""" ASR 服务单元测试 TDD 测试用例 - 基于 DevelopmentPlan.md 的验收标准 验收标准： - 字错率 (WER) ≤ 10% - 时间戳精度 ≤ 100ms """ import pytest from typing import Any # 导入待实现的模块（TDD 红灯阶段） # from app.services.ai.asr import ASRService, ASRResult, ASRSegment class TestASRService: """ASR 服务测试""" @pytest.mark.ai @pytest.mark.unit def test_asr_service_initialization(self) -> None: """测试 ASR 服务初始化""" # TODO: 实现 ASR 服务 # service = ASRService() # assert service.is_ready() # assert service.model_name is not None pytest.skip("待实现：ASR 服务初始化") @pytest.mark.ai @pytest.mark.unit def test_asr_transcribe_audio_file(self) -> None: """测试音频文件转写""" # TODO: 实现音频转写 # service = ASRService() # result = service.transcribe("tests/fixtures/audio/sample.wav") # # assert result.status == "success" # assert result.text is not None # assert len(result.text) > 0 pytest.skip("待实现：音频转写") @pytest.mark.ai @pytest.mark.unit def test_asr_output_format(self) -> None: """测试 ASR 输出格式""" # TODO: 实现 ASR 服务 # service = ASRService() # result = service.transcribe("tests/fixtures/audio/sample.wav") # # # 验证输出结构 # assert hasattr(result, "text") # assert hasattr(result, "segments") # assert hasattr(result, "language") # assert hasattr(result, "duration_ms") # # # 验证 segment 结构 # for segment in result.segments: # assert hasattr(segment, "text") # assert hasattr(segment, "start_ms") # assert hasattr(segment, "end_ms") # assert hasattr(segment, "confidence") # assert segment.end_ms >= segment.start_ms pytest.skip("待实现：ASR 输出格式") class TestASRAccuracy: """ASR 准确率测试""" @pytest.mark.ai @pytest.mark.unit def test_word_error_rate_threshold(self) -> None: """ 测试字错率阈值 验收标准：WER ≤ 10% """ # TODO: 使用标注测试集验证 # service = ASRService() # test_cases = load_asr_labeled_dataset() # # total_errors = 0 # total_words = 0 # # for case in test_cases: # result = service.transcribe(case["audio_path"]) # wer = calculate_word_error_rate( # result.text, # case["ground_truth"] # ) # total_errors += wer * len(case["ground_truth"]) # total_words += len(case["ground_truth"]) # # overall_wer = total_errors / total_words # assert overall_wer <= 0.10, f"WER {overall_wer:.2%} 超过阈值 10%" pytest.skip("待实现：WER 测试") @pytest.mark.ai @pytest.mark.unit @pytest.mark.parametrize("audio_type,expected_wer_threshold", [ ("clean_speech", 0.05), # 清晰语音 WER < 5% ("background_music", 0.10), # 背景音乐 WER < 10% ("multiple_speakers", 0.15), # 多人对话 WER < 15% ("noisy_environment", 0.20), # 嘈杂环境 WER < 20% ]) def test_wer_by_audio_type( self, audio_type: str, expected_wer_threshold: float, ) -> None: """测试不同音频类型的 WER""" # TODO: 实现分类型 WER 测试 # service = ASRService() # test_cases = load_asr_test_set_by_type(audio_type) # # wer = calculate_average_wer(service, test_cases) # assert wer <= expected_wer_threshold pytest.skip(f"待实现：{audio_type} WER 测试") class TestASRTimestamp: """ASR 时间戳测试""" @pytest.mark.ai @pytest.mark.unit def test_timestamp_monotonic_increase(self) -> None: """测试时间戳单调递增""" # TODO: 实现时间戳验证 # service = ASRService() # result = service.transcribe("tests/fixtures/audio/sample.wav") # # prev_end = 0 # for segment in result.segments: # assert segment.start_ms >= prev_end, \ # f"时间戳不是单调递增: {segment.start_ms} < {prev_end}" # prev_end = segment.end_ms pytest.skip("待实现：时间戳单调递增") @pytest.mark.ai @pytest.mark.unit def test_timestamp_precision(self) -> None: """ 测试时间戳精度 验收标准：精度 ≤ 100ms """ # TODO: 使用标注测试集验证 # service = ASRService() # test_cases = load_timestamp_labeled_dataset() # # total_error = 0 # total_segments = 0 # # for case in test_cases: # result = service.transcribe(case["audio_path"]) # for i, segment in enumerate(result.segments): # if i < len(case["ground_truth_timestamps"]): # gt = case["ground_truth_timestamps"][i] # start_error = abs(segment.start_ms - gt["start_ms"]) # end_error = abs(segment.end_ms - gt["end_ms"]) # total_error += (start_error + end_error) / 2 # total_segments += 1 # # avg_error = total_error / total_segments if