You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi, I ran the following testing code to convert .wav -> mel using librosa and then Univnet with pretrained checkpoint to do the inverse but the results were extremely bad. Can you point out what I'm doing wrong? The input file is clean, US english speech. arguments: -p ./chkpt/univ_c16_0292.pt -c config/default_c16.yaml -i /Users/kelseyd/Documents/train/TF -o ./out
for filename in tqdm.tqdm(glob.glob(os.path.join(args.input_folder, '*.wav'))):
y, sr = librosa.load(filename,sr=24000)
mel=librosa.feature.melspectrogram(y=y, sr=sr, n_fft=1024, n_mels=100, fmin=0, fmax=12000)
mel = torch.from_numpy(mel)
Hi, I ran the following testing code to convert .wav -> mel using librosa and then Univnet with pretrained checkpoint to do the inverse but the results were extremely bad. Can you point out what I'm doing wrong? The input file is clean, US english speech. arguments: -p ./chkpt/univ_c16_0292.pt -c config/default_c16.yaml -i /Users/kelseyd/Documents/train/TF -o ./out
for filename in tqdm.tqdm(glob.glob(os.path.join(args.input_folder, '*.wav'))):
y, sr = librosa.load(filename,sr=24000)
mel=librosa.feature.melspectrogram(y=y, sr=sr, n_fft=1024, n_mels=100, fmin=0, fmax=12000)
mel = torch.from_numpy(mel)
The text was updated successfully, but these errors were encountered: