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Speaker embedding (d-vector) trained with GE2E loss

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I run the code in preprocess.py and it has an error: `Traceback (most recent call last): File "preprocess.py", line 92, in preprocess(**vars(PARSER.parse_args())) File "preprocess.py", line 71, in preprocess for speaker_name,...

When the input tensor shape is [1, 800] or [1, 320] and When I use the following code > mel_tensor = wav2mel(wav_tensor, 16000) # 16000 is the sample rate I...

I am using pre-trained model to get the embedding but getting below error: ``` RuntimeError Traceback (most recent call last) in 2 import torchaudio 3 ----> 4 wav2mel = torch.jit.load("wav2mel.pt")...

I am run visualization and get error: [INFO] model loaded. Preprocess: 1% 12/889 [00:00 Tensor: wav_tensor0 = (self.sox_effects).forward(wav_tensor, sample_rate, ) mel_tensor = (self.log_melspectrogram).forward(wav_tensor0, ) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

When i run the usage,i encountered a problem: C:\Users\86151\Desktop\Voice-Recognize-system-master\Scripts\python.exe C:\Users\86151\Desktop\Voice-Recognize-system-master\dvector-master\demo.py Traceback (most recent call last): File "C:\Users\86151\Desktop\Voice-Recognize-system-master\dvector-master\demo.py", line 5, in wav2mel = torch.jit.load("wav2mel.pt") File "C:\Users\86151\Desktop\Voice-Recognize-system-master\lib\site-packages\torch\jit\_serialization.py", line 162, in load cpp_module...

I wanna get a 601 dim dvector,and follow the step "Train from scratch" 1. python preprocess.py ../LibriSpeech/train-clean-360 -o preprocessed 2. python train.py preprocessed train601 then there is an error Traceback...

Running visualize("preprocessed", "preprocessed/wav2mel.pt", "dvector-step5000.pt", ".") Getting the following error while torch.jit.load ``` RuntimeError: Unknown builtin op: torchaudio_sox::apply_effects_tensor. Could not find any similar ops to torchaudio_sox::apply_effects_tensor. This op may not exist...