File size: 2,965 Bytes
4d3248c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 | import json
import random
import os
import shutil
from pathlib import Path
# --- CONFIG ---
input_manifest = "thai_processed_data/manifest_clustered.jsonl"
output_dir = "check_clusters" # Where we will copy files for you to listen
samples_to_check = 5 # How many groups to check
files_per_group = 3 # How many audio files per group to copy
# --------------
def main():
print(f"Reading {input_manifest}...")
# 1. Load and Group Data
clusters = {}
with open(input_manifest, 'r', encoding='utf-8') as f:
for line in f:
data = json.loads(line)
speaker_id = data['speaker']
audio_path = data['audio_path']
if speaker_id not in clusters:
clusters[speaker_id] = []
clusters[speaker_id].append(audio_path)
# Filter for groups that actually have pairs (size > 1)
valid_clusters = [k for k, v in clusters.items() if len(v) >= 2]
print(f"Found {len(clusters)} total groups.")
print(f"Found {len(valid_clusters)} groups with at least 2 files (valid for pairing).")
if not valid_clusters:
print("Error: No valid clusters found! Did you run the clustering script?")
return
# 2. Pick Random Groups to Audit
selected_speakers = random.sample(valid_clusters, min(samples_to_check, len(valid_clusters)))
# 3. Copy Files for Manual Checking
if os.path.exists(output_dir):
shutil.rmtree(output_dir)
os.makedirs(output_dir)
print(f"\n--- GENERATING SAMPLES IN '{output_dir}' ---")
for i, spk_id in enumerate(selected_speakers):
# Create a subfolder for this speaker
folder_name = f"Group_{i+1}_{spk_id}"
folder_path = os.path.join(output_dir, folder_name)
os.makedirs(folder_path)
# Get random files from this speaker
files = clusters[spk_id]
selected_files = random.sample(files, min(files_per_group, len(files)))
print(f"\nGroup {i+1} (ID: {spk_id}):")
for src_path in selected_files:
# Handle path logic (in case paths are relative)
if not os.path.exists(src_path):
# Try prepending 'thaitts_emilia_dataset' or common roots if not found
# But usually manifest paths are relative to where you ran preprocess
print(f" [WARNING] File not found: {src_path}")
continue
file_name = os.path.basename(src_path)
dst_path = os.path.join(folder_path, file_name)
shutil.copy2(src_path, dst_path)
print(f" - Copied: {file_name}")
print(f"\nDONE! Go open the folder '{output_dir}' and listen to the files.")
print("If files in 'Group_1' sound like the same person, the clustering worked!")
if __name__ == "__main__":
main() |