静音检测

复制import subprocess
import json

# 使用 ffprobe 检测音频文件中的静音段（静音阈值 -50dB，最小静音时长 0.5 秒）
def detect_silence(audio_path: str, threshold: int = -50, duration: float = 0.5) -> list:
    cmd = [
        'ffprobe',
        '-f', 'lavfi',
        '-i', f"amovie={audio_path},astats=metadata=1:reset=1",
        '-show_entries', 'frame=pkt_pts_time:frame_tags=lavfi.astats.Mean_level',
        '-of', 'json',
        audio_path
    ]
    result = subprocess.run(cmd, capture_output=True, text=True)
    data = json.loads(result.stdout)
    
    # 简化示例：仅演示调用方式，实际需解析帧数据
    frames = data.get('frames', [])
    silences = []
    start = None
    for f in frames:
        level = float(f['tags'].get('lavfi.astats.Mean_level', 0))
        if level < threshold:
            if start is None:
                start = float(f['pkt_pts_time'])
        else:
            if start is not None:
                end = float(f['pkt_pts_time'])
                if end - start >= duration:
                    silences.append({'start': start, 'end': end})
                start = None
    return silences

# 示例调用
# silences = detect_silence('input.mp3')
# print(silences)  # [{'start': 1.2, 'end': 2.8}, ...]

复制package main

import (
	"fmt"
	"os/exec"
	"strings"
)

// detectSilence 调用 FFmpeg silencedetect 过滤器，返回静音段列表
func detectSilence(inputPath string, noiseThreshold string, minDuration string) ([]string, error) {
	cmd := exec.Command("ffmpeg",
		"-i", inputPath,
		"-af", fmt.Sprintf("silencedetect=noise=%s:d=%s", noiseThreshold, minDuration),
		"-f", "null",
		"-",
	)
	out, err := cmd.CombinedOutput()
	if err != nil {
		return nil, fmt.Errorf("ffmpeg failed: %w", err)
	}

	// 解析输出中的静音段行
	lines := strings.Split(string(out), "\n")
	var silences []string
	for _, line := range lines {
		if strings.Contains(line, "silence_start") || strings.Contains(line, "silence_end") {
			silences = append(silences, strings.TrimSpace(line))
		}
	}
	return silences, nil
}

func main() {
	silences, err := detectSilence("input.mp3", "-50dB", "0.5")
	if err != nil {
		fmt.Println("Error:", err)
		return
	}
	for _, s := range silences {
		fmt.Println(s)
	}
}

复制// 浏览器端：使用 Web Audio API 分析音频缓冲区中的静音段
function detectSilenceInBuffer(audioBuffer, threshold = 0.01, minSilenceSamples = 22050) {
    const channelData = audioBuffer.getChannelData(0);
    const silences = [];
    let start = null;

    for (let i = 0; i < channelData.length; i++) {
        const sample = Math.abs(channelData[i]);
        if (sample < threshold) {
            if (start === null) start = i;
        } else {
            if (start !== null) {
                const duration = i - start;
                if (duration >= minSilenceSamples) {
                    silences.push({
                        start: start / audioBuffer.sampleRate,
                        end: i / audioBuffer.sampleRate
                    });
                }
                start = null;
            }
        }
    }
    return silences;
}

// 示例：加载音频文件并检测
// const context = new AudioContext();
// fetch('audio.mp3').then(r => r.arrayBuffer()).then(buf =>
//     context.decodeAudioData(buf, buffer => {
//         const silences = detectSilenceInBuffer(buffer);
//         console.log(silences);
//     })
// );