data/resample.py

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.