{ "contract": { "script_sha256": "4b97e676eb21f79c9bfaaa665866881c3faaf40c1e1a895bc2f9bbc27b0a63fa", "script_text": "\"\"\"D採用前の短時間合成制御測定。自然音声/MOS/テストを追加しない。\"\"\"\nimport os\nfor k in ('OMP_NUM_THREADS','OPENBLAS_NUM_THREADS','MKL_NUM_THREADS'): os.environ[k]='1'\nfrom pathlib import Path\nimport sys, json, hashlib, importlib.util, importlib, traceback, datetime, platform\nfrom dataclasses import replace\nimport numpy as np\nROOT=Path(__file__).resolve().parent/'vocoder'\nsys.path.insert(0,str(ROOT))\nfrom vocoderbench import hnm_control as control, hnm_synthesis as base\nOUT=ROOT/'runs/adoption-controls-synthetic'\nOUT.mkdir(parents=True,exist_ok=True)\ndef sha(p): return hashlib.sha256(Path(p).read_bytes()).hexdigest()\ndef ah(a): return hashlib.sha256(np.ascontiguousarray(a).tobytes()).hexdigest()\npkg=ROOT.parent/'noise_candidates/D'\nspec=importlib.util.spec_from_file_location('_adoption_D',pkg/'__init__.py',submodule_search_locations=[str(pkg)])\nm=importlib.util.module_from_spec(spec);sys.modules[spec.name]=m;spec.loader.exec_module(m)\nd=importlib.import_module('_adoption_D.hnm_synthesis')\nsource=Path(__file__).read_bytes().decode('utf-8')\ncontract={'script_sha256':sha(__file__),'script_text':source,'baseline_files':{p.name:sha(p) for p in (ROOT/'vocoderbench').glob('hnm*.py')},'candidate_files':{p.name:sha(p) for p in pkg.glob('*.py')},'python':platform.python_version(),'numpy':np.__version__,'seeds':list(range(8)),'sample_rate':16000,'duration':0.5,'planned_outputs':192,'scope':'_noise only; harmonic synthesis unchanged; no MOS','criteria':{'finite':True,'length':'exact parameter n_samples','silence':'exact zero where interpolated target power is zero','gain_relative_max_error':1e-12,'pitch_noise_max_error':0.0,'normalized_analytic_expected_power_absolute_error':1e-12,'empirical_power':'descriptive only; eight seeds do not guarantee convergence, especially narrow bands'}}\n(OUT/'contract.json').write_text(json.dumps(contract,ensure_ascii=False,indent=2),encoding='utf-8')\np=control.make_synthetic_parameters(f0_hz=140,duration=.5,noise_fraction=1)\nflat=p; grid=p.frequency_grid\ncases={'zero_noise':replace(p,noise_psd=np.zeros_like(p.noise_psd)),'flat':p}\nfor name,shape in [('dc_concentrated',np.exp(-grid/80)),('nyquist_concentrated',np.exp(-(8000-grid)/80))]:\n shape=shape/np.trapezoid(shape,grid)*np.trapezoid(p.noise_psd[0],grid)\n cases[name]=replace(p,noise_psd=np.tile(shape,(len(p.frame_times),1)))\nfor name,mask in [('sound_to_silence',p.frame_times<.25),('short_burst',(p.frame_times>=.245)&(p.frame_times<=.255))]:\n cases[name]=replace(p,noise_psd=p.noise_psd*mask[:,None])\nfor name,kwargs in [('gain_minus6',{'gain_db':-6}),('gain_plus6',{'gain_db':6}),('time_half',{'time_scale':.5}),('time_double',{'time_scale':2}),('pitch_minus12',{'pitch_semitones':-12}),('pitch_plus12',{'pitch_semitones':12})]: cases[name]=control.edit_parameters(p,**kwargs)\nrows=[]; waves={}; analytic=[]\nfor name,q in cases.items():\n powers=np.trapezoid(q.noise_psd,q.frequency_grid,axis=1)\n target=np.interp(np.arange(q.n_samples)/q.sample_rate,q.frame_times,powers)\n for method,module in [('v2',base),('D',d)]:\n active=np.flatnonzero(powers>0)\n if len(active):\n nfft=512; fftgrid=np.fft.rfftfreq(nfft,1/q.sample_rate);df=q.sample_rate/nfft\n psd=np.interp(fftgrid,q.frequency_grid,q.noise_psd[active[0]]/powers[active[0]])\n endweight=1 if method=='v2' else .5\n den=df*(psd[1:-1].sum()+endweight*(psd[0]+psd[-1]));norm=psd/den\n # Parseval: endpoint variances + twice interior complex energies, divided by N^2.