Keep baseline TTS ASR evaluation unchanged and retain failed-audio evidence

Signed-off-by: tzhouam <tzhouam@connect.ust.hk>

tests/e2e/online_serving/test_qwen3_tts_customvoice_expansion.py

@@ -148,9 +148,6 @@ def test_sample_rate_001(omni_server, online_client) -> None:
         "stream": False,
         "response_format": "wav",
         "sample_rate": 8000,
-        # Whisper-small can mishear the narrowband "kilohertz" pronunciation.
-        # Recheck the same WAV with stronger ASR, preserving the 0.9 gate.
-        "transcript_escalation_model": "large-v3",
         "task_type": "CustomVoice",
         "voice": "vivian",
     }

tests/helpers/tests/test_assertions.py

@@ -40,56 +40,6 @@ def test_short_transcript_unrelated_text_still_fails():
         )
 
 
-@pytest.mark.parametrize("result", ["small_matches", "strong_matches", "both_mismatch", "wrong_sample_rate"])
-def test_qwen3_tts_narrowband_asr_preserves_content_and_sample_rate_gates(monkeypatch, result):
-    from tests.e2e.online_serving import test_qwen3_tts_customvoice_expansion as speech
-
-    expected = "This response should be encoded as eight kilohertz audio."
-    sample_rate = 24_000 if result == "wrong_sample_rate" else 8000
-    buffer = io.BytesIO()
-    with wave.open(buffer, "wb") as wav:
-        wav.setnchannels(1)
-        wav.setsampwidth(2)
-        wav.setframerate(sample_rate)
-        wav.writeframes(_pcm_sine(sample_rate=sample_rate))
-    audio_bytes = buffer.getvalue()
-    models = []
-
-    def transcribe(raw_bytes, model_size="small", language=None):
-        assert raw_bytes == audio_bytes
-        models.append(model_size)
-        if result == "small_matches":
-            return expected
-        if model_size == "large-v3" and result == "strong_matches":
-            return "This response should be encoded as 8kHz audio."
-        return "This response should be encoded as 8K red audio."
-
-    monkeypatch.setattr(assertions, "convert_audio_bytes_to_text", transcribe)
-    monkeypatch.setattr(assertions, "_assert_preset_voice_gender_from_audio", lambda *_args, **_kwargs: None)
-
-    def request(config):
-        assert config["input"] == expected
-        assert_audio_speech_response(
-            OmniResponse(success=True, audio_bytes=audio_bytes, audio_format="audio/wav"), config, "full_model"
-        )
-
-    client = SimpleNamespace(send_audio_speech_request=request)
-    error = {
-        "both_mismatch": "after ASR escalation",
-        "wrong_sample_rate": "Expected sample_rate=8000",
-    }.get(result)
-    expectation = pytest.raises(AssertionError, match=error) if error else nullcontext()
-    with expectation:
-        speech.test_sample_rate_001(SimpleNamespace(model=speech.MODEL), client)
-    expected_models = {
-        "small_matches": ["small"],
-        "strong_matches": ["small", "large-v3"],
-        "both_mismatch": ["small", "large-v3"],
-        "wrong_sample_rate": [],
-    }[result]
-    assert models == expected_models
-
-
 def _capture_transcribe(monkeypatch) -> dict:
     captured: dict = {}