Background / engine_safaa_v4.py
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S190: WPE runs in a timeout-guarded subprocess instead of unbounded in-process
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#!/usr/bin/env python3
"""
الءفاؑ v3 β€” Dedicated Dereverberation Engine
Ψ₯Ψ²Ψ§Ω„Ψ© Ψ§Ω„Ψ΅Ψ―Ω‰ ΩˆΨ§Ω„Ψ±ΩŠΩΩŠΨ±Ψ¨
FIXES vs v2:
B1 _jalaa() late window: 150ms β†’ 450ms (was reading 50-200ms; Β§3.3 says 50-500ms)
B2 _decode() now uses pcm_f32le β†’ float32; soundfile when available (no 16-bit truncation)
B3 _band_energy() samples across full file (was FFT of first 1024 samples only)
B4 G4 Ra-trill: scans full audio in overlapping 1s windows (was first 1s only)
B5 _rt60() fallback slope condition was malformed (med-4 guard logic fixed)
IMPROVEMENTS vs v2:
I1 DF3 three passes now run in parallel (ThreadPoolExecutor) β€” 3Γ— faster
I2 _enc() intermediates are mono; only final output is stereo
I3 _tailnr() reduces nr by 1 when JALAA already ran (avoid double-attenuation)
I4 DF3 speech-pass attenuation capped to Β§79 per-style limits:
Murattal ≀ 18 dB / Mujawwad ≀ 6 dB
I5 WPE LRA check uses 50% overlapping frames (was non-overlapping β†’ noisy)
I6 SafaaState gains guard_pass/guard_warn lists (structured; JSON report improved)
I7 LF EQ: LF band RT60 scaled by 1.3Γ— per Β§3.4 (LF decays slower than broadband)
I8 process() tracks all temp paths; single cleanup on exit (no leaks)
I9 _decode() try/finally ensures temp file removed on exception
I10 DRR-weighted JALAA: skip when DRR already > 6 dB (room is already reasonably dry)
PIPELINE (unchanged order)
S1 RT60 estimation (Schroeder backward integration)
S2 Sub-band LF room mode removal (3 bands, LF-scaled depth) [B5/I7]
S3 WPE dereverberation RT60 > 1.0s
S4 DF3 reverb-adapted (speech/transition/tail, parallel) [I1/I4]
S5 JALAA per-frame DRR gate [B1/I10]
S6 Tail floor NR (afftdn calibrated) [I3]
S7 Arabic phoneme guards [B3/B4]
USAGE
python3 engine_safaa_v3.py input.wav output.wav [--tier X] [--mujawwad 0.0] [--rt60 0.0]
KB REFS: Β§3 Β§28 Β§35 Β§36 Β§52 Β§79 Β§109 Β§138 Β§140 Β§143 Β§145 Β§151 Β§152 Β§154
"""
from __future__ import annotations
__version__ = 'v4'
import os, shutil, subprocess, tempfile, warnings, multiprocessing as mp
from concurrent.futures import ThreadPoolExecutor, as_completed
from dataclasses import dataclass, field
from pathlib import Path
from typing import List, Optional, Tuple
warnings.filterwarnings('ignore')
_TMP = tempfile.gettempdir()
try:
import numpy as np
NUMPY_OK = True
except ImportError:
NUMPY_OK = False
try:
import soundfile as SF
SF_OK = True
except ImportError:
SF_OK = False
try:
from scipy.io import wavfile as _scipy_wavfile
SCIPY_WAV_OK = True
except ImportError:
SCIPY_WAV_OK = False
# DF3 binary
# S188: self-healing resolution + real executability self-test (was just a
# path/PATH existence check β€” could report "available" for a binary that
# exists but isn't actually executable or fails to run on this container)
_DF3_CLI_BIN = ''
_DF3_INIT_ERR = ''
for _c in [str(Path(__file__).parent / 'deep-filter'),
'/home/claude/deep-filter', 'deep-filter', 'deepfilter', 'deep_filter']:
_p = Path(_c)
if _p.is_absolute():
if _p.exists() and not os.access(_c, os.X_OK):
try: os.chmod(_c, 0o755)
except Exception: pass
if _p.exists() and os.access(_c, os.X_OK):
_DF3_CLI_BIN = _c; break
elif shutil.which(_c):
_DF3_CLI_BIN = _c; break
if _DF3_CLI_BIN:
try:
subprocess.run([_DF3_CLI_BIN, '--help'], capture_output=True, timeout=10)
except Exception as _e:
_DF3_INIT_ERR = f'{type(_e).__name__}: {_e}'
_DF3_CLI_BIN = ''
DF3_OK = bool(_DF3_CLI_BIN)
if not DF3_OK:
print(f'[INIT] deep-filter unavailable'
f'{(" β€” " + _DF3_INIT_ERR) if _DF3_INIT_ERR else " (no candidate found)"}')
# nara_wpe
WPE_OK = False
try:
from nara_wpe.wpe import wpe_v8
from nara_wpe.utils import stft as _wpe_stft, istft as _wpe_istft
WPE_OK = True
except ImportError:
pass
# ─── Constants ────────────────────────────────────────────────────────────────
SR = 48000
WAV_CODEC = 'pcm_s24le'
RT60_MIN = 0.15 # below: nothing to do
RT60_WPE_MIN = 1.00 # Β§109.6
RT60_TAILNR = 0.30
RT60_AGGR = 1.50
MUJ_RT60_FLOOR = 1.20 # Β§145.3
# Β§79 per-style DF attenuation hard limits β€” v4: raised for deeper cleaning
_DF3_LIM_MURATTAL = 24 # dB maximum (was 18)
_DF3_LIM_MUJAWWAD = 8 # dB maximum (was 6)
_DF3_SPEECH = 15 # was 12
_DF3_TRANS = 24 # was 20
_DF3_TAIL = 32 # was 28
_CHUNK_S = 0.100
_XFADE_N = 960
_RMS_MAX_DELTA = 1.0
_LRA_MAX_DELTA = 0.5 # Β§109.4
DRR_ALREADY_DRY = 3.0 # v4: lower threshold β†’ JALAA runs on more material (was 6.0)
# ─── State ────────────────────────────────────────────────────────────────────
@dataclass
class SafaaState:
input_path: str = ''
source_tier: str = 'TIER_UNKNOWN'
mujawwad_conf: float = 0.0
rt60_initial: float = 0.0
drr_before: float = 0.0
drr_after: float = 0.0
lf_eq: bool = False
wpe: bool = False
df3: bool = False
jalaa: bool = False
tail_nr: bool = False
guard_reverts: int = 0
guard_pass: List[str] = field(default_factory=list) # [I6]
guard_warn: List[str] = field(default_factory=list) # [I6]
log: List[str] = field(default_factory=list)
_tmps: List[str] = field(default_factory=list, repr=False)
def _L(st, msg):
st.log.append(msg); print(msg)
def _track(st, path):
"""Register a temp path for cleanup. Returns path."""
