitude mask which is applied to the complex representation. It's strictly equivalent to a magnitude mask, but the phase is kept so the resynthesis can be done.
from asteroid.
Solved by #19
from asteroid.
Related Issues (20)
- Legacy Install Failure HOT 1
- X-UMX: lr_scheduler_step() missing 1 required positional argument: 'metric' HOT 4
- About the usage HOT 1
- torchmetrics>=0.11.0 HOT 2
- HOW TO USE OTHER DATASET TO TRAIN Multi-Decoder-DPRNN MODEL HOT 3
- val loss in distribute training HOT 2
- refer to asteroid/dsp/overlap_add.py:31 LambdaOverlapAdd model use file_separate output audio file is All noise HOT 2
- KeyError while evaluating musdb18 (X-UMX) HOT 2
- RunTimeError related with NCCL when training librimix recipe HOT 3
- Input and output mean scales updated during training (X-UMX) HOT 5
- how to train the dataset HOT 3
- Transfer learning of pretrained model on custom dataset HOT 2
- Inference script to hear samples from AVSpeech Model ?
- Support for mobile development (Android)? HOT 2
- PIT Loss for multichannel audio for speech separation HOT 1
- test model
- mossFormer2 & sepTDA models HOT 2
- KeyError: 'source_2_path' when training ConvTasNet using enh_single mode HOT 3
- ConvTasNet pretrained huggingface model inference setup
- How to use GPU rather than CPU
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