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import librosa
import soundfile as sf
import os
import concurrent.futures
def resample_audio(file_path, target_directory, target_sr=24000):
# Load the audio file
audio, sr = librosa.load(file_path, sr=None)
# Resample the audio
if sr != target_sr:
audio_resampled = librosa.resample(audio, orig_sr=sr, target_sr=target_sr)
# Determine the new file path
target_file_path = os.path.join(target_directory, os.path.basename(file_path))
# Export the resampled audio
sf.write(target_file_path, audio_resampled, target_sr)
def resample_audio_multithreaded(source_folder, target_folder, target_sr=24000):
if not os.path.exists(target_folder):
os.makedirs(target_folder)
# Create a list of tasks
tasks = []
for root, dirs, files in os.walk(source_folder):
for file in files:
if file.endswith(".wav"):
source_file_path = os.path.join(root, file)
relative_path = os.path.relpath(root, source_folder)
target_directory = os.path.join(target_folder, relative_path)
if not os.path.exists(target_directory):
os.makedirs(target_directory)
tasks.append((source_file_path, target_directory))
# Process the tasks in parallel using multiple threads
with concurrent.futures.ThreadPoolExecutor() as executor:
futures = [executor.submit(resample_audio, task[0], task[1], target_sr) for task in tasks]
concurrent.futures.wait(futures)
if __name__ == '__main__':
# Example usage
resample_audio_multithreaded("fsd2018", 'fsd2018_24k')
# Note: The actual execution of this code is not possible here due to the lack of access to the user's filesystem.
# The user should run this script on their local machine.
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