if path and path not in (st.input_path,):
st._tmps.append(path)
return path
def _cleanup_all(st):
for p in st._tmps:
try:
if p and os.path.exists(p): os.unlink(p)
except Exception:
pass
st._tmps.clear()
# ─── FFmpeg helpers ───────────────────────────────────────────────────────────
def _run(cmd, timeout=600):
r = subprocess.run(cmd, capture_output=True, timeout=timeout)
return r.returncode, r.stdout, r.stderr
def _tmp(tag, st=None):
p = os.path.join(_TMP, f'safaa3_{tag}_{os.getpid()}.wav')
if st is not None:
st._tmps.append(p)
return p
def _cleanup(*paths):
for p in paths:
try:
if p and os.path.exists(p): os.unlink(p)
except Exception:
pass
def _decode(path, st=None):
"""
Float32 mono at SR. [B2/I9]
Uses soundfile when available (faster, native float32).
Falls back to ffmpeg pcm_f32le + wave read.
try/finally ensures temp file removed on exception.
"""
if not NUMPY_OK:
return None
t = None
try:
if SF_OK:
# ffmpeg β†’ pcm_f32le temp, then soundfile reads it natively
t = os.path.join(_TMP, f'safaa3_dec_{os.getpid()}.wav')
rc, _, _ = _run(['ffmpeg', '-y', '-i', path,
'-acodec', 'pcm_f32le',
'-ar', str(SR), '-ac', '1',
'-loglevel', 'error', t])
if rc or not os.path.exists(t):
return None
data, _ = SF.read(t, dtype='float32', always_2d=False)
return data
elif SCIPY_WAV_OK:
# scipy.io.wavfile can read pcm_f32le natively
t = os.path.join(_TMP, f'safaa3_dec_{os.getpid()}.wav')
rc, _, _ = _run(['ffmpeg', '-y', '-i', path,
'-acodec', 'pcm_f32le',
'-ar', str(SR), '-ac', '1',
'-loglevel', 'error', t])
if rc or not os.path.exists(t):
return None
_, data = _scipy_wavfile.read(t)
if data.dtype != np.float32:
data = data.astype(np.float32) / np.iinfo(data.dtype).max
return data.copy()
else:
# Final fallback: pcm_s16le β†’ int16 β†’ float32 normalised
t = os.path.join(_TMP, f'safaa3_dec_{os.getpid()}.wav')
rc, _, _ = _run(['ffmpeg', '-y', '-i', path,
'-acodec', 'pcm_s16le',
'-ar', str(SR), '-ac', '1',
'-loglevel', 'error', t])
if rc or not os.path.exists(t):
return None
import wave as _w
with _w.open(t, 'rb') as f:
raw = f.readframes(f.getnframes())
return np.frombuffer(raw, dtype=np.int16).astype(np.float32) / 32768.0
except Exception:
return None
finally:
if t and os.path.exists(t):
try: os.unlink(t)
except Exception: pass
def _enc_mono(src, dst):
"""Intermediate encode: mono 24-bit. [I2]"""
rc, _, _ = _run(['ffmpeg', '-y', '-i', src,
'-acodec', WAV_CODEC,
'-ar', str(SR), '-ac', '1',
'-loglevel', 'error', dst])
return rc == 0 and os.path.exists(dst)
def _enc_stereo(src, dst):
"""Final output encode: stereo 24-bit. [I2]"""
rc, _, _ = _run(['ffmpeg', '-y', '-i', src,
'-acodec', WAV_CODEC,
'-ar', str(SR), '-ac', '2',
'-loglevel', 'error', dst])
return rc == 0 and os.path.exists(dst)
def _rmsdb(s):
return float(20 * np.log10(np.sqrt(np.mean(s ** 2)) + 1e-10))
def _band_energy(s, flo, fhi, n_fft=2048, n_samples=8):
"""
Band energy estimate sampled across the full signal. [B3]
Averages n_samples evenly-spaced windows rather than only the first n_fft samples.
"""
if len(s) < n_fft:
return 0.0
step = max(n_fft, len(s) // (n_samples + 1))
positions = range(0, len(s) - n_fft, step)
energies = []
fr = np.fft.rfftfreq(n_fft, 1.0 / SR)
mask = (fr >= flo) & (fr <= fhi)
for pos in positions:
sp = np.abs(np.fft.rfft(s[pos:pos + n_fft], n=n_fft))
energies.append(float(np.mean(sp[mask] ** 2) + 1e-20))
return float(np.mean(energies)) if energies else 0.0
# ─── Stage 1: RT60 (Schroeder backward integration) ──────────────────────────
def _rt60(samples, sr=SR):
"""
Schroeder backward integration (Β§3.1).
Find -5 dB and -25 dB crossings of backward energy β†’ T20 Γ— 3 = T60.
Fallback: linear regression on the decay region. [B5]
"""
if not NUMPY_OK or samples is None or len(samples) < sr * 3:
return 0.0
fn = int(0.020 * sr)
n = len(samples) // fn
if n < 30:
return 0.0
energy = np.array([float(np.mean(samples[i * fn:(i + 1) * fn] ** 2)) for i in range(n)])
energy = np.maximum(energy, 1e-20)
sch = np.cumsum(energy[::-1])[::-1]
sch_db = 10 * np.log10(sch / (sch[0] + 1e-20))
t5 = t25 = None
for i, v in enumerate(sch_db):
if t5 is None and v <= -5.0: t5 = i * 0.020
if t25 is None and v <= -25.0: t25 = i * 0.020; break
if t5 is not None and t25 is not None and t25 > t5:
return float(np.clip((t25 - t5) * 3.0, 0.0, 6.0))
# Fallback: slope estimation on the decay tail [B5]
edb = 10 * np.log10(energy)
med = float(np.median(edb))
# Find the decay region: frames below median but above noise floor
decay_mask = (edb > med - 30) & (edb < med - 2)
if decay_mask.sum() < 6:
return 0.0
t_arr = np.where(decay_mask)[0] * 0.020
e_arr = edb[decay_mask]
slope = float(np.polyfit(t_arr, e_arr, 1)[0])
if slope >= -1.0:
return 0.0
return float(np.clip(60.0 / abs(slope), 0.0, 4.0))
def _drr(samples, sr=SR):
"""
DRR: energy ratio early(0-50ms) vs late(50-500ms) (Β§3.3/Β§28.6).
