320 lines
12 KiB
C++
320 lines
12 KiB
C++
#include "whisper.h"
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#include "common.h"
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#define MINIAUDIO_IMPLEMENTATION
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#include "miniaudio.h"
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#include <vector>
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#include <cstdio>
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#include <string>
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#include <atomic>
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#include <chrono>
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#include <thread>
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#include <csignal>
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#include <cstdlib>
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#include <algorithm>
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#include <cstring>
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#include <mutex>
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// 全局原子变量（线程安全）
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std::atomic<bool> is_recording(false);
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std::atomic<bool> exit_program(false);
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std::atomic<int> recorded_seconds(0); // 实时录制时长
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// 音频缓冲区（加锁保护）
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std::vector<float> audio_buffer;
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std::mutex buffer_mutex;
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// 可选超时（默认60秒，可自定义）
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const int RECORD_TIMEOUT = 60; // 延长到60秒，也可设为0取消超时
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// 信号处理：Ctrl+C 优雅退出
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void signal_handler(int sig) {
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if (sig == SIGINT) {
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printf("\n\n🛑 收到退出信号，正在清理资源...\n");
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exit_program.store(true);
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is_recording.store(false);
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exit(0);
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}
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}
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// 音频回调（取消30秒帧上限）
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void data_callback(ma_device* pDevice, void* pOutput, const void* pInput, ma_uint32 frameCount) {
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if (!is_recording.load() || pInput == NULL) return;
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const float* pInputFloat = (const float*)pInput;
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if (pInputFloat == NULL) return;
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std::lock_guard<std::mutex> lock(buffer_mutex);
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// 取消固定帧上限，仅保留内存保护（可选）
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const size_t max_memory = 16000 * 120; // 最多120秒（约200MB内存）
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if (audio_buffer.size() < max_memory) {
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audio_buffer.insert(audio_buffer.end(), pInputFloat, pInputFloat + frameCount);
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// 更新实时录制时长
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recorded_seconds.store(audio_buffer.size() / 16000);
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}
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}
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// 静音检测（裁剪无效音频，减少识别量）
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int trim_silence(const float* audio_data, int audio_len, float threshold = 0.001f) {
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// 跳过开头静音
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int start = 0;
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while (start < audio_len && fabs(audio_data[start]) < threshold) {
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start++;
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}
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// 跳过结尾静音
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int end = audio_len - 1;
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while (end > start && fabs(audio_data[end]) < threshold) {
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end--;
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}
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// 返回有效音频长度（至少保留1秒）
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return std::max(end - start + 1, 16000);
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}
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// 列出系统音频设备
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void list_audio_devices(ma_context& context, ma_device_info** pCaptureInfos, ma_uint32& captureCount) {
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printf("\n📜 系统可用麦克风设备列表：\n");
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printf("=============================================\n");
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ma_result result = ma_context_get_devices(&context, NULL, NULL, pCaptureInfos, &captureCount);
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if (result != MA_SUCCESS) {
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fprintf(stderr, "❌ 获取设备列表失败，使用默认设备\n");
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*pCaptureInfos = NULL;
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captureCount = 0;
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return;
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}
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for (ma_uint32 i = 0; i < captureCount; ++i) {
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printf("🔧 设备ID: %u | 名称: %s\n", i, (*pCaptureInfos)[i].name);
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printf(" 声道数: 1 | 采样率: 16000 Hz\n");
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printf("---------------------------------------------\n");
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}
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printf("=============================================\n");
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}
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// 提示信息（修复printf多参数问题）
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void print_usage() {
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printf("=============================================\n");
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printf("🎤 语音识别程序（CPU优化版）\n");
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printf("操作说明：\n");
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printf(" 1. 按下【回车键】开始录制\n");
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printf(" 2. 说话完成后按回车停止录制并识别\n");
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printf(" 3. 录制超过%d秒自动停止（可自定义）\n", RECORD_TIMEOUT);
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printf(" 4. 录制中实时显示时长：【录制中... X秒】\n");
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printf(" 5. Ctrl+C 退出程序\n");
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printf("=============================================\n"); // 移除多余的RECORD_TIMEOUT参数