total_segments > 0 else 0 # assert avg_error <= 100, f"平均时间戳误差 {avg_error:.0f}ms 超过阈值 100ms" pytest.skip("待实现：时间戳精度测试") @pytest.mark.ai @pytest.mark.unit def test_timestamp_within_audio_duration(self) -> None: """测试时间戳在音频时长范围内""" # TODO: 实现边界验证 # service = ASRService() # result = service.transcribe("tests/fixtures/audio/sample.wav") # # for segment in result.segments: # assert segment.start_ms >= 0 # assert segment.end_ms <= result.duration_ms pytest.skip("待实现：时间戳边界验证") class TestASRLanguage: """ASR 语言处理测试""" @pytest.mark.ai @pytest.mark.unit def test_chinese_mandarin_recognition(self) -> None: """测试普通话识别""" # TODO: 实现普通话测试 # service = ASRService() # result = service.transcribe("tests/fixtures/audio/mandarin.wav") # # assert result.language == "zh-CN" # assert "你好" in result.text or len(result.text) > 0 pytest.skip("待实现：普通话识别") @pytest.mark.ai @pytest.mark.unit def test_mixed_language_handling(self) -> None: """测试中英混合语音处理""" # TODO: 实现混合语言测试 # service = ASRService() # result = service.transcribe("tests/fixtures/audio/mixed_cn_en.wav") # # # 应能识别中英文混合内容 # assert result.status == "success" pytest.skip("待实现：中英混合识别") @pytest.mark.ai @pytest.mark.unit def test_dialect_handling(self) -> None: """测试方言处理""" # TODO: 实现方言测试 # service = ASRService() # # # 方言可能降级处理或提示 # result = service.transcribe("tests/fixtures/audio/cantonese.wav") # # if result.status == "success": # assert result.language in ["zh-CN", "zh-HK", "yue"] # else: # assert result.warning == "dialect_detected" pytest.skip("待实现：方言处理") class TestASRSpecialCases: """ASR 特殊情况测试""" @pytest.mark.ai @pytest.mark.unit def test_silent_audio(self) -> None: """测试静音音频""" # TODO: 实现静音测试 # service = ASRService() # result = service.transcribe("tests/fixtures/audio/silent.wav") # # assert result.status == "success" # assert result.text == "" or result.segments == [] pytest.skip("待实现：静音音频处理") @pytest.mark.ai @pytest.mark.unit def test_very_short_audio(self) -> None: """测试极短音频 (< 1秒)""" # TODO: 实现极短音频测试 # service = ASRService() # result = service.transcribe("tests/fixtures/audio/short_500ms.wav") # # assert result.status == "success" pytest.skip("待实现：极短音频处理") @pytest.mark.ai @pytest.mark.unit def test_long_audio(self) -> None: """测试长音频 (> 5分钟)""" # TODO: 实现长音频测试 # service = ASRService() # result = service.transcribe("tests/fixtures/audio/long_10min.wav") # # assert result.status == "success" # assert result.duration_ms >= 600000 # 10分钟 pytest.skip("待实现：长音频处理") @pytest.mark.ai @pytest.mark.unit def test_corrupted_audio_handling(self) -> None: """测试损坏音频处理""" # TODO: 实现错误处理测试 # service = ASRService() # result = service.transcribe("tests/fixtures/audio/corrupted.wav") # # assert result.status == "error" # assert "corrupted" in result.error_message.lower() or \ # "invalid" in result.error_message.lower() pytest.skip("待实现：损坏音频处理") class TestASRPerformance: """ASR 性能测试""" @pytest.mark.ai @pytest.mark.performance def test_transcription_speed(self) -> None: """ 测试转写速度 验收标准：实时率 ≤ 0.5 (转写时间 / 音频时长) """ # TODO: 实现性能测试 # import time # # service = ASRService() # # # 60秒测试音频 # start_time = time.time() # result = service.transcribe("tests/fixtures/audio/60s_sample.wav") # processing_time = time.time() - start_time # # audio_duration = result.duration_ms / 1000 # real_time_factor = processing_time / audio_duration # # assert real_time_factor <= 0.5, \ # f"实时率 {real_time_factor:.2f} 超过阈值 0.5" pytest.skip("待实现：转写速度测试") @pytest.mark.ai @pytest.mark.performance def test_concurrent_transcription(self) -> None: """测试并发转写""" # TODO: 实现并发测试 # import asyncio # # service = ASRService() # # async def transcribe_one(audio_path: str): # return await service.transcribe_async(audio_path) # # # 并发处理 5 个音频 # tasks = [ # transcribe_one(f"tests/fixtures/audio/sample_{i}.wav") # for i in range(5) # ] # results = await asyncio.gather(*tasks) # # assert all(r.status == "success" for r in results) pytest.skip("待实现：并发转写测试")