"""
if not NUMPY_OK or samples is None:
return 0.0
en = int(0.050 * sr)
ln = int(0.450 * sr) # late window: 50-500ms
step = int(0.200 * sr)
vals = []
for s in range(0, len(samples) - en - ln, step):
er = float(np.sqrt(np.mean(samples[s:s + en] ** 2)) + 1e-10)
lr = float(np.sqrt(np.mean(samples[s + en:s + en + ln] ** 2)) + 1e-10)
if er > 1e-5 and lr > 1e-5:
vals.append(20.0 * np.log10(er / lr))
return float(np.median(vals)) if vals else 0.0
# ─── Stage 2: Sub-band LF EQ (Β§3.4) ─────────────────────────────────────────
def _lf_eq(wav, samples, rt60, st):
"""
Three EQ bands with LF-scaled depth. [I7]
Β§3.4: LF bands have longer RT60 (empirically ~1.3Γ— broadband).
Apply the LF multiplier before computing per-band depth.
Mujawwad: reduce depth and enforce RT60 floor (Β§145.3).
"""
if rt60 < RT60_MIN:
return wav
lf_rt60 = rt60 * 1.30 # Β§3.4: LF decays ~30% slower [I7]
scale = float(np.clip(lf_rt60 / 0.5, 1.0, 6.0))
d_sub = float(np.clip(scale * 1.0, 1.0, 6.0))
d_lo = float(np.clip(scale * 0.7, 0.7, 4.2))
d_room = float(np.clip(scale * 0.4, 0.4, 2.4))
if st.mujawwad_conf > 0.6:
d_sub *= 0.5; d_lo *= 0.5; d_room *= 0.5
if rt60 < MUJ_RT60_FLOOR * 1.5:
r = float(np.clip((rt60 - MUJ_RT60_FLOOR) / (MUJ_RT60_FLOOR * 0.5 + 0.001), 0, 1))
d_sub *= r; d_lo *= r; d_room *= r
_L(st, f' [S2-LF] Mujawwad floor limiter ratio={r:.2f}')
flt = []
if d_sub > 0.2: flt.append(f'equalizer=f=150:width_type=o:width=1.4:g=-{d_sub:.1f}')
if d_lo > 0.2: flt.append(f'equalizer=f=300:width_type=o:width=1.2:g=-{d_lo:.1f}')
if d_room > 0.2: flt.append(f'equalizer=f=500:width_type=o:width=1.0:g=-{d_room:.1f}')
if not flt:
return wav
out = _tmp('s2', st)
rc, _, _ = _run(['ffmpeg', '-y', '-i', wav, '-af', ','.join(flt),
'-acodec', WAV_CODEC, '-ar', str(SR), '-ac', '1', # mono [I2]
'-loglevel', 'error', out])
if rc or not os.path.exists(out):
return wav
post = _decode(out)
if post is not None and samples is not None:
d = _rmsdb(post) - _rmsdb(samples)
if abs(d) > 3.0: # relaxed: LF EQ at high RT60 can legitimately remove >1dB
_cleanup(out); st.guard_reverts += 1
_L(st, f' [S2-LF] RMS Ξ”={d:+.2f}dB β€” REVERT'); return wav
st.lf_eq = True
_L(st, f' [S2-LF] βœ“ lf_rt60={lf_rt60:.2f}s sub={d_sub:.1f} lo={d_lo:.1f} room={d_room:.1f} dB')
return out
# ─── Stage 3: WPE (threshold 1.0s, Β§109.6) ───────────────────────────────────
def _lra_overlapping(s, frame_s=0.4, hop_s=0.2, sr=SR):
"""LRA estimate using 50% overlapping frames. [I5]"""
fn = int(frame_s * sr)
hn = int(hop_s * sr)
if len(s) < fn:
return 0.0
db = [float(20 * np.log10(np.sqrt(np.mean(s[i:i + fn] ** 2)) + 1e-10))
for i in range(0, len(s) - fn, hn)]
return float(np.percentile(db, 95) - np.percentile(db, 10)) if len(db) >= 4 else 0.0
WPE_TIMEOUT_S = 240 # S190: hard cap so a slow/atypical file can't eat the whole 600s job budget
def _wpe_compute_worker(mi, mo, rt60, mujawwad_conf, q):
"""Runs in a separate forked process so a slow/hung wpe_v8 call can be
killed without taking down the whole engine. Writes result wav to `mo`
on success; only a small dict goes back through the queue."""
try:
if SF_OK:
y, _ = SF.read(mi, dtype='float32', always_2d=False)
else:
import wave as _w
with _w.open(mi, 'rb') as f: raw = f.readframes(f.getnframes())
y = np.frombuffer(raw, dtype=np.float32).copy()
if mujawwad_conf > 0.6: taps, iters = 5, 2
elif rt60 > 4.0: taps, iters = 12, 3
elif rt60 > 2.0: taps, iters = 10, 3
else: taps, iters = 8, 3
delay = 3
Y = _wpe_stft(y, size=512, shift=128)
Z = wpe_v8(Y[..., np.newaxis], taps=taps, delay=delay, iterations=iters)
z = _wpe_istft(Z[..., 0], size=512, shift=128)
z = z[:len(y)] if len(z) > len(y) else np.pad(z, (0, len(y) - len(z)))
ld = abs(_lra_overlapping(y) - _lra_overlapping(z)) # [I5]
if ld > _LRA_MAX_DELTA:
Z2 = wpe_v8(Y[..., np.newaxis], taps=taps, delay=delay, iterations=max(1, iters - 1))
z2 = _wpe_istft(Z2[..., 0], size=512, shift=128)
z2 = z2[:len(y)] if len(z2) > len(y) else np.pad(z2, (0, len(y) - len(z2)))
ld2 = abs(_lra_overlapping(y) - _lra_overlapping(z2))
if ld2 > _LRA_MAX_DELTA:
q.put({'ok': False, 'reason': f'LRA {ld2:.2f}LU after retry β€” REVERT'})
return
z = z2; ld = ld2
if SF_OK:
SF.write(mo, z.astype(np.float32), SR, subtype='FLOAT')
else:
import wave as _w
b16 = (np.clip(z, -1, 1) * 32767).astype(np.int16)
with _w.open(mo, 'wb') as f:
f.setnchannels(1); f.setsampwidth(2); f.setframerate(SR)
f.writeframes(b16.tobytes())
q.put({'ok': True, 'taps': taps, 'delay': delay, 'iters': iters, 'ld': float(ld)})
except Exception as e:
q.put({'ok': False, 'reason': f'exception: {e}'})
def _wpe(wav, rt60, st):
if not WPE_OK:
_L(st, ' [S3-WPE] nara_wpe not installed β†’ pip install nara_wpe soundfile')
return wav
if rt60 < RT60_WPE_MIN:
_L(st, f' [S3-WPE] RT60={rt60:.2f}s < {RT60_WPE_MIN}s β€” skip (Β§109.6)')
return wav
_L(st, f' [S3-WPE] RT60={rt60:.2f}s β€” running WPE (cap {WPE_TIMEOUT_S}s)')
d = tempfile.mkdtemp(prefix='safaa3_wpe_')
try:
mi = os.path.join(d, 'in.wav')
rc, _, _ = _run(['ffmpeg', '-y', '-i', wav,
'-acodec', 'pcm_f32le', '-ar', str(SR), '-ac', '1',
'-loglevel', 'error', mi])
if rc or not os.path.exists(mi):
return wav
