feat: add ImageFind application and release pipelines

tests/test_speech_quality.py

@@ -0,0 +1,120 @@
+from __future__ import annotations
+
+from types import SimpleNamespace
+
+from imagefind.speech_quality import (
+    normalize_language,
+    pcm16_voiced_regions,
+    select_language,
+    transcript_quality,
+)
+
+
+def test_language_policy_treats_stream_metadata_as_weak_hint() -> None:
+    assert select_language(["en", "zh"], policy="zh_priority") == "zh"
+    assert select_language(["en", "zh"], policy="auto") == "en"
+    assert select_language(["en", "en"], policy="zh_priority", stream_language="zh-CN") == "zh"
+    assert select_language([], policy="zh_priority") == "zh"
+    assert select_language([], policy="zh_priority", stream_language="eng") == "zh"
+    assert select_language([], policy="auto", stream_language="eng") == "en"
+    assert normalize_language("<|zh|>") == "zh"
+
+
+def test_chinese_priority_rejects_weak_or_implausible_language_detection() -> None:
+    assert select_language(["jw", "nn", "jw"], policy="zh_priority") == "zh"
+    assert select_language(["en"], policy="zh_priority") == "zh"
+    assert select_language(["en", "en", "zh"], policy="zh_priority") == "zh"
+
+
+def test_chinese_priority_does_not_trust_short_korean_or_japanese_detection() -> None:
+    # Whisper's one-token detector commonly confuses short/noisy Mandarin
+    # clips with ko/ja.  Choosing that language makes the whole decode wrong.
+    assert select_language(["ko", "ko", "ko"], policy="zh_priority") == "zh"
+    assert select_language(["ja", "ja"], policy="zh_priority") == "zh"
+    assert select_language(["jw", "jw"], policy="auto") == "jw"
+
+
+def test_quality_accepts_normal_chinese_english_and_mixed_transcripts() -> None:
+    samples = (
+        ("这是一个正常的中文语音识别结果，包含完整的句子和清晰的信息。", "zh"),
+        ("This is a clear English transcript with enough useful information.", "en"),
+        ("今天我们 discuss ImageFind 的 audio search 功能。", "zh"),
+    )
+    for text, language in samples:
+        quality = transcript_quality(text, 12_000, speech_ratio=0.7, expected_language=language)
+        assert quality.accepted is True
+        assert quality.score >= 0.9
+        assert quality.flags == ()
+
+
+def test_quality_rejects_repeated_wrong_script_and_replacement_characters() -> None:
+    repeated = transcript_quality(
+        "කකකකකකකකකකකකකකකකකකකක",
+        12_000,
+        speech_ratio=0.7,
+        expected_language="zh",
+    )
+    damaged = transcript_quality(
+        "这是一段损坏的字幕�内容",
+        8_000,
+        speech_ratio=0.6,
+        expected_language="zh",
+    )
+    assert repeated.accepted is False
+    assert {"repeated_characters", "unexpected_script"}.issubset(repeated.flags)
+    assert damaged.accepted is False
+    assert "invalid_characters" in damaged.flags
+
+
+def test_quality_rejects_full_english_hallucination_when_chinese_is_forced() -> None:
+    result = transcript_quality(
+        "This entire segment was decoded in the wrong language.",
+        8_000,
+        speech_ratio=0.8,
+        expected_language="zh",
+    )
+    assert result.accepted is False
+    assert "language_script_conflict" in result.flags
+
+
+def test_quality_rejects_short_phrase_hallucination_but_accepts_silence() -> None:
+    hallucination = transcript_quality(
+        "谢谢观看",
+        30_000,
+        speech_ratio=0.01,
+        expected_language="zh",
+    )
+    silence = transcript_quality("", 30_000, speech_ratio=0.0, expected_language="zh")
+    assert hallucination.accepted is False
+    assert "short_hallucination" in hallucination.flags
+    assert silence.accepted is True
+    assert silence.units == 0
+
+
+def test_quality_does_not_reject_sparse_legitimate_speech_by_chunk_duration() -> None:
+    quality = transcript_quality("今天天气不错", 30_000, speech_ratio=0.08, expected_language="zh")
+    assert quality.accepted is True
+    assert "too_little_text" not in quality.flags
+
+
+def test_vad_regions_bridge_short_gaps_and_skip_short_noise(monkeypatch) -> None:
+    decisions = [False] * 4 + [True] * 10 + [False] * 8 + [True] * 10 + [False] * 20 + [True] * 3
+
+    class Detector:
+        def __init__(self, _mode):
+            self.index = 0
+
+        def is_speech(self, _frame, _sample_rate):
+            value = decisions[self.index]
+            self.index += 1
+            return value
+
+    monkeypatch.setitem(__import__("sys").modules, "webrtcvad", SimpleNamespace(Vad=Detector))
+    raw = b"\0\0" * 480 * len(decisions)
+    regions = pcm16_voiced_regions(raw, 16_000)
+
+    assert len(regions) == 1
+    start, end, ratio = regions[0]
+    assert start < 4 * 480
+    assert end > 32 * 480
+    assert 0 < ratio < 1