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6351b36 | 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 | #!/usr/bin/env python3
"""Extract TitaNet embeddings using NVIDIA NeMo.
Model: nvidia/speakerverification_en_titanet_large (supervised, 192-dim)
Install: pip install nemo_toolkit[asr]
"""
import argparse
import torch
import numpy as np
from extraction_utils import load_audio, extract_all
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--device", default="cuda" if torch.cuda.is_available() else "cpu")
parser.add_argument("--base-dir", default=None)
parser.add_argument("--output-dir", default=None)
args = parser.parse_args()
import nemo.collections.asr as nemo_asr
print(f"Loading TitaNet on {args.device}...")
model = nemo_asr.models.EncDecSpeakerLabelModel.from_pretrained(
"nvidia/speakerverification_en_titanet_large"
)
model = model.to(args.device)
model.eval()
def model_fn(audio_path):
# NeMo's get_embedding works directly with file paths
emb = model.get_embedding(str(audio_path))
return emb.squeeze().cpu().numpy()
extract_all(model_fn, "titanet", args.base_dir, args.output_dir)
if __name__ == "__main__":
main()
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