\n endpoint_var=endweight*norm[[0,-1]]*q.sample_rate*nfft\n interior_complex_energy=norm[1:-1]*q.sample_rate*nfft/2\n expected=float((endpoint_var.sum()+2*interior_complex_energy.sum())/nfft**2)\n analytic.append({'case':name,'method':method,'normalized_expected_power':expected,'absolute_error':abs(expected-1),'endpoint_expected_power_fraction':float(endpoint_var.sum()/nfft**2),'target_power_mean':float(target.mean())})\n for seed in range(8):\n row={'case':name,'method':method,'seed':seed}\n try:\n y=module._noise(q,seed);waves[(name,method,seed)]=y\n spectrum=np.abs(np.fft.rfft(y))**2;freq=np.fft.rfftfreq(len(y),1/q.sample_rate);total=float(spectrum.sum())\n row.update(status='measured',waveform_float64_sha256=ah(y),n_samples=len(y),expected_n_samples=q.n_samples,finite=bool(np.isfinite(y).all()),peak=float(np.max(np.abs(y))),power=float(np.mean(y*y)),target_power_mean=float(target.mean()),power_ratio=float(np.mean(y*y)/target.mean()) if target.mean()>0 else None,zero_target_samples=int((target==0).sum()),zero_target_max_abs=float(np.max(np.abs(y[target==0]))) if np.any(target==0) else None,low_200hz_energy_fraction=float(spectrum[freq<200].sum()/total) if total else None,high_7800hz_energy_fraction=float(spectrum[freq>7800].sum()/total) if total else None)\n if name.startswith('gain_'):\n gain=10**((-6 if name=='gain_minus6' else 6)/20);reference=waves[('flat',method,seed)]*gain\n row['gain_relative_max_error']=float(np.max(np.abs(y-reference))/max(np.max(np.abs(reference)),1e-30))\n if name.startswith('pitch_'): row['pitch_noise_max_error']=float(np.max(np.abs(y-waves[('flat',method,seed)])))\n row['criteria_pass']=bool(row['finite'] and len(y)==q.n_samples and row.get('zero_target_max_abs',0) in (None,0) and row.get('gain_relative_max_error',0)<=1e-12 and row.get('pitch_noise_max_error',0)==0)\n except Exception: row.update(status='failed',traceback=traceback.format_exc(),criteria_pass=False)\n rows.append(row)\nsummary={}\nfor name in cases:\n for method in ('v2','D'):\n rr=[r for r in rows if r['case']==name and r['method']==method and r['status']=='measured']\n ratios=[r['power_ratio'] for r in rr if r['power_ratio'] is not None]\n summary[name+'/'+method]={'outputs':len(rr),'all_criteria_pass':all(r['criteria_pass'] for r in rr),'mean_power_ratio':float(np.mean(ratios)) if ratios else None,'min_power_ratio':min(ratios) if ratios else None,'max_power_ratio':max(ratios) if ratios else None}\nfailures=sum(not r['criteria_pass'] for r in rows)+sum(r['absolute_error']>1e-12 for r in analytic)\nresult={'contract':contract,'finished_at':datetime.datetime.now(datetime.timezone.utc).isoformat(),'status':'completed' if not failures else 'criteria_failed','failures':failures,'rows':rows,'analytic':analytic,'summary':summary,'limitations':['Synthetic noise-only control measurement, not human quality or MOS calibration.','Finite eight-seed power variation is reported, not thresholded.','Pitch noise invariance is appropriate: independent noise PSD remains fixed under pitch edit.','Time edits verify exact output length and absence of nonfinite samples; do not imply identical stochastic waveforms.']}\n(OUT/'results.json').write_text(json.dumps(result,ensure_ascii=False,indent=2),encoding='utf-8')\nprint(json.dumps({'status':result['status'],'failures':failures,'outputs':len(rows),'analytic_cases':len(analytic),'summary':summary},ensure_ascii=False))\r\n", "baseline_files": { "hnm.py": "58f0378793b7433f80bf854972882298649799d8e3d0868674816e9bf6b63f74", "hnm_analysis.py": "3f45703667237333d76c4145c1513e4eb3342bd40f01a714c10303082440e26a", "hnm_control.py": "b2f5efbbb1e550569c231a08f12997d94b0bacb130bcc816fe6bd458b17a98bc", "hnm_diagnostics.py": "a3f47468d10db7e8040c78fc24546043b2eeae6b518f59da1f5904c674aae436", "hnm_parameters.py": "635bf222bac8ce41897c0977677e67be4366724f4239a9e85e153169fcea2cf0", "hnm_synthesis.py": "937721cd363f06afa3bf4c20c1ff182a8c337c4b19ac9f4b57314f6adea6b44c" }, "candidate_files": { "hnm.py": "58f0378793b7433f80bf854972882298649799d8e3d0868674816e9bf6b63f74", "hnm_analysis.py": "3f45703667237333d76c4145c1513e4eb3342bd40f01a714c10303082440e26a", "hnm_control.py": "b2f5efbbb1e550569c231a08f12997d94b0bacb130bcc816fe6bd458b17a98bc", "hnm_parameters.py": "635bf222bac8ce41897c0977677e67be4366724f4239a9e85e153169fcea2cf0", "hnm_synthesis.py": "a4fda7d4cfcaff18f49862b09f5c289d3947a8517f4885b35b281102d953ef0c", "__init__.py": "73738d70706824f85fdfac302306af505437a50b0ca4cdc68fd57aec211a308d" }, "python": "3.12.14", "numpy": "2.3.5", "seeds": [ 