在没有剪辑的情况下将音频样本添加到其中的正确方法是什么?

我在不同频率(正弦/锯齿/三角形生成器)中产生声音样本作为一个双值数组[-1…1 ]。我想把所有信号合并成一个。

1)如果我添加( 组合规格化 )最后标准化为[-1…1]-音质良好,但信号太安静。

2)如果我使用线性( 联合线性压缩 )或日志( 组合式压缩 )压缩信号更大,但质量很差(金属声)。 我做错什么了?我想我错过了处理步骤。 在创建最终文件时添加来自多个源wav文件的音频信号的一般可接受算法是什么(Yamaha等合成器为此使用哪些方法)?

附加的 以下内容:

-我生成的音频(组合两个示例:top-combinewithnormalize、bottom-combinewithndynarangecompression)。顶部信号是安静的,但正确。底部-更大声,但可怕。 audio samples

-Java代码(草稿,未优化):

// add samples and linear normalize to [-1,1]
public static double[] combineWithNormalize( double[]... audio) {
    if (audio.length == 0) return null;
    if (audio.length == 1) return audio[0];

    int maxIdx = 0;
    // look for the longest sample
    for(double[] arr: audio)
        if (arr.length > maxIdx) maxIdx = arr.length;

    // add 0 to the end of short samples
    for(int i=0; i < audio.length; i++)
        if (audio[i].length < maxIdx) audio[i] = Arrays.copyOf(audio[i], maxIdx);

    // add all samples to result (+ find absolute max value)
    double[] result = new double[maxIdx];
    double normalizer  = 1.0;
    for (int i = 0; i < maxIdx; i++) {
        for (int j = 0; j < audio.length; j++)
            result[i] += audio[j][i];
        double res = Math.abs(result[i]);
        if (res > normalizer)
            normalizer = res;
    }

    //normalize rezult
    double coeff = 1.0/ normalizer;
    if (normalizer !=1.0)
        for (int i = 0; i < maxIdx; i++)
            result[i] *= coeff;
    return result;
}

// add samples and liners compression (all samples must be [-1..1])
public static double[] combineWithLinearDynaRangeCompression(double threshold, double[]... audio) {
    if (audio.length == 0 || threshold >= 1 || threshold < 0) return null;
    if (audio.length == 1) return audio[1];
    int maxIdx = 0;

    // look for the longest sample
    for(double[] arr: audio)
        if (arr.length > maxIdx) maxIdx = arr.length;

    // add 0 to the end of short samples
    for(int i=0; i < audio.length; i++)
        if (audio[i].length < maxIdx) audio[i] = Arrays.copyOf(audio[i], maxIdx);

    double[] result = Arrays.copyOf(audio[0], maxIdx); // Copy first sample
    double linearCoeff  = (1-threshold)/(2-threshold);

    // Add all samples to first + compression
    for (int j = 0; j < maxIdx; j++) {
        double res = 0;
        for (int i = 1; i < audio.length; i++)
            res =  result[j] + audio[i][j];
        double absRes = Math.abs(res);
        result[j] = (absRes <= threshold) ? res :  Math.signum(res) * (threshold + linearCoeff * (absRes - threshold));
    }
    return result;
}

// add samples and log compression (all samples must be [-1..1])
public static double[] combineWithLnDynaRangeCompression(double threshold, double[]... audio) {
    if (audio.length == 0 || threshold >= 1 || threshold < 0) return null;
    if (audio.length == 1) return audio[0];
    int maxIdx = 0;

    // look for the longest sample
    for(double[] arr: audio)
        if (arr.length > maxIdx) maxIdx = arr.length;

    // add 0 to the end of short samples
    for(int i=0; i < audio.length; i++)
        if (audio[i].length < maxIdx) audio[i] = Arrays.copyOf(audio[i], maxIdx);

    double[] result = Arrays.copyOf(audio[0], maxIdx); // Copy first sample
    double expCoeff = alphaT[(int) threshold*100];

    // Add all samples to first + compression
    for (int j = 0; j < maxIdx; j++) {
        double res = 0;
        for (int i = 1; i < audio.length; i++)
            res =  result[j] + audio[i][j];
        double absRes = Math.abs(res);
        result[j] = (absRes <= threshold) ? res :
                Math.signum(res) * (threshold + ( 1 - threshold) *
                    Math.log(1.0 + expCoeff * (absRes-threshold) /(2-threshold)) /  Math.log(1.0 + expCoeff ));
    }
    return result;
}

// Solutions of equations  pow(1+x,1/x)=exp((1-t)/(2-t)) for t=0, 0.01, 0.02 ... 0.99
final private static double[] alphaT =
        {
                2.51286, 2.54236, 2.57254, 2.60340, 2.63499, 2.66731, 2.70040, 2.73428, 2.76899, 2.80454,
                2.84098, 2.87833, 2.91663, 2.95592, 2.99622, 3.03758, 3.08005, 3.12366, 3.16845, 3.21449,
                3.26181, 3.31048, 3.36054, 3.41206, 3.46509, 3.51971, 3.57599, 3.63399, 3.69380, 3.75550,
                3.81918, 3.88493, 3.95285, 4.02305, 4.09563, 4.17073, 4.24846, 4.32896, 4.41238, 4.49888,
                4.58862, 4.68178, 4.77856, 4.87916, 4.98380, 5.09272, 5.20619, 5.32448, 5.44790, 5.57676,
                5.71144, 5.85231, 5.99980, 6.15437, 6.31651, 6.48678, 6.66578, 6.85417, 7.05269, 7.26213,
                7.48338, 7.71744, 7.96541, 8.22851, 8.50810, 8.80573, 9.12312, 9.46223, 9.82527, 10.21474,
                10.63353, 11.08492, 11.57270, 12.10126, 12.67570, 13.30200, 13.98717, 14.73956, 15.56907, 16.48767,
                17.50980, 18.65318, 19.93968, 21.39661, 23.05856, 24.96984, 27.18822, 29.79026, 32.87958, 36.59968,
                41.15485, 46.84550, 54.13115, 63.74946, 76.95930, 96.08797, 125.93570, 178.12403, 289.19889, 655.12084
        };

提前谢谢。