NVIDIA / tacotron2

Tacotron 2 - PyTorch implementation with faster-than-realtime inference
BSD 3-Clause "New" or "Revised" License
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Tacotron2 and waveglow model not inferencing a clear output: AWS SageMaker. #524

Open hasankh17 opened 3 years ago

hasankh17 commented 3 years ago

Hello, I have trained my tacotron2 model successfully on around 2000+ audio files. However, while inferencing the audio output through Waveglow the audio is not clear. There is too much noise. Where as it was generating a perfect clear audio when I tested the model couple of months back. While training the model I stopped the training at error rate 0.18 as the model was overfitting.

hparams.batch_size = 20 
hparams.epochs = 500 

hparams.p_attention_dropout=0.4
hparams.p_decoder_dropout=0.1
hparams.decay_start = 15000         # wait till decay_start to start decaying learning rate
hparams.A_ = 5e-4                   # Start/Max Learning Rate
hparams.B_ = 8000                   # Decay Rate
hparams.C_ = 0                      # Shift learning rate equation by this value
hparams.min_learning_rate = 1e-6    # Min Learning Rate
generate_mels = True # Don't change
hparams.show_alignments = True
alignment_graph_height = 600
alignment_graph_width = 1000
hparams.load_mel_from_disk = True
hasankh17 commented 3 years ago

image