0, 1, 2, 3, 4, 5, 6, 7 ], "sample_rate": 16000, "duration": 0.5, "planned_outputs": 192, "scope": "_noise only; harmonic synthesis unchanged; no MOS", "criteria": { "finite": true, "length": "exact parameter n_samples", "silence": "exact zero where interpolated target power is zero", "gain_relative_max_error": 1e-12, "pitch_noise_max_error": 0.0, "normalized_analytic_expected_power_absolute_error": 1e-12, "empirical_power": "descriptive only; eight seeds do not guarantee convergence, especially narrow bands" } }, "finished_at": "2026-10-12T07:26:57.639281+00:00", "status": "completed", "failures": 0, "rows": [ { "case": "zero_noise", "method": "v2", "seed": 0, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "v2", "seed": 1, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "v2", "seed": 2, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "v2", "seed": 3, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "v2", "seed": 4, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "v2", "seed": 5, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "v2", "seed": 6, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "v2", "seed": 7, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "D", "seed": 0, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "D", "seed": 1, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "D", "seed": 2, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "D", "seed": 3, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "D", "seed": 4, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "D", "seed": 5, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "D", "seed": 6, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "zero_noise", "method": "D", "seed": 7, "status": "measured", "waveform_float64_sha256": "4f7988030a00d082fe445e00a2ac5dab502300ff1b80e8592dd569867b60ef74", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.0, "power": 0.0, "target_power_mean": 0.0, "power_ratio": null, "zero_target_samples": 8000, "zero_target_max_abs": 0.0, "low_200hz_energy_fraction": null, "high_7800hz_energy_fraction": null, "criteria_pass": true }, { "case": "flat", "method": "v2", "seed": 0, "status": "measured", "waveform_float64_sha256": "e8e5e5eb021766b70eef02faa34df8d7a077e1a72c739dcdab689e6ac7086d89", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.9336915518054576, "power": 0.06452933923613037, "target_power_mean": 0.06309573444801932, "power_ratio": 1.0227211046935687, "zero_target_samples": 0, "zero_target_max_abs": null, "low_200hz_energy_fraction": 0.026964411543415164, "high_7800hz_energy_fraction": 0.029269474126072875, "criteria_pass": true }, { "case": "flat", "method": "v2", "seed": 1, "status": "measured", "waveform_float64_sha256": "110b6a69e17501a3ac1945c515a222ff57180957b71874ab97d436514a86b44f", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.9831765408931392, "power": 0.0631353212767973, "target_power_mean": 0.06309573444801932, "power_ratio": 1.0006274089544136, "zero_target_samples": 0, "zero_target_max_abs": null, "low_200hz_energy_fraction": 0.023323152998413543, "high_7800hz_energy_fraction": 0.027947243266259324, "criteria_pass": true }, { "case": "flat", "method": "v2", "seed": 2, "status": "measured", "waveform_float64_sha256": "4ad2d50609346aa73ed59118bcf9bee6285a18ddc7d5b4009ba6674d9a802610", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.9301932691029352, "power": 0.06216513404216795, "target_power_mean": 0.06309573444801932, "power_ratio": 0.9852509775186461, "zero_target_samples": 