mo = os.path.join(d, 'out.wav')
ctx = mp.get_context('fork')
q = ctx.Queue()
proc = ctx.Process(target=_wpe_compute_worker, args=(mi, mo, rt60, st.mujawwad_conf, q))
proc.start()
proc.join(WPE_TIMEOUT_S)
if proc.is_alive():
proc.terminate(); proc.join(5)
if proc.is_alive():
proc.kill(); proc.join(5)
st.guard_reverts += 1
_L(st, f' [S3-WPE] TIMED OUT after {WPE_TIMEOUT_S}s β€” using source for this stage only')
return wav
result = q.get() if not q.empty() else {'ok': False, 'reason': 'worker died with no result'}
if not result.get('ok'):
st.guard_reverts += 1
_L(st, f" [S3-WPE] {result.get('reason', 'failed')} β€” REVERT")
return wav
out = _tmp('s3', st)
if not _enc_mono(mo, out):
return wav
st.wpe = True
_L(st, f" [S3-WPE] βœ“ taps={result['taps']} delay={result['delay']} "
f"iters={result['iters']} LRA Ξ”={result['ld']:.2f}LU")
return out
except Exception as e:
_L(st, f' [S3-WPE] exception: {e}'); return wav
finally:
shutil.rmtree(d, ignore_errors=True)
# ─── Stage 4: DF3 smooth adaptive VAD (Β§22.5 / Β§106 / RL-01 / RL-16) ─────────
_ADF_LOUD_T = -15.0 # dBFS β€” projecting voice β†’ protect
_ADF_QUIET_T = -25.0 # dBFS β€” soft/breath β†’ clean hard
_ADF_SNR_GATE = 10.0 # v4: lower gate β†’ more chunks get cleaned (was 12)
_ADF_CHUNK_S = 0.050 # 50ms chunks β€” finer granularity than isteidad 100ms
_ADF_XFADE = int(0.120 * 48000) # v4: 120ms crossfade (was 40ms) β€” much smoother seams
# RL-16: guard bands β€” restore these from original after blend
_RL16_BANDS = [(220, 290), (950, 1100)] # Hz: Ghunnah nasal pole + formant zone
def _df3_pipe_decode(path, sr):
"""Decode WAV to float32 mono via ffmpeg pipe β€” avoids wave/soundfile dep."""
r = subprocess.run(
['ffmpeg', '-nostdin', '-y', '-hide_banner', '-loglevel', 'error',
'-i', path, '-ar', str(sr), '-ac', '1', '-f', 'f32le', '-'],
capture_output=True, timeout=120)
if r.returncode or len(r.stdout) < 4:
return None
return np.frombuffer(r.stdout, dtype=np.float32).copy()
def _stft_restore_bands(processed, original, sr, bands):
"""
RL-16: after DF3 blend, restore specified Hz bands from original.
Uses STFT with 50% overlap Hann window β€” preserves phase coherence.
"""
from numpy.fft import rfft, irfft
N = 2048; HOP = N // 2
freqs = np.fft.rfftfreq(N, d=1.0/sr) # Hz per bin
restore_mask = np.zeros(len(freqs), dtype=bool)
for lo, hi in bands:
restore_mask |= (freqs >= lo) & (freqs <= hi)
win = np.hanning(N).astype(np.float32)
min_n = min(len(processed), len(original))
p = processed[:min_n].astype(np.float64)
o = original[:min_n].astype(np.float64)
out = np.zeros(min_n, dtype=np.float64)
norm = np.zeros(min_n, dtype=np.float64)
for s in range(0, min_n - N, HOP):
Pf = rfft(p[s:s+N] * win)
Of = rfft(o[s:s+N] * win)
Pf[restore_mask] = Of[restore_mask] # restore original in guard bands
frame = irfft(Pf) * win
out[s:s+N] += frame; norm[s:s+N] += win**2
valid = norm > 1e-8
out[valid] /= norm[valid]
out[~valid] = p[~valid]
return out.astype(np.float32)
def _df3(wav, samples, rt60, st):
if not DF3_OK:
_L(st, f' [S4-DF3] deep-filter unavailable{(": " + _DF3_INIT_ERR) if _DF3_INIT_ERR else " (not found)"} β€” skip'); return wav
# Β§106.3 + Β§79 atten limits β€” v4: stronger per-class
lim = _DF3_LIM_MUJAWWAD if st.mujawwad_conf > 0.6 else _DF3_LIM_MURATTAL
a_loud = min(10, lim) # was 8
a_mid = min(18, lim) # was 15
a_quiet = min(24, lim + 10) # was 20
a_trans = min(14, lim) # v4: new transition class between loud/mid
if st.mujawwad_conf > 0.6:
a_loud = min(a_loud, 8)
a_mid = min(a_mid, 10)
a_quiet = min(a_quiet, 14)
a_trans = min(a_trans, 9)
d = tempfile.mkdtemp(prefix='safaa3_df3_')
try:
# ── Prepare pcm_s16le mono input ──────────────────────────────────
fi = os.path.join(d, 'in.wav')
rc, _, _ = _run(['ffmpeg', '-y', '-i', wav,
'-acodec', 'pcm_s16le', '-ar', str(SR), '-ac', '1',
'-loglevel', 'error', fi])
if rc or not os.path.exists(fi):
return wav
mono = _df3_pipe_decode(fi, SR)
if mono is None:
return wav
total = len(mono)
# ── VAD β€” 50ms chunks with SNR gate (Β§22.5) ──────────────────────
CHUNK = int(_ADF_CHUNK_S * SR)
nc = max(1, total // CHUNK)
# Estimate noise floor from quietest 10% of chunks
rms_db = np.array([
20.0 * np.log10(np.sqrt(np.mean(mono[i*CHUNK:(i+1)*CHUNK]**2)) + 1e-12)
for i in range(nc)])
noise_floor = float(np.percentile(rms_db, 10))
loud_m = rms_db > _ADF_LOUD_T
quiet_m = rms_db <= _ADF_QUIET_T
mid_m = ~loud_m & ~quiet_m
# Β§22.5 SNR gate: chunks already clean enough β†’ skip DF3, use original
chunk_snr = rms_db - noise_floor
clean_m = chunk_snr >= _ADF_SNR_GATE
# ── Label smoothing β€” mode filter over 7-chunk window (v4: was 3) ──────
# Wider window prevents micro-class flicker that causes audible texture changes
raw_cls = np.where(loud_m, 0, np.where(mid_m, 1, 2))
smoothed_cls = raw_cls.copy()
half = 3
for i in range(half, nc - half):
window = raw_cls[i-half:i+half+1]
counts = np.bincount(window, minlength=3)
smoothed_cls[i] = int(np.argmax(counts))
loud_m = smoothed_cls == 0
mid_m = smoothed_cls == 1
quiet_m = smoothed_cls == 2
n_loud = int(loud_m.sum()); n_mid = int(mid_m.sum())
n_quiet = int(quiet_m.sum()); n_clean = int(clean_m.sum())
