| """Minimal usage example for hv-contour. |
| |
| Synthesizes three whistles with prescribed contours, encodes them, and |
| prints pairwise similarities. |
| """ |
| import math |
| import os |
| import wave |
| from array import array |
|
|
| from hv_contour import HVContour |
|
|
|
|
| OUTDIR = "./hv_contour_example" |
|
|
|
|
| def _write_wav(path: str, samples, sr: int = 16000) -> None: |
| ints = array( |
| "h", |
| (max(-32768, min(32767, int(x * 32767))) for x in samples), |
| ) |
| with wave.open(path, "wb") as w: |
| w.setnchannels(1) |
| w.setsampwidth(2) |
| w.setframerate(sr) |
| w.writeframes(ints.tobytes()) |
|
|
|
|
| def _whistle(contour: str, f0: float, f1: float, |
| dur_ms: int = 600, sr: int = 16000): |
| n = int(sr * dur_ms / 1000) |
| dur_s = dur_ms / 1000.0 |
| out = [] |
| for i in range(n): |
| t = i / n |
| if contour == "R": |
| f = f0 + (f1 - f0) * t |
| elif contour == "F": |
| f = f0 + (f1 - f0) * t |
| elif contour == "W": |
| peak = max(f0, f1) * 1.2 |
| f = (f0 + (peak - f0) * (t / 0.5) if t < 0.5 |
| else peak - (peak - f1) * ((t - 0.5) / 0.5)) |
| elif contour == "U": |
| trough = min(f0, f1) * 0.8 |
| f = (f0 - (f0 - trough) * (t / 0.5) if t < 0.5 |
| else trough + (f1 - trough) * ((t - 0.5) / 0.5)) |
| else: |
| f = f0 |
| phase = 2 * math.pi * f * (i / sr) |
| env = math.sin(math.pi * i / n) ** 0.5 |
| out.append(0.5 * env * math.sin(phase)) |
| return out |
|
|
|
|
| def main() -> None: |
| os.makedirs(OUTDIR, exist_ok=True) |
|
|
| |
| samples = [ |
| ("up", _whistle("R", 800, 1600)), |
| ("down", _whistle("F", 1600, 800)), |
| ("flat", _whistle("S", 1200, 1200)), |
| ] |
| paths = [] |
| for name, sig in samples: |
| p = os.path.join(OUTDIR, f"{name}.wav") |
| _write_wav(p, sig) |
| paths.append(p) |
|
|
| model = HVContour(dim=50000, seed=42) |
|
|
| print("=" * 60) |
| print("hv-contour") |
| print("=" * 60) |
| print() |
|
|
| encoded = [] |
| for path in paths: |
| contours, hv = model.encode_file(path) |
| tokens = [c.token for c in contours] |
| print(f" {os.path.basename(path):<12} " |
| f"tokens = {' '.join(tokens):<10} " |
| f"dim = {hv.dim} ones = {sum(hv.bits)}") |
| encoded.append((os.path.basename(path), hv)) |
| print() |
|
|
| print("=" * 60) |
| print("Pairwise similarity") |
| print("=" * 60) |
| print(f" {'':<12}" + "".join(f"{n:>10}" for n, _ in encoded)) |
| for name_a, hv_a in encoded: |
| row = f" {name_a:<12}" |
| for name_b, hv_b in encoded: |
| row += f"{hv_a.similarity(hv_b):>10.3f}" |
| print(row) |
| print() |
|
|
| print("=" * 60) |
| print("Cross-check the audio round-trip") |
| print("=" * 60) |
| for name, _ in encoded: |
| print(f" synth {name:<6} -> extracted " |
| f"{' '.join(c.token for c in model.encode_file(os.path.join(OUTDIR, f'{name}.wav'))[0])}") |
| print() |
|
|
|
|
| if __name__ == "__main__": |
| main() |
