以下是我现在正在使用的内容:
for (int i = 0, numSamples = soundBytes.length / 2; i < numSamples; i += 2)
{
// Get the samples.
int sample1 = ((soundBytes[i] & 0xFF) << 8) | (soundBytes[i + 1] & 0xFF); // Automatically converts to unsigned int 0...65535
int sample2 = ((outputBytes[i] & 0xFF) << 8) | (outputBytes[i + 1] & 0xFF); // Automatically converts to unsigned int 0...65535
// Normalize for simplicity.
float normalizedSample1 = sample1 / 65535.0f;
float normalizedSample2 = sample2 / 65535.0f;
float normalizedMixedSample = 0.0f;
// Apply the algorithm.
if (normalizedSample1 < 0.5f && normalizedSample2 < 0.5f)
normalizedMixedSample = 2.0f * normalizedSample1 * normalizedSample2;
else
normalizedMixedSample = 2.0f * (normalizedSample1 + normalizedSample2) - (2.0f * normalizedSample1 * normalizedSample2) - 1.0f;
int mixedSample = (int)(normalizedMixedSample * 65535);
// Replace the sample in soundBytes array with this mixed sample.
soundBytes[i] = (byte)((mixedSample >> 8) & 0xFF);
soundBytes[i + 1] = (byte)(mixedSample & 0xFF);
}
据我所知,这是该页面定义的算法的准确表示:http://www.vttoth.com/CMS/index.php/technical-notes/68
然而,只是混合声音和静音(全0)会产生非常明显听起来不正确的声音,也许最好将其描述为更高音和更响亮。
非常感谢您帮助我确定我是否正确实施了算法,或者我是否只需要采用不同的方法(不同的算法/方法)?
答案 0 :(得分:3)
在链接文章中,作者假定 A 和 B 来表示整个音频流。更具体地说, X 表示流 X 中所有样本的最大abs值 - 其中 X 是 A 或 B 。所以他的算法所做的是扫描两个流的全部以计算每个流的最大abs样本,然后对事物进行缩放,使得输出理论上达到峰值1.0。您需要对数据进行多次传递才能实现此算法,如果您的数据是流式传输,则它将无法正常工作。
以下是我认为算法如何工作的示例。它假定样本已经转换为浮点到侧面步骤,转换代码的问题是错误的。我稍后会解释它有什么问题:
double[] samplesA = ConvertToDoubles(samples1);
double[] samplesB = ConvertToDoubles(samples2);
double A = ComputeMax(samplesA);
double B = ComputeMax(samplesB);
// Z always equals 1 which is an un-useful bit of information.
double Z = A+B-A*B;
// really need to find a value x such that xA+xB=1, which I think is:
double x = 1 / (Math.sqrt(A) * Math.sqrt(B));
// Now mix and scale the samples
double[] samples = MixAndScale(samplesA, samplesB, x);
混合和缩放:
double[] MixAndScale(double[] samplesA, double[] samplesB, double scalingFactor)
{
double[] result = new double[samplesA.length];
for (int i = 0; i < samplesA.length; i++)
result[i] = scalingFactor * (samplesA[i] + samplesB[i]);
}
计算最大峰值:
double ComputeMaxPeak(double[] samples)
{
double max = 0;
for (int i = 0; i < samples.length; i++)
{
double x = Math.abs(samples[i]);
if (x > max)
max = x;
}
return max;
}
转换。请注意我如何使用short以便正确维护符号位:
double[] ConvertToDouble(byte[] bytes)
{
double[] samples = new double[bytes.length/2];
for (int i = 0; i < samples.length; i++)
{
short tmp = ((short)bytes[i*2])<<8 + ((short)(bytes[i*2+1]);
samples[i] = tmp / 32767.0;
}
return samples;
}