_L(st, f' [S4-ADF] 50ms chunks: LOUD={n_loud} MID={n_mid} '
f'QUIET={n_quiet} CLEAN(skip)={n_clean} nf={noise_floor:.1f}dBFS')
# ── 3 parallel DF passes with per-class flags ─────────────────────
df_out = {}
def _run_pass(cls, atten, pf=False, pf_beta=0.02):
od = os.path.join(d, cls); os.makedirs(od, exist_ok=True)
cmd = [_DF3_CLI_BIN, '--atten-lim-db', str(atten)]
if pf:
cmd += ['--pf', '--pf-beta', str(pf_beta)]
cmd += ['-o', od, fi]
try:
r2 = subprocess.run(cmd, capture_output=True, timeout=180) # S186: same per-class guard as main
except subprocess.TimeoutExpired:
_L(st, f' [S4-ADF] {cls} pass TIMED OUT after 180s β€” using source for this class only') # S186
return cls, mono.copy()
wp = os.path.join(od, 'in.wav')
if r2.returncode or not os.path.exists(wp):
_stderr = r2.stderr.decode('utf-8', errors='replace')[:400] if r2.stderr else ''
_stdout = r2.stdout.decode('utf-8', errors='replace')[:200] if r2.stdout else ''
_L(st, f' [S4-ADF] {cls} pass failed rc={r2.returncode} cmd={cmd}')
_L(st, f' [S4-ADF] stderr: {_stderr!r}')
if _stdout: _L(st, f' [S4-ADF] stdout: {_stdout!r}')
return cls, mono.copy() # S183/S185: was silent
arr = _df3_pipe_decode(wp, SR)
if arr is None:
_L(st, f' [S4-ADF] {cls} decode failed β€” using source')
return cls, mono.copy()
pf_tag = ' +PF' if pf else ''
_L(st, f' [S4-ADF] {cls:6s} {atten:2d}dB{pf_tag} βœ“ '
f'max={np.max(np.abs(arr)):.4f}')
return cls, arr
with ThreadPoolExecutor(max_workers=4) as ex:
futs = [
ex.submit(_run_pass, 'loud', a_loud, False),
ex.submit(_run_pass, 'mid', a_mid, False),
ex.submit(_run_pass, 'quiet', a_quiet, True, 0.04), # PF quiet only
ex.submit(_run_pass, 'trans', a_trans, False), # v4: transition class
]
for fut in as_completed(futs):
cls, arr = fut.result()
df_out[cls] = arr
# ── Expand masks to sample level ──────────────────────────────────
def _expand(mask):
full = np.zeros(total, dtype=bool)
for i, v in enumerate(mask):
if v:
s = i * CHUNK
full[s:min(s + CHUNK, total)] = True
return full
l_s = _expand(loud_m); m_s = _expand(mid_m)
q_s = _expand(quiet_m); c_s = _expand(clean_m)
min_n = min(total, *(len(df_out[c]) for c in ('loud', 'mid', 'quiet')))
blended = np.zeros(min_n, dtype=np.float64)
blended[l_s[:min_n]] = df_out['loud'][:min_n][l_s[:min_n]]
blended[m_s[:min_n]] = df_out['mid'][:min_n][m_s[:min_n]]
blended[q_s[:min_n]] = df_out['quiet'][:min_n][q_s[:min_n]]
# Β§22.5 clean gate: restore original on already-clean chunks
blended[c_s[:min_n]] = mono[:min_n][c_s[:min_n]]
# ── 120ms sigmoid crossfade at every class boundary (v4: was cosine 40ms) ──
# Sigmoid gives perceptually flatter transition β€” no "click" at midpoint
cls_map = (l_s[:min_n].astype(np.int8) * 1 +
m_s[:min_n].astype(np.int8) * 2 +
q_s[:min_n].astype(np.int8) * 3)
bounds = np.where(np.diff(cls_map) != 0)[0]
FADE = _ADF_XFADE
for b in bounds:
s_cf = max(0, b - FADE // 2)
e_cf = min(min_n, b + FADE // 2)
if e_cf <= s_cf: continue
ln_ = e_cf - s_cf
# Sigmoid: x from -6..+6 β†’ smooth S-curve
x = np.linspace(-6.0, 6.0, ln_)
fi_ = 1.0 / (1.0 + np.exp(-x)) # sigmoid fade-in
fo = 1.0 - fi_ # sigmoid fade-out
cb = int(cls_map[s_cf])
ca = int(cls_map[min(e_cf, min_n - 1)])
cb_n = 'loud' if cb==1 else ('mid' if cb==2 else 'quiet')
ca_n = 'loud' if ca==1 else ('mid' if ca==2 else 'quiet')
# v4: blend through 'trans' class at midpoint for 3-way smooth
mid_blend = (
df_out[cb_n][:min_n][s_cf:e_cf].astype(np.float64) * fo * 0.5 +
df_out['trans'][:min_n][s_cf:e_cf].astype(np.float64) * 0.5 +
df_out[ca_n][:min_n][s_cf:e_cf].astype(np.float64) * fi_ * 0.5
)
blended[s_cf:e_cf] = mid_blend
_L(st, f' [S4-ADF] {len(bounds)} sigmoid crossfades @ {FADE} samp (120ms)')
# ── RL-16: restore Ghunnah guard bands from original ──────────────
blended_f32 = np.where(np.isfinite(blended), blended, 0.0).astype(np.float32)
blended_f32 = _stft_restore_bands(blended_f32, mono[:min_n], SR, _RL16_BANDS)
_L(st, f' [S4-ADF] RL-16 bands restored: '
f'{", ".join(f"{lo}-{hi}Hz" for lo,hi in _RL16_BANDS)}')
# ── Silence guard ─────────────────────────────────────────────────
if float(np.max(np.abs(blended_f32))) < 1e-4:
_L(st, ' [S4-ADF] ⚠ silent result β€” fallback to mid pass')
blended_f32 = df_out['mid'][:min_n].astype(np.float32)
# ── Encode to pcm_s24le stereo ────────────────────────────────────
out = _tmp('s4', st)
r3 = subprocess.run(
['ffmpeg', '-nostdin', '-y', '-hide_banner', '-loglevel', 'error',
'-f', 'f32le', '-ar', str(SR), '-ac', '1', '-i', '-',
'-ar', str(SR), '-ac', '2', '-acodec', 'pcm_s24le', out],
input=blended_f32.tobytes(), capture_output=True, timeout=120)
if r3.returncode or not os.path.exists(out):
return wav
delta = _rmsdb(blended_f32) - _rmsdb(mono)
st.df3 = True
_L(st, f' [S4-ADF] βœ“ loud={a_loud}dB mid={a_mid}dB quiet={a_quiet}dB '
f'RMS Ξ”={delta:+.2f}dB')
return out
except Exception as e:
_L(st, f' [S4-DF3] exception: {e}'); return wav
finally:
shutil.rmtree(d, ignore_errors=True)
# ─── Stage 5: JALAA per-frame DRR gate (Β§28.6) ───────────────────────────────
def _jalaa(wav, samples, rt60, drr_before, st):
"""
Per-frame DRR classification β†’ calibrated afftdn on reverb-dominated frames.
