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I want to train this model in vctk dataset, but i don't know how to generate the json files provided by you? #5
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Hi @Georgehappy1. I'll add some instructions to the README soon. The format of the json file is:
The following steps should get you most of the way to generating your own: from pathlib import Path
import librosa
from tqdm import tqdm
import json
metadata = []
data_path = Path("path/to/VCTK-Corpus/")
for path in tqdm(list(data_path.rglob("*.wav"))):
in_path = path.relative_to(data_path).with_suffix("")
duration = round(librosa.get_duration(filename=path), 2)
out_path = Path("train") / in_path.parts[-2] / in_path.stem
metadata.append([str(in_path), 0, duration, str(out_path)]) That'll take a little time to run. Then you can optionally split train_path = Path("datasets/VCTK")
train_path.mkdir(parents=True, exist_ok=True)
with open(train_path / "train.json", "w") as file:
json.dump(metadata, file, indent=4) Let me know if that works for you. Also, please share your results if you get the training working! |
@bshall Thank you for your reply! I will follow your instructions to train the model in vctk. I will show the results here once results come out. |
No problem @Georgehappy1. Also, I forgot to mention that you'll have to add a new config file dataset:
dataset: VCTK
language: english
path: VCTK
n_speakers: 109 Then when you run any of the scripts you'll use the flag |
@Georgehappy1, just checking if you ever managed to get the training on VCTK working? |
yes, i have got the results. Thank u for ur help. Later i will upload the demo link here. |
@Georgehappy1, fantastic! Looking forward to hearing the results. If you'd like to contribute your model and dataset splits, I'd be very happy to take a look at a pull request. |
@bshall hi, the demo link is here https://drive.google.com/drive/folders/1c1VQFzC2zf25OXZPkNTiwlaHHZOREBGe?usp=sharing |
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