0, "zero_target_max_abs": null, "low_200hz_energy_fraction": 0.028782049706293777, "high_7800hz_energy_fraction": 0.0237393384664301, "criteria_pass": true }, { "case": "flat", "method": "v2", "seed": 3, "status": "measured", "waveform_float64_sha256": "d928e13e0155ca178d655eef734390a0b40ecf7c25f386a42a4268919418c9c0", "n_samples": 8000, "expected_n_samples": 8000, "finite": true, "peak": 0.9376729470271186, "power": 0.06238842148182647, "target_power_mean": 0.06309573444801932, "power_ratio": 0.9887898449494148, "zero_target_samples": 0, "zero_target_max_abs": null, "low_200hz_energy_fraction": 0.023388645909865446, "high_7800hz_energy_fraction": 0.030870818805758576, "criteria_pass": true }, { "case": "flat", "method": "v2", "seed": 4, "status": "measured", "waveform_float64_sha256": "f7cf16734619bc27b58f4404bd3bdbf48fb0e0e53cc100b046beb50936759a40", 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"max_power_ratio": 1.0294272110497042 }, "short_burst/v2": { "outputs": 8, "all_criteria_pass": true, "mean_power_ratio": 1.0473211644284606, "min_power_ratio": 0.9181364962985197, "max_power_ratio": 1.3145026361780303 }, "short_burst/D": { "outputs": 8, "all_criteria_pass": true, "mean_power_ratio": 1.0480665957680184, "min_power_ratio": 0.9216271031576425, "max_power_ratio": 1.3140923666149238 }, "gain_minus6/v2": { "outputs": 8, "all_criteria_pass": true, "mean_power_ratio": 0.9989924180355878, "min_power_ratio": 0.9763322306308057, "max_power_ratio": 1.022721104693569 }, "gain_minus6/D": { "outputs": 8, "all_criteria_pass": true, "mean_power_ratio": 0.999060030397229, "min_power_ratio": 0.9767851240819172, "max_power_ratio": 1.022837494322539 }, "gain_plus6/v2": { "outputs": 8, "all_criteria_pass": true, "mean_power_ratio": 0.9989924180355876, "min_power_ratio": 0.9763322306308054, "max_power_ratio": 1.0227211046935683 }, "gain_plus6/D": { "outputs": 8, "all_criteria_pass": true, "mean_power_ratio": 0.9990600303972286, "min_power_ratio": 0.9767851240819168, "max_power_ratio": 1.0228374943225385 }, "time_half/v2": { "outputs": 8, "all_criteria_pass": true, "mean_power_ratio": 1.0006556321856466, "min_power_ratio": 0.9742292398266549, "max_power_ratio": 1.0297613893766142 }, "time_half/D": { "outputs": 8, "all_criteria_pass": true, "mean_power_ratio": 1.0007425634704321, "min_power_ratio": 0.9740588369831976, "max_power_ratio": 1.0296281639641123 }, "time_double/v2": { "outputs": 8, "all_criteria_pass": true, "mean_power_ratio": 0.9956973122305979, "min_power_ratio": 0.9821062682847963, "max_power_ratio": 1.0112996284909688 }, "time_double/D": { "outputs": 8, "all_criteria_pass": true, "mean_power_ratio": 0.995832437268704, "min_power_ratio": 0.9820159449375391, "max_power_ratio": 1.0114143061760856 }, "pitch_minus12/v2": { "outputs": 8, "all_criteria_pass": true, "mean_power_ratio": 0.9989924180355878, "min_power_ratio": 0.9763322306308054, "max_power_ratio": 1.0227211046935687 }, "pitch_minus12/D": { "outputs": 8, "all_criteria_pass": true, "mean_power_ratio": 0.9990600303972286, "min_power_ratio": 0.9767851240819169, "max_power_ratio": 1.0228374943225387 }, "pitch_plus12/v2": { "outputs": 8, "all_criteria_pass": true, "mean_power_ratio": 0.9989924180355878, "min_power_ratio": 0.9763322306308054, "max_power_ratio": 1.0227211046935687 }, "pitch_plus12/D": { "outputs": 8, "all_criteria_pass": true, "mean_power_ratio": 0.9990600303972286, "min_power_ratio": 0.9767851240819169, "max_power_ratio": 1.0228374943225387 } }, "limitations": [ "Synthetic noise-only control measurement, not human quality or MOS calibration.", "Finite eight-seed power variation is reported, not thresholded.", "Pitch noise invariance is appropriate: independent noise PSD remains fixed under pitch edit.", "Time edits verify exact output length and absence of nonfinite samples; do not imply identical stochastic waveforms." ] }