[B1] Late window corrected to 450ms (50-500ms per Β§3.3).
[I10] Skip entirely if DRR already > DRR_ALREADY_DRY (room is dry enough).
"""
if not NUMPY_OK or samples is None or rt60 < 0.30:
_L(st, f' [S5-JALAA] RT60={rt60:.2f}s < 0.30 β€” skip'); return wav
if drr_before > DRR_ALREADY_DRY:
_L(st, f' [S5-JALAA] DRR={drr_before:.1f}dB already dry β€” skip [I10]'); return wav
fn = int(0.200 * SR)
en = int(0.050 * SR)
ln = int(0.450 * SR) # [B1] was 0.150 β†’ 450ms (50-500ms window)
n = len(samples) // fn
if n < 5:
return wav
nf_vals = []
for i in range(n):
s = i * fn; chunk = samples[s:s + fn]
if len(chunk) < en + ln:
continue
er = float(np.sqrt(np.mean(chunk[:en] ** 2)) + 1e-10)
lr = float(np.sqrt(np.mean(chunk[en:en + ln] ** 2)) + 1e-10)
if er < 1e-5: continue
if 20.0 * np.log10(er / lr) < 3.0: # reverb-dominated
nf_vals.append(float(20 * np.log10(lr + 1e-10)))
if not nf_vals:
_L(st, ' [S5-JALAA] no reverb frames β€” skip'); return wav
nf = float(np.clip(float(np.median(nf_vals)) + 3, -72, -20)) # v4: floor raised -25β†’-20
nr = 3 if rt60 > RT60_AGGR else 2 # v4: base raised (was 2/1)
if st.mujawwad_conf > 0.6: nr = max(1, nr - 1)
# v4: two-pass JALAA β€” first pass stationary, second adaptive tracking
out = _tmp('s5a', st)
rc, _, _ = _run(['ffmpeg', '-y', '-i', wav,
'-af', f'afftdn=nr={nr}:nf={nf:.0f}:nt=w:tn=1',
'-acodec', WAV_CODEC, '-ar', str(SR), '-ac', '1',
'-loglevel', 'error', out])
if rc or not os.path.exists(out):
return wav
out2 = _tmp('s5b', st)
rc2, _, _ = _run(['ffmpeg', '-y', '-i', out,
'-af', f'afftdn=nr={max(1,nr-1)}:nf={nf+3:.0f}:nt=w:tn=1',
'-acodec', WAV_CODEC, '-ar', str(SR), '-ac', '1',
'-loglevel', 'error', out2])
if rc2 or not os.path.exists(out2):
pass # keep single-pass result
else:
_cleanup(out); out = out2
post = _decode(out)
if post is not None:
d = _rmsdb(post) - _rmsdb(samples)
if abs(d) > _RMS_MAX_DELTA:
_cleanup(out); st.guard_reverts += 1
_L(st, f' [S5-JALAA] RMS Ξ”={d:+.2f}dB β€” REVERT'); return wav
st.jalaa = True
_L(st, f' [S5-JALAA] βœ“ reverb_frames={len(nf_vals)}/{n} nf={nf:.0f}dB nr={nr}')
return out
# ─── Stage 6: Tail floor NR β€” 2-stage (afftdn + anlmdn) ─────────────────────
def _tailnr(wav, samples, rt60, st):
"""
2-stage NR pipeline (Β§83.3 order: stationary β†’ non-stationary):
Stage A: afftdn with nt=w (adaptive tracking) for stationary noise floor.
Stage B: anlmdn (s=7:p=3:r=15) for transient/non-stationary residuals.
RT60-scaled nr: base=2, +1 per 1.5s RT60 above threshold, cap=5 (Β§5.3: 20dB/nr max).
[I3] If JALAA already ran, reduce nr by 1 to avoid double-attenuation.
RL-16: sibilant SNR guard β€” revert if Safir/Tafasshi band drops > 2dB.
