About loss and sparse_categorical_accuracy

[azraelkuan]

Hi, I use this repo to train my own dataset, but i found that the sparse_categorical_accuracy increase very slowly

how about your training process?

[azraelkuan]

my step:

1. find wav_dir -iname *.wav | sort -R | tr "\n" " " | xargs -d " " -I{} sox {} -r 16000 -b 16 -c 1 -e signed-integer -t raw - > input.s16
2. ./dump_data input.s16 features.f32 pcm.s16
3. python train_lpcnet.py

[azraelkuan]

thanks for your work, in my experience, when the loss is around 2, the generate wav is very good.
this is the spectrum of the generated wav

[HallidayReadyOne]

Hi, @azraelkuan, the audio mentioned above is generated using features extracted from the original audio or predicted features?