mirror of
https://github.com/thorstenMueller/Thorsten-Voice.git
synced 2024-11-21 15:33:10 +01:00
49 lines
1.9 KiB
Python
49 lines
1.9 KiB
Python
# This script removes recordings from an ljspeech file/directory structured dataset based on CSV file from "getDatasetSpeechRate"
|
|
# Writte by Thorsten Müller (deep-learning-german@gmx.net) and provided without any warranty.
|
|
# https://github.com/thorstenMueller/deep-learning-german-tts/
|
|
# https://twitter.com/ThorstenVoice
|
|
|
|
# Changelog:
|
|
# v0.1 - 26.09.2021 - Initial version
|
|
|
|
import os
|
|
import csv
|
|
import shutil
|
|
|
|
dataset_dir = "/Users/thorsten/Downloads/thorsten-export-20210909/" # Directory where metadata.csv is in
|
|
subfolder_removed = "___removed"
|
|
in_csv_file = os.path.join(dataset_dir,"speech_rate_report.csv")
|
|
to_remove = []
|
|
|
|
# Open metadata.csv file
|
|
with open(os.path.join(dataset_dir,in_csv_file)) as csvfile:
|
|
reader = csv.reader(csvfile, delimiter=';')
|
|
for row in reader:
|
|
if row[4] == "yes":
|
|
# Recording in that row should be removed from dataset
|
|
to_remove.append(row[0])
|
|
print("Recording " + row[0] + " will be removed from dataset.")
|
|
|
|
print("\n" + str(len(to_remove)) + " recordings has been marked for deletion.")
|
|
|
|
if len(to_remove) > 0:
|
|
|
|
metadata_cleaned = open(os.path.join(dataset_dir,"metadata_cleaned.csv"),"w")
|
|
|
|
# Create new subdirectory for removed wav files
|
|
removed_dir = os.path.join(dataset_dir,subfolder_removed)
|
|
if not os.path.exists(removed_dir):
|
|
os.makedirs(removed_dir)
|
|
|
|
# Remove lines from metadata.csv and move wav files to new subdirectory
|
|
with open(os.path.join(dataset_dir,"metadata.csv")) as csvfile:
|
|
reader = csv.reader(csvfile, delimiter='|')
|
|
for row in reader:
|
|
if (row[0] + ".wav") not in to_remove:
|
|
metadata_cleaned.write(row[0] + "|" + row[1] + "|" + row[2] + "\n")
|
|
else:
|
|
# Move recording to new subfolder
|
|
shutil.move(os.path.join(dataset_dir,"wavs",row[0] + ".wav"),removed_dir)
|
|
|
|
metadata_cleaned.close()
|