"""
if rt60 < RT60_TAILNR or samples is None or not NUMPY_OK:
return wav
fn = int(0.200 * SR)
overall = _rmsdb(samples)
fdb = np.array([float(20 * np.log10(np.sqrt(np.mean(samples[i:i+fn]**2)) + 1e-10))
for i in range(0, len(samples) - fn, fn)])
quiet = fdb[fdb < overall - 10]
if len(quiet) == 0:
return wav
nf = float(np.clip(float(np.median(quiet)) + 4, -72, -25))
# v4: RT60-scaled nr β€” higher cap (8 was 5), stronger base
nr = min(8, 3 + int((rt60 - RT60_TAILNR) / 1.2)) # was cap=5, base=2, step=1.5
if st.mujawwad_conf > 0.6: nr = max(1, nr - 1)
if st.jalaa: nr = max(1, nr - 1) # [I3]
# ── Stage A: afftdn with adaptive noise tracking ──────────────────────
out_a = _tmp('s6a', st)
rc, _, _ = _run(['ffmpeg', '-y', '-i', wav,
'-af', f'afftdn=nr={nr}:nf={nf:.0f}:nt=w:om=o',
'-acodec', WAV_CODEC, '-ar', str(SR), '-ac', '2',
'-loglevel', 'error', out_a])
if rc or not os.path.exists(out_a):
return wav
# ── Stage B: anlmdn for non-stationary residuals ──────────────────────
# anlmdn: s=patch size, p=context, r=search radius (Β§95 KB)
# Scale strength with nr: gentle (s=5) at nr<=2, standard (s=7) at nr>2
patch = 7 if nr > 2 else 5
out_b = _tmp('s6b', st)
rc2, _, _ = _run(['ffmpeg', '-y', '-i', out_a,
'-af', f'anlmdn=s={patch}:p=3:r=15:m=1',
'-acodec', WAV_CODEC, '-ar', str(SR), '-ac', '2',
'-loglevel', 'error', out_b])
if rc2 or not os.path.exists(out_b):
# Stage B failed β€” commit Stage A only
st.tail_nr = True
jalaa_note = ' (JALAA-adj)' if st.jalaa else ''
_L(st, f' [S6-tailNR] βœ“ 1-stage nr={nr}{jalaa_note} nf={nf:.0f}dB '
f'[anlmdn failed β€” Stage A only]')
return out_a
# ── Sibilant SNR guard (RL-16 spirit) ─────────────────────────────────
post_s = _decode(out_b)
if post_s is not None:
sib_orig = _band_energy(samples, 3500, 8000)
sib_post = _band_energy(post_s, 3500, 8000)
sib_drop = sib_post - sib_orig
if sib_drop < -2.0:
_L(st, f' [S6-tailNR] sibilant drop {sib_drop:+.1f}dB β€” '
f'revert Stage B, keep Stage A')
_cleanup(out_b)
st.tail_nr = True
_L(st, f' [S6-tailNR] βœ“ nr={nr} nf={nf:.0f}dB [Stage A only]')
return out_a
# ── Stage C: v4 β€” gentle anlmdn second pass for reverb tail residual ────
out_c = _tmp('s6c', st)
rc3, _, _ = _run(['ffmpeg', '-y', '-i', out_b,
'-af', f'anlmdn=s=5:p=3:r=10:m=1',
'-acodec', WAV_CODEC, '-ar', str(SR), '-ac', '2',
'-loglevel', 'error', out_c])
if rc3 or not os.path.exists(out_c):
pass # keep Stage B
else:
post_c = _decode(out_c)
if post_c is not None:
sib_c = _band_energy(post_c, 3500, 8000)
sib_drop_c = sib_c - _band_energy(samples, 3500, 8000)
if sib_drop_c >= -2.5:
_cleanup(out_b); out_b = out_c
else:
_cleanup(out_c)
_cleanup(out_a)
st.tail_nr = True
jalaa_note = ' (JALAA-adj)' if st.jalaa else ''
_L(st, f' [S6-tailNR] βœ“ 3-stage nr={nr}{jalaa_note} nf={nf:.0f}dB '
f'patch={patch} rt60={rt60:.1f}s')
return out_b
# ─── Stage 7: Arabic phoneme guards (Β§35/Β§52/Β§143/Β§152) ──────────────────────
def _arabic_guards(orig_s, proc_wav, st):
"""
Seven guards verifying Tajweed-critical features survived processing.
WARN-only by design β€” reverb is worse than mild phoneme loss.
Results stored in st.guard_pass / st.guard_warn (structured). [I6]
[B3] _band_energy() now samples across full file.
[B4] G4 Ra-trill scans full audio in overlapping 1s windows.
"""
if not NUMPY_OK or orig_s is None:
return proc_wav
proc_s = _decode(proc_wav)
if proc_s is None:
return proc_wav
n = min(len(orig_s), len(proc_s))
o = orig_s[:n]; p = proc_s[:n]
def chk(name, cond, detail):
entry = f'{name}: {detail}'
if cond:
st.guard_pass.append(entry); _L(st, f' [S7-PASS] {entry}')
else:
st.guard_warn.append(entry); _L(st, f' [S7-WARN] ⚠ {entry}')
# G1 Ghunnah 250-300 Hz (Β§152.3)
go = _band_energy(o, 250, 300); gp = _band_energy(p, 250, 300)
if go > 1e-15:
d = 10 * np.log10(gp / go + 1e-20)
chk('G1-Ghunnah', d >= -3.0, f'{d:+.1f}dB {"βœ“" if d>=-3 else "⚠ nasal murmur lost"}')
# G2 Ikhfa 250-400 Hz (Β§52.5)
io = _band_energy(o, 250, 400); ip = _band_energy(p, 250, 400)
if io > 1e-15:
d = 10 * np.log10(ip / io + 1e-20)
chk('G2-Ikhfa', d >= -4.0, f'{d:+.1f}dB {"βœ“" if d>=-4 else "⚠ ikhfa nasalisation lost"}')
# G3 Qalqalah burst (Β§52.7, Β§143 Class 2)
sil_n = int(0.020 * SR); bst_n = int(0.030 * SR)
total = viol = 0
for i in range(0, n - sil_n - bst_n, sil_n):
sr_ = float(np.sqrt(np.mean(o[i:i + sil_n] ** 2)) + 1e-10)
br_ = float(np.sqrt(np.mean(o[i + sil_n:i + sil_n + bst_n] ** 2)) + 1e-10)
if sr_ < 0.005 and br_ > sr_ * 5:
total += 1
bp = float(np.sqrt(np.mean(p[i + sil_n:i + sil_n + bst_n] ** 2)) + 1e-10)
if 20 * np.log10(bp / br_ + 1e-10) < -6.0: viol += 1
if total > 0:
pct = viol / total * 100
chk('G3-Qalqalah', pct <= 20,
f'{total} bursts {pct:.0f}% violated {"βœ“" if pct<=20 else "⚠ echo burst attenuated"}')
# G4 Ra trill AM 25-35 Hz β€” FULL AUDIO scan in overlapping 1s windows [B4]
win = SR; hop = SR // 2
am_ratios = []
for pos in range(0, n - win, hop):
ef_o = np.abs(np.fft.rfft(np.abs(o[pos:pos + win]), n=win))
ef_p = np.abs(np.fft.rfft(np.abs(p[pos:pos + win]), n=win))
am_o = float(np.mean(ef_o[25:36])); am_p = float(np.mean(ef_p[25:36]))
if am_o > 1e-8:
am_ratios.append(am_p / am_o)
if am_ratios:
r = float(np.median(am_ratios))
chk('G4-Ra-trill', r >= 0.70,
f'AM ratio={r:.2f} (median over {len(am_ratios)} windows) '
f'{"βœ“" if r>=0.70 else "⚠ Ψ± trill may be smeared"}')
# G5 Safir 5.5-12 kHz β€” Ψ΅ Ψ³ Ψ² (Β§152.3)
so = _band_energy(o, 5500, 12000); sp = _band_energy(p, 5500, 12000)
if so > 1e-15:
d = 10 * np.log10(sp / so + 1e-20)
chk('G5-Safir', d >= -5.0,
f'{d:+.1f}dB {"βœ“" if d>=-5 else "⚠ Ψ΅ Ψ³ Ψ² may be dull"}')
# G6 Tafasshi 3-8 kHz β€” Ψ΄ (Β§152.3)
to = _band_energy(o, 3000, 8000); tp = _band_energy(p, 3000, 8000)
if to > 1e-15:
d = 10 * np.log10(tp / to + 1e-20)
chk('G6-Tafasshi', d >= -4.0,
f'{d:+.1f}dB {"βœ“" if d>=-4 else "⚠ Ψ΄ may lose spread"}')
# G7 Izhar silence count (Β§52.5.1)
def _sil_count(s):
fn_ = int(0.010 * SR)
db = np.array([float(20 * np.log10(np.sqrt(np.mean(s[i:i + fn_] ** 2)) + 1e-10))
for i in range(0, len(s) - fn_, fn_)])
med = float(np.median(db)); c = 0; in_s = False; sl = 0
for v in db:
if v < med - 18: in_s = True; sl += 1
else:
if in_s and 2 <= sl <= 8: c += 1
in_s = False; sl = 0
return c
sc_o = _sil_count(o); sc_p = _sil_count(p)
if sc_o > 0:
r = sc_p / sc_o
chk('G7-Izhar', r >= 0.70,
f'silences {sc_o}β†’{sc_p} ({r:.0%}) {"βœ“" if r>=0.70 else "⚠ words may run together"}')
total_g = len(st.guard_pass) + len(st.guard_warn)
if st.guard_warn:
_L(st, f' [S7] {len(st.guard_warn)}/{total_g} warnings β€” check output for Tajweed artifacts')
else:
_L(st, f' [S7] All {total_g} guards passed βœ“')
return proc_wav
# ─── Main ─────────────────────────────────────────────────────────────────────
def process(input_path, output_path, source_tier='TIER_UNKNOWN',
mujawwad_conf=0.0, force_rt60=0.0, verbose=True):
"""
الءفاؑ v3 β€” main entry point.
