File size: 2,104 Bytes
39da493 | 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 | #!/usr/bin/env python3
"""
Extract audio from Nigerian Common Voice parquet files.
"""
import os
import sys
from pathlib import Path
try:
import pandas as pd
from datasets import load_dataset
import soundfile as sf
except ImportError:
print("Installing required packages...")
os.system("pip install pandas datasets soundfile pyarrow")
import pandas as pd
from datasets import load_dataset
import soundfile as sf
BASE_DIR = Path.home() / "voice-training"
DATASETS_DIR = BASE_DIR / "datasets" / "nigerian_cv"
OUTPUT_DIR = BASE_DIR / "prepared_data"
LANGUAGES = ["yoruba", "hausa", "igbo", "english"]
def extract_language(lang: str):
"""Extract audio files for a language."""
lang_dir = DATASETS_DIR / lang
output_dir = OUTPUT_DIR / lang
output_dir.mkdir(parents=True, exist_ok=True)
print(f"\n=== Extracting {lang.upper()} ===")
for split in ["train", "validation", "test"]:
parquet_file = lang_dir / f"{split}-00000-of-00001.parquet"
if not parquet_file.exists():
print(f" {split}: not found")
continue
print(f" Processing {split}...")
try:
# Load parquet
df = pd.read_parquet(parquet_file)
print(f" Found {len(df)} samples")
# Check columns
print(f" Columns: {list(df.columns)}")
# Extract first few samples
for idx in range(min(5, len(df))):
row = df.iloc[idx]
print(f" Sample {idx}: {row.get('sentence', 'N/A')[:50]}...")
except Exception as e:
print(f" Error: {e}")
def main():
print("=== Extracting Nigerian Common Voice Audio ===")
print(f"Input: {DATASETS_DIR}")
print(f"Output: {OUTPUT_DIR}")
for lang in LANGUAGES:
if (DATASETS_DIR / lang).exists():
extract_language(lang)
else:
print(f"\n{lang}: directory not found")
print("\n=== Extraction complete ===")
if __name__ == "__main__":
main()
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