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f898cfc | 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 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 | """Command-line dataset generator.
Examples
--------
Free Piper TTS (no key)::
python generate.py --out output --push-hf-repo user/hey-android
Google Cloud TTS + Edge Impulse upload::
python generate.py --gcp-api-key "$GCP_TTS_API_KEY" \\
--edge-impulse-api-key "$EDGE_IMPULSE_API_KEY"
"""
from __future__ import annotations
import argparse
import os
from src import edge_impulse
from src.backends import select_backend
from src.builder import build_dataset
from src.config import DEFAULT_UNKNOWN_PHRASES, DEFAULT_WAKE_PHRASES, DatasetConfig
from src.hf_export import export_hf_dataset, push_to_hub
def _read_lines(path: str | None, fallback: list[str]) -> list[str]:
if not path:
return list(fallback)
lines = [ln.strip() for ln in open(path, encoding="utf-8") if ln.strip()]
return lines or list(fallback)
def main() -> None:
p = argparse.ArgumentParser(description="Generate a wake-word dataset (GCP TTS or free Piper).")
p.add_argument("--out", default="output")
p.add_argument("--hf-out", default="hf_dataset")
p.add_argument("--dataset-name", default="hey_android")
p.add_argument("--wake-label", default="hey_android")
p.add_argument("--wake-phrases-file", default=None)
p.add_argument("--unknown-phrases-file", default=None)
p.add_argument("--gcp-api-key", default=os.environ.get("GCP_TTS_API_KEY", ""))
p.add_argument("--base-repeats", type=int, default=1)
p.add_argument("--augmentations", type=int, default=8)
p.add_argument("--background-noise", type=int, default=200)
p.add_argument("--max-voices", type=int, default=7)
p.add_argument("--test-ratio", type=float, default=0.2)
p.add_argument("--push-hf-repo", default=None, help="e.g. username/dataset-name")
p.add_argument("--hf-token", default=os.environ.get("HF_TOKEN", ""))
p.add_argument("--hf-private", action="store_true")
p.add_argument("--edge-impulse-api-key", default=os.environ.get("EDGE_IMPULSE_API_KEY", ""))
p.add_argument("--ei-allow-duplicates", action="store_true")
args = p.parse_args()
backend = select_backend(
gcp_api_key=args.gcp_api_key,
language_prefixes=["en", "nl", "de", "fr", "es"],
max_gcp_voices_per_locale=3,
max_piper_voices=args.max_voices,
sample_rate_hz=16000,
)
print(f"Backend: {backend.source}")
config = DatasetConfig(
out_dir=args.out,
dataset_name=args.dataset_name,
wake_label=args.wake_label,
wake_phrases=_read_lines(args.wake_phrases_file, DEFAULT_WAKE_PHRASES),
unknown_phrases=_read_lines(args.unknown_phrases_file, DEFAULT_UNKNOWN_PHRASES),
base_repeats_per_phrase_per_voice=args.base_repeats,
augmentations_per_speech_clip=args.augmentations,
background_noise_samples=args.background_noise,
max_piper_voices=args.max_voices,
test_ratio=args.test_ratio,
)
result = build_dataset(config, backend)
repo_id = args.push_hf_repo or "your-username/your-dataset"
hf_dir = export_hf_dataset(config, result, args.hf_out, repo_id=repo_id)
print(f"Hugging Face dataset folder: {hf_dir}")
if args.push_hf_repo and args.hf_token:
url = push_to_hub(hf_dir, args.push_hf_repo, args.hf_token, private=args.hf_private)
print(f"Pushed dataset: {url}")
if args.edge_impulse_api_key:
ei_result = edge_impulse.upload_dataset(
dataset_dir=args.out,
api_key=args.edge_impulse_api_key,
allow_duplicates=args.ei_allow_duplicates,
)
print(f"Edge Impulse: {ei_result.uploaded} uploaded, {ei_result.failed} failed.")
if __name__ == "__main__":
main()
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