Returns SafaaState with full diagnostics.
All temp files are tracked and cleaned up on exit. [I8]
"""
st = SafaaState(input_path=input_path, source_tier=source_tier,
mujawwad_conf=mujawwad_conf)
_L(st, f'\n{"═"*60}')
_L(st, f' الءفاؑ {__version__} β€” Ψ₯Ψ²Ψ§Ω„Ψ© Ψ§Ω„Ψ΅Ψ―Ω‰ ΩˆΨ§Ω„Ψ±ΩŠΩΩŠΨ±Ψ¨')
_L(st, f' Input : {Path(input_path).name}')
_L(st, f' Tier : {source_tier} Mujawwad: {mujawwad_conf:.2f}')
_L(st, f'{"═"*60}')
s_orig = _decode(input_path)
if s_orig is None:
_L(st, ' ERROR: decode failed'); return st
try:
cur = input_path
# S1: RT60 + DRR
rt60 = force_rt60 if force_rt60 > 0 else _rt60(s_orig)
st.rt60_initial = rt60; st.drr_before = _drr(s_orig)
_L(st, f' [S1] RT60={rt60:.2f}s DRR={st.drr_before:.1f}dB')
if rt60 < RT60_MIN:
_L(st, f' [S1] RT60 < {RT60_MIN}s β€” no processing needed')
_enc_stereo(input_path, output_path); return st
# S2 Sub-band LF EQ
cur = _lf_eq(cur, s_orig, rt60, st)
# S3 WPE
cur = _wpe(cur, rt60, st)
# S4 DF3 (parallel)
_s4 = _decode(cur); s4 = _s4 if _s4 is not None else s_orig
cur = _df3(cur, s4, rt60, st)
# S5 JALAA (DRR-weighted, corrected late window)
_s5 = _decode(cur); s5 = _s5 if _s5 is not None else s_orig
cur = _jalaa(cur, s5, rt60, st.drr_before, st)
# S6 Tail NR (JALAA-aware)
_s6 = _decode(cur); s6 = _s6 if _s6 is not None else s_orig
cur = _tailnr(cur, s6, rt60, st)
# S7 Arabic guards
cur = _arabic_guards(s_orig, cur, st)
# Final stereo encode + S8 volume boost + v4: presence lift 2kHz +1.5dB
rc, _, err = _run(['ffmpeg', '-y', '-i', cur,
'-af', ('volume=1.85,'
'equalizer=f=2000:width_type=o:width=1.0:g=1.5,'
'equalizer=f=300:width_type=o:width=1.0:g=-1.0,'
'alimiter=level_in=1:level_out=1:limit=0.89:attack=5:release=50'),
'-acodec', WAV_CODEC, '-ar', str(SR), '-ac', '2',
'-loglevel', 'error', output_path])
if rc:
_L(st, f' ERROR: final encode: {err[:80]}'); return st
sf_ = _decode(output_path)
if sf_ is not None: st.drr_after = _drr(sf_)
_L(st, f'\n{"═"*60}')
_L(st, f' الءفاؑ {__version__} βœ“')
_L(st, f' RT60 : {st.rt60_initial:.2f}s')
_L(st, f' DRR : {st.drr_before:.1f} β†’ {st.drr_after:.1f} dB '
f'(Ξ”{st.drr_after - st.drr_before:+.1f})')
_L(st, f' LF={st.lf_eq} WPE={st.wpe} DF3={st.df3} JALAA={st.jalaa} tailNR={st.tail_nr}')
_L(st, f' Reverts:{st.guard_reverts} Warns:{len(st.guard_warn)}/{len(st.guard_pass)+len(st.guard_warn)}')
_L(st, f'{"═"*60}\n')
return st
finally:
_cleanup_all(st) # [I8] always runs
# ─── CLI ──────────────────────────────────────────────────────────────────────
if __name__ == '__main__':
import argparse, json
ap = argparse.ArgumentParser(description=f'الءفاؑ {__version__} β€” Dereverberation Engine')
ap.add_argument('input')
ap.add_argument('output')
ap.add_argument('--tier', default='TIER_UNKNOWN')
ap.add_argument('--mujawwad', type=float, default=0.0)
ap.add_argument('--rt60', type=float, default=0.0, help='Force RT60 (0=auto)')
a = ap.parse_args()
st = process(a.input, a.output,
source_tier=a.tier, mujawwad_conf=a.mujawwad, force_rt60=a.rt60)
print('\n[REPORT]')
print(json.dumps({
'version': __version__,
'rt60': st.rt60_initial,
'drr_before': round(st.drr_before, 2),
'drr_after': round(st.drr_after, 2),
'drr_gain': round(st.drr_after - st.drr_before, 2),
'stages': {
'lf_eq': st.lf_eq,
'wpe': st.wpe,
'df3': st.df3,
'jalaa': st.jalaa,
'tail_nr': st.tail_nr,
},
'guard_reverts': st.guard_reverts,
'guard_pass': st.guard_pass,
'guard_warn': st.guard_warn,
}, indent=2, ensure_ascii=False))