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}
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// CPU优化提示
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void print_cpu_optimize_tips() {
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printf("⚡ CPU优化配置说明：\n");
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printf(" ✅ 已启用多线程识别（自动适配CPU核心数）\n");
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printf(" ✅ 已启用静音裁剪（减少无效音频识别）\n");
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printf(" ✅ 已使用贪心采样（最快的识别策略）\n");
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printf(" 📌 模型优化：推荐使用 ggml-medium-q4_0.bin（量化版）\n");
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printf(" 📌 编译优化：已用 -O3 最高级优化\n");
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printf("=============================================\n");
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}
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int main(int argc, char** argv) {
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signal(SIGINT, signal_handler);
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if (argc < 2) {
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fprintf(stderr, "Usage: %s <model_path>\n", argv[0]);
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return 1;
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}
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const char* model_path = argv[1];
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// 1. 初始化音频上下文
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ma_context context;
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if (ma_context_init(NULL, 0, NULL, &context) != MA_SUCCESS) {
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fprintf(stderr, "❌ 初始化音频上下文失败\n");
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return 1;
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}
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// 2. 枚举麦克风设备
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ma_device_info* pCaptureInfos = NULL;
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ma_uint32 captureCount = 0;
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list_audio_devices(context, &pCaptureInfos, captureCount);
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// 3. 选择麦克风设备
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ma_uint32 device_id = 0;
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if (captureCount > 0) {
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printf("\n👉 请输入要使用的麦克风设备ID：");
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if (scanf("%u", &device_id) != 1 || device_id >= captureCount) {
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fprintf(stderr, "❌ 输入无效，使用默认设备ID 0\n");
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device_id = 0;
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}
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while (getchar() != '\n'); // 清空输入缓冲区
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}
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// 4. 初始化 Whisper 模型（CPU优化，移除不存在的use_flash_attention）
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struct whisper_context_params cparams = whisper_context_default_params();
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cparams.use_gpu = false; // 强制CPU（避免GPU检测开销）
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// 移除 cparams.use_flash_attention = false; （旧版本无此成员）
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printf("\n🚀 正在加载模型：%s\n", model_path);
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struct whisper_context* ctx = whisper_init_from_file_with_params(model_path, cparams);
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if (!ctx) {
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fprintf(stderr, "❌ 初始化Whisper模型失败\n");
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ma_context_uninit(&context);
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return 1;
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}
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// 显示CPU优化提示
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print_cpu_optimize_tips();
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printf("✅ 模型加载成功！\n");
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// 5. 初始化录音设备
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ma_device_config deviceConfig = ma_device_config_init(ma_device_type_capture);
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deviceConfig.capture.format = ma_format_f32;
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deviceConfig.capture.channels = 1;
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deviceConfig.sampleRate = 16000;
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deviceConfig.dataCallback = data_callback;
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deviceConfig.pUserData = NULL;
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if (captureCount > 0 && pCaptureInfos != NULL) {
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deviceConfig.capture.pDeviceID = &pCaptureInfos[device_id].id;
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printf("\n✅ 已选择麦克风：%s\n", pCaptureInfos[device_id].name);
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} else {
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printf("\n✅ 使用默认麦克风设备\n");
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}
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ma_device device;
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if (ma_device_init(&context, &deviceConfig, &device) != MA_SUCCESS) {
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fprintf(stderr, "❌ 打开录音设备失败\n");
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whisper_free(ctx);
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ma_context_uninit(&context);
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return 1;
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}
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if (ma_device_start(&device) != MA_SUCCESS) {
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fprintf(stderr, "❌ 启动录音设备失败\n");
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ma_device_uninit(&device);
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whisper_free(ctx);
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ma_context_uninit(&context);
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return 1;
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}
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print_usage();
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// 主循环
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while (!exit_program.load()) {
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printf("\n👉 按下回车键开始录制...\n");
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getchar();
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if (exit_program.load()) break;
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// 重置录制状态
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is_recording.store(true);
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recorded_seconds.store(0);
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{
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std::lock_guard<std::mutex> lock(buffer_mutex);
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audio_buffer.clear();
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}
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printf("🎙️ 正在录制（按回车停止，最长%d秒）...\n", RECORD_TIMEOUT);
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// 录制时长实时显示线程
