tts-voice-creator-clone-and.../tests/test_audio_problems.py
mARTin-B78 a0cd7b867f feat(voices): show audio problems in the voice library
Single-voice health endpoint (GET /api/voices/{id}/health), problems stored in
meta on import, shown in the Try-out voice panel; architecture note and docs.

Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
2026-10-04 16:35:10 +02:00

71 lines
2.7 KiB
Python

"""audio_problems: silence gap, clipped burst, level jump, clean signal."""
import sys
from pathlib import Path
import unittest
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
from pydub import AudioSegment
from pydub.generators import Sine, Square
from core.audio import audio_problems
SR = 24000
def tone(ms, gain=-20):
return Sine(300, sample_rate=SR).to_audio_segment(ms).apply_gain(gain)
def kinds(seg):
return {p["kind"] for p in audio_problems(seg)}
class AudioProblemTests(unittest.TestCase):
def test_clean(self):
self.assertEqual(audio_problems(tone(4000, -18).set_frame_rate(SR)), [])
def test_silence_gap(self):
seg = tone(2000) + AudioSegment.silent(2000, frame_rate=SR) + tone(2000)
p = [x for x in audio_problems(seg) if x["kind"] == "silence"]
self.assertEqual(len(p), 1)
self.assertAlmostEqual(p[0]["start_s"], 2.0, delta=0.1)
def test_edge_silence_ignored(self):
seg = AudioSegment.silent(3000, frame_rate=SR) + tone(2000) + AudioSegment.silent(3000, frame_rate=SR)
self.assertNotIn("silence", kinds(seg))
def test_clipping(self):
burst = Square(300, sample_rate=SR).to_audio_segment(400).apply_gain(+10)
seg = tone(2000) + burst + tone(2000)
p = [x for x in audio_problems(seg) if x["kind"] == "clipping"]
self.assertTrue(p)
self.assertAlmostEqual(p[0]["start_s"], 2.0, delta=0.1)
def test_level_jump(self):
seg = tone(2000, -40) + tone(2000, -10)
p = [x for x in audio_problems(seg) if x["kind"] == "level_jump"]
self.assertEqual(len(p), 1)
self.assertAlmostEqual(p[0]["start_s"], 2.0, delta=0.1)
class VoiceHealthTests(unittest.TestCase):
def test_analyze_and_stored(self):
import tempfile
from core.voice import _voice_health, _validate_voice_meta
with tempfile.TemporaryDirectory() as d:
wav = Path(d) / "EN_F_test.wav"
(tone(2000) + AudioSegment.silent(2000, frame_rate=SR) + tone(2000)).export(str(wav), format="wav")
h = _voice_health(wav, meta={}, transcript="hi", duration=6.0, analyze=True)
self.assertEqual([p["kind"] for p in h["problems"]], ["silence"])
self.assertIn("Long silence in reference audio", h["warnings"])
stored = _voice_health(wav, meta={"audio_problems": h["problems"]}, transcript="hi", duration=6.0)
self.assertEqual(stored["problems"], h["problems"])
self.assertEqual(_voice_health(wav, meta={}, transcript="hi", duration=6.0)["problems"], [])
with self.assertRaises(ValueError):
_validate_voice_meta({"audio_problems": "x"})
if __name__ == "__main__":
unittest.main()