File size: 4,944 Bytes
8c2913a | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 | """Extract an auditable prosody profile from a GLaDOS reference clip."""
import argparse
import json
import subprocess
from pathlib import Path
import librosa
import numpy as np
import soundfile as sf
def finite_percentiles(values, percentiles):
values = np.asarray(values)
values = values[np.isfinite(values)]
if len(values) == 0:
return [None for _ in percentiles]
return [round(float(x), 3) for x in np.percentile(values, percentiles)]
def analyze(path: Path, text: str | None = None) -> dict:
audio, sr = librosa.load(str(path), sr=16000, mono=True)
duration = len(audio) / sr
hop = 160
f0, voiced, _ = librosa.pyin(
audio,
fmin=65,
fmax=500,
sr=sr,
frame_length=1024,
hop_length=hop,
)
rms = librosa.feature.rms(y=audio, frame_length=1024, hop_length=hop)[0]
rms_db = librosa.amplitude_to_db(np.maximum(rms, 1e-8), ref=1.0)
centroid = librosa.feature.spectral_centroid(y=audio, sr=sr, hop_length=hop)[0]
flatness = librosa.feature.spectral_flatness(y=audio, hop_length=hop)[0]
intervals = librosa.effects.split(audio, top_db=32, frame_length=1024, hop_length=hop)
pauses = []
for left, right in zip(intervals, intervals[1:]):
start = right[0] / sr
end = left[1] / sr
if start - end >= 0.08:
pauses.append({"start": round(end, 3), "end": round(start, 3), "duration": round(start - end, 3)})
voiced_f0 = f0[np.isfinite(f0) & voiced]
times = np.arange(len(f0)) * hop / sr
valid = np.isfinite(f0)
contour_times = np.linspace(0, duration, 20)
if valid.any():
contour_f0 = np.interp(contour_times, times[valid], f0[valid])
else:
contour_f0 = np.full_like(contour_times, np.nan)
energy_times = np.arange(len(rms_db)) * hop / sr
contour_energy = np.interp(contour_times, energy_times, rms_db)
profile = {
"file": str(path),
"sample_rate_for_analysis": sr,
"duration_sec": round(duration, 3),
"voiced_fraction": round(float(np.mean(voiced)), 3),
"pause_map": pauses,
"f0_hz": {
"median": finite_percentiles(voiced_f0, [50])[0],
"p10_p90": finite_percentiles(voiced_f0, [10, 90]),
"contour_20_points": [round(float(x), 2) for x in contour_f0],
},
"energy_db": {
"p10_p50_p90": finite_percentiles(rms_db, [10, 50, 90]),
"dynamic_range_db": round(float(np.percentile(rms_db, 90) - np.percentile(rms_db, 10)), 3),
"contour_20_points": [round(float(x), 2) for x in contour_energy],
},
"timbral_proxies": {
"spectral_centroid_hz_median": finite_percentiles(centroid, [50])[0],
"spectral_flatness_median": finite_percentiles(flatness, [50])[0],
},
"interpretation": {
"target": "soft, close-mic, restrained mechanical delivery",
"sarcasm": "low-to-moderate pitch movement with deliberate clause-final timing",
"smile": "look for local energy/brightness lift around emphasized words; do not synthesize a broad cheerful smile",
},
}
if text:
profile["text"] = text
profile["text_chars_per_sec"] = round(len(text) / duration, 3)
return profile
def warp_duration(source: Path, reference: Path, output: Path) -> None:
reference_duration = librosa.get_duration(path=str(reference))
output.parent.mkdir(parents=True, exist_ok=True)
subprocess.run(
[
"rubberband",
"-3",
"-D",
f"{reference_duration:.6f}",
str(source),
str(output),
],
check=True,
stdout=subprocess.DEVNULL,
stderr=subprocess.DEVNULL,
)
audio, sr = sf.read(output, always_2d=False)
peak = float(np.max(np.abs(audio)))
if peak > 0.95:
audio = audio * (0.95 / peak)
sf.write(output, audio, sr, subtype="PCM_16")
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument("--reference", type=Path, required=True)
parser.add_argument("--source", type=Path)
parser.add_argument("--text")
parser.add_argument("--output-profile", type=Path, required=True)
parser.add_argument("--warp-source", type=Path)
args = parser.parse_args()
profile = analyze(args.reference, args.text)
if args.source:
profile["source"] = analyze(args.source, args.text)
args.output_profile.parent.mkdir(parents=True, exist_ok=True)
args.output_profile.write_text(json.dumps(profile, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
if args.warp_source:
if not args.source:
raise SystemExit("--warp-source requires --source")
warp_duration(args.source, args.reference, args.warp_source)
print(json.dumps(profile, ensure_ascii=False, indent=2))
if __name__ == "__main__":
main()
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