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std::thread progress_thread([&]() {
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while (is_recording.load() && !exit_program.load()) {
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printf("\r📊 录制中... %d秒", recorded_seconds.load());
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fflush(stdout); // 强制刷新输出
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std::this_thread::sleep_for(std::chrono::seconds(1));
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}
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});
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// 等待用户停止录制（主线程监听，避免子线程输入阻塞）
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std::atomic<bool> stop_record(false);
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std::thread wait_thread([&]() {
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getchar();
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stop_record.store(true);
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is_recording.store(false);
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});
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// 超时控制（可选）
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auto start_time = std::chrono::steady_clock::now();
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while (!stop_record.load() && !exit_program.load()) {
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auto duration = std::chrono::duration_cast<std::chrono::seconds>(
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std::chrono::steady_clock::now() - start_time).count();
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if (RECORD_TIMEOUT > 0 && duration >= RECORD_TIMEOUT) {
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printf("\n⏱️ 录制超时（%d秒），自动停止\n", RECORD_TIMEOUT);
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is_recording.store(false);
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stop_record.store(true);
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break;
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}
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std::this_thread::sleep_for(std::chrono::milliseconds(100));
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}
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wait_thread.join();
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progress_thread.join();
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is_recording.store(false);
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printf("\n"); // 换行，清理进度显示
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if (exit_program.load()) break;
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// 检查录制数据
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std::vector<float> captured_audio;
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{
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std::lock_guard<std::mutex> lock(buffer_mutex);
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captured_audio = audio_buffer;
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}
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if (captured_audio.empty()) {
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printf("⚠️ 未采集到音频数据，请重新录制\n");
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continue;
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}
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// 优化1：静音裁剪（减少识别数据量）
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int valid_len = trim_silence(captured_audio.data(), captured_audio.size());
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float valid_seconds = (float)valid_len / 16000;
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printf("🔍 正在识别（有效音频长度：%.2f秒，原始：%.2f秒）...\n",
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valid_seconds, (float)captured_audio.size() / 16000);
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auto recognize_start = std::chrono::steady_clock::now();
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// 优化2：调整识别参数（CPU最优配置）
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whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
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wparams.language = "zh";
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wparams.n_threads = std::max(2, (int)std::thread::hardware_concurrency()); // 至少2线程
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wparams.print_progress = false;
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wparams.print_realtime = false;
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wparams.temperature = 0.0; // 最快的温度设置
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wparams.max_len = 0;
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wparams.translate = false;
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wparams.no_context = true;
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wparams.single_segment = true; // 单段识别（更快）
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wparams.print_special = false; // 不打印特殊字符
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wparams.token_timestamps = false; // 关闭时间戳（节省计算）
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// 执行识别（仅识别有效音频）
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if (whisper_full(ctx, wparams, captured_audio.data(), valid_len) != 0) {
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fprintf(stderr, "❌ 识别失败\n");
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continue;
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}
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// 输出识别结果
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auto recognize_duration = std::chrono::duration_cast<std::chrono::milliseconds>(
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std::chrono::steady_clock::now() - recognize_start).count();
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float speed = valid_seconds / (recognize_duration / 1000.0);
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printf("⏱️ 识别耗时：%.2f 秒 | 识别速度：%.2fx实时速度\n",
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recognize_duration / 1000.0, speed);
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const int n_segments = whisper_full_n_segments(ctx);
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if (n_segments == 0) {
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printf("📝 未识别到有效内容\n");
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} else {
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printf("📝 识别结果：\n");
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for (int i = 0; i < n_segments; ++i) {
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const char* text = whisper_full_get_segment_text(ctx, i);
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printf(" %s\n", text);
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}
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}
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}
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// 清理资源
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ma_device_uninit(&device);
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ma_context_uninit(&context);
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whisper_free(ctx);
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printf("✅ 资源清理完成，程序退出\n");
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return 0;
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}
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