impressionyang
a3f1b1d9a6
- 新增 VoiceActivityDetector 基于能量+过零率的语音活动检测 - 引入 Catch2 单元测试框架 - 添加 4 个测试模块: AudioProcessor/VAD/MelSpectrogram/WhisperTokenizer - 从构建中移除废弃的 tokenizer/decoder 文件 - 39 个测试用例全部通过 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
126 lines
3.9 KiB
C++
126 lines
3.9 KiB
C++
#include <catch2/catch_test_macros.hpp>
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#include <catch2/matchers/catch_matchers_floating_point.hpp>
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#include "core/audio_processor.h"
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#include <cmath>
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#include <numeric>
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using namespace impress;
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using Catch::Matchers::WithinAbs;
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// ============================================================================
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// AudioProcessor 测试
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// ============================================================================
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TEST_CASE("归一化 PCM16 数据", "[audio_processor]") {
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std::vector<short> pcm16 = {0, 16384, -16384, 32767, -32768};
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auto normalized = AudioProcessor::normalize(pcm16);
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REQUIRE(normalized.size() == pcm16.size());
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REQUIRE_THAT(normalized[0], WithinAbs(0.0f, 1e-5f));
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REQUIRE_THAT(normalized[1], WithinAbs(0.5f, 1e-5f));
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REQUIRE_THAT(normalized[2], WithinAbs(-0.5f, 1e-5f));
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REQUIRE_THAT(normalized[3], WithinAbs(32767.0f / 32768.0f, 1e-5f));
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REQUIRE_THAT(normalized[4], WithinAbs(-1.0f, 1e-5f));
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}
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TEST_CASE("归一化全零 PCM16 数据", "[audio_processor]") {
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std::vector<short> pcm16(1000, 0);
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auto normalized = AudioProcessor::normalize(pcm16);
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for (float v : normalized) {
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REQUIRE_THAT(v, WithinAbs(0.0f, 1e-5f));
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}
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}
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TEST_CASE("浮点数据归一化", "[audio_processor]") {
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std::vector<float> input = {0.0f, 0.5f, -0.5f, 1.0f, -1.0f};
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auto normalized = AudioProcessor::normalizeFloats(input);
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// 最大绝对值为 1.0，所以数据不变
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REQUIRE_THAT(normalized[0], WithinAbs(0.0f, 1e-5f));
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REQUIRE_THAT(normalized[3], WithinAbs(1.0f, 1e-5f));
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REQUIRE_THAT(normalized[4], WithinAbs(-1.0f, 1e-5f));
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}
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TEST_CASE("浮点数据归一化 - 小值放大", "[audio_processor]") {
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std::vector<float> input = {0.001f, -0.002f, 0.003f};
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auto normalized = AudioProcessor::normalizeFloats(input);
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// 最大绝对值 0.003，归一化后最大值应为 1.0
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REQUIRE_THAT(normalized[2], WithinAbs(1.0f, 1e-5f));
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REQUIRE_THAT(normalized[0], WithinAbs(1.0f / 3.0f, 1e-4f));
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REQUIRE_THAT(normalized[1], WithinAbs(-2.0f / 3.0f, 1e-4f));
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}
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TEST_CASE("等采样率重采样 - 数据不变", "[audio_processor]") {
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AudioProcessor processor(16000);
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std::vector<float> input = {0.0f, 0.5f, -0.5f, 1.0f};
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auto output = processor.resample(input, 16000);
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REQUIRE(output.size() == input.size());
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for (size_t i = 0; i < input.size(); i++) {
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REQUIRE_THAT(output[i], WithinAbs(input[i], 1e-5f));
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}
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}
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TEST_CASE("上采样 - 样本数增加", "[audio_processor]") {
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AudioProcessor processor(32000);
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std::vector<float> input(1000, 0.5f);
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auto output = processor.resample(input, 16000);
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REQUIRE(output.size() == 2000); // 16k -> 32k = 2x
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// 恒定信号值不变
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REQUIRE_THAT(output[0], WithinAbs(0.5f, 1e-5f));
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REQUIRE_THAT(output[1999], WithinAbs(0.5f, 1e-5f));
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}
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TEST_CASE("下采样 - 样本数减少", "[audio_processor]") {
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AudioProcessor processor(8000);
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std::vector<float> input(2000, 0.5f);
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auto output = processor.resample(input, 16000);
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REQUIRE(output.size() == 1000); // 16k -> 8k = 0.5x
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REQUIRE_THAT(output[0], WithinAbs(0.5f, 1e-5f));
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}
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TEST_CASE("分帧 - 基本功能", "[audio_processor]") {
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AudioProcessor processor(16000);
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std::vector<float> input(1000, 1.0f);
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auto frames = processor.frame(input, 200, 100);
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// 帧数: (1000 - 200) / 100 + 1 = 9
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REQUIRE(frames.size() == 9);
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for (const auto& frame : frames) {
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REQUIRE(frame.size() == 200);
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}
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}
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TEST_CASE("分帧 - 输入不足一帧", "[audio_processor]") {
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AudioProcessor processor(16000);
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std::vector<float> input(50, 1.0f);
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auto frames = processor.frame(input, 200, 100);
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REQUIRE(frames.empty());
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}
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TEST_CASE("分帧 - 精确匹配", "[audio_processor]") {
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AudioProcessor processor(16000);
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std::vector<float> input(400, 1.0f);
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auto frames = processor.frame(input, 200, 200);
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REQUIRE(frames.size() == 2);
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for (const auto& frame : frames) {
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REQUIRE(frame.size() == 200);
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}
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}
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