mirror of
https://github.com/thorstenMueller/Thorsten-Voice.git
synced 2024-11-28 19:03:15 +01:00
120 lines
4.0 KiB
Python
120 lines
4.0 KiB
Python
|
# This script generates the folder structure for ljspeech-1.1 processing from mimic-recording-studio database
|
|||
|
|
|
|||
|
|
# Changelog
|
|||
|
|
# v1.0 - Initial release by Thorsten Müller (https://github.com/thorstenMueller/deep-learning-german-tts)
|
|||
|
|
# v1.1 - Great improvements by Peter Schmalfeldt (https://github.com/manifestinteractive)
|
|||
|
|
# - Audio processing with ffmpeg (mono and samplerate of 22.050 Hz)
|
|||
|
|
# - Much better Python coding than my original version
|
|||
|
|
# - Greater logging output to command line
|
|||
|
|
# - See more details here: https://gist.github.com/manifestinteractive/6fd9be62d0ede934d4e1171e5e751aba
|
|||
|
|
# - Thanks Peter, it's a great contribution :-)
|
|||
|
|
# v1.2 - Added choice for choosing which recording session should be exported as LJSpeech
|
|||
|
|
|
|||
|
|
import glob
|
|||
|
|
import sqlite3
|
|||
|
|
import ffmpeg
|
|||
|
|
import os
|
|||
|
|
|
|||
|
|
from shutil import copyfile
|
|||
|
|
from shutil import rmtree
|
|||
|
|
|
|||
|
|
# Setup Directory Data
|
|||
|
|
cwd = os.path.dirname(os.path.abspath(__file__))
|
|||
|
|
mrs_dir = os.path.join(cwd, os.pardir, "mimic-recording-studio")
|
|||
|
|
output_dir = os.path.join(cwd, "dataset")
|
|||
|
|
output_dir_audio = ""
|
|||
|
|
output_dir_audio_temp=""
|
|||
|
|
output_dir_speech = ""
|
|||
|
|
|
|||
|
|
# Create folders needed for ljspeech
|
|||
|
|
def create_folders():
|
|||
|
|
global output_dir
|
|||
|
|
global output_dir_audio
|
|||
|
|
global output_dir_audio_temp
|
|||
|
|
global output_dir_speech
|
|||
|
|
|
|||
|
|
print('→ Creating Dataset Folders')
|
|||
|
|
|
|||
|
|
output_dir_speech = os.path.join(output_dir, "LJSpeech-1.1")
|
|||
|
|
|
|||
|
|
# Delete existing folder if exists for clean run
|
|||
|
|
if os.path.exists(output_dir_speech):
|
|||
|
|
rmtree(output_dir_speech)
|
|||
|
|
|
|||
|
|
output_dir_audio = os.path.join(output_dir_speech, "wavs")
|
|||
|
|
output_dir_audio_temp = os.path.join(output_dir_speech, "temp")
|
|||
|
|
|
|||
|
|
# Create Clean Folders
|
|||
|
|
os.makedirs(output_dir_speech)
|
|||
|
|
os.makedirs(output_dir_audio)
|
|||
|
|
os.makedirs(output_dir_audio_temp)
|
|||
|
|
|
|||
|
|
def convert_audio():
|
|||
|
|
global output_dir_audio
|
|||
|
|
global output_dir_audio_temp
|
|||
|
|
|
|||
|
|
recordings = len([name for name in os.listdir(output_dir_audio_temp) if os.path.isfile(os.path.join(output_dir_audio_temp,name))])
|
|||
|
|
|
|||
|
|
print('→ Converting %s Audio Files to 22050 Hz, 16 Bit, Mono\n' % "{:,}".format(recordings))
|
|||
|
|
|
|||
|
|
for idx, wav in enumerate(glob.glob(os.path.join(output_dir_audio_temp, "*.wav"))):
|
|||
|
|
|
|||
|
|
percent = (idx + 1) / recordings
|
|||
|
|
|
|||
|
|
print('› \033[96m%s\033[0m \033[2m%s / %s (%s)\033[0m ' % (os.path.basename(wav), "{:,}".format((idx + 1)), "{:,}".format(recordings), "{:.0%}".format(percent)))
|
|||
|
|
|
|||
|
|
# Convert WAV file to required format
|
|||
|
|
(ffmpeg
|
|||
|
|
.input(wav)
|
|||
|
|
.output(os.path.join(output_dir_audio, os.path.basename(wav)), acodec='pcm_s16le', ac=1, ar=22050, loglevel='error')
|
|||
|
|
.overwrite_output()
|
|||
|
|
.run(capture_stdout=True)
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
# Delete Temp File
|
|||
|
|
os.remove(wav)
|
|||
|
|
|
|||
|
|
# Remove Temp Folder
|
|||
|
|
rmtree(output_dir_audio_temp)
|
|||
|
|
|
|||
|
|
def create_meta_data():
|
|||
|
|
print('→ Creating META Data')
|
|||
|
|
|
|||
|
|
conn = sqlite3.connect(os.path.join(mrs_dir, "backend", "db", "mimicstudio.db"))
|
|||
|
|
c = conn.cursor()
|
|||
|
|
|
|||
|
|
# Create metadata.csv for ljspeech
|
|||
|
|
metadata = open(os.path.join(output_dir_speech, "metadata.csv"), mode="w", encoding="utf8")
|
|||
|
|
|
|||
|
|
# List available recording sessions
|
|||
|
|
user_models = c.execute('SELECT uuid, user_name from usermodel ORDER BY created_date DESC').fetchall()
|
|||
|
|
user_id = user_models[0][0]
|
|||
|
|
|
|||
|
|
for row in user_models:
|
|||
|
|
print(row[0] + ' -> ' + row[1])
|
|||
|
|
|
|||
|
|
user_answer = input('Please choose ID of recording session to export (default is newest session) [' + user_id + ']: ')
|
|||
|
|
|
|||
|
|
if user_answer:
|
|||
|
|
user_id = user_answer
|
|||
|
|
|
|||
|
|
|
|||
|
|
for row in c.execute('SELECT audio_id, prompt, lower(prompt) FROM audiomodel WHERE user_id = "' + user_id + '" ORDER BY length(prompt)'):
|
|||
|
|
metadata.write(row[0] + "|" + row[1] + "|" + row[2] + "\n")
|
|||
|
|
copyfile(os.path.join(mrs_dir, "backend", "audio_files", user_id, row[0] + ".wav"), os.path.join(output_dir_audio_temp, row[0] + ".wav"))
|
|||
|
|
|
|||
|
|
metadata.close()
|
|||
|
|
conn.close()
|
|||
|
|
|
|||
|
|
def main():
|
|||
|
|
print('\n\033[48;5;22m MRS to LJ Speech Processor \033[0m\n')
|
|||
|
|
|
|||
|
|
create_folders()
|
|||
|
|
create_meta_data()
|
|||
|
|
convert_audio()
|
|||
|
|
|
|||
|
|
print('\n\033[38;5;86;1m✔\033[0m COMPLETE【ツ】\n')
|
|||
|
|
|
|||
|
|
if __name__ == '__main__':
|
|||
|
|
main()
|