如何找到两个不同音频样本之间的标度?

本文介绍了如何找到两个不同音频样本之间的标度?的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我打算开发一个通用应用程序来分析音频样本.当我说通用"时，我的意思是任何技术(Javascript，C，Java等)都可以使用它. 基本上，我使用Apple的AVFoundation在iOS上创建了一个应用程序，该应用程序实时接收长度为512(bufferSize = 512)的麦克风采样. 在Python上，我使用PyAudio做了同样的事情，但是不幸的是，我收到了非常不同的值...

I'm planning to make an universal application that analyses audio samples. When I say 'universal' I mean that any technology (Javascript, C, Java, etc) can use it. Basically I made an application on iOS, using Apple's AVFoundation, that receives on real time the microphone samples at a lenght of 512 (bufferSize = 512). At Python I made the same thing, using PyAudio, but unfortunately I received very different values...

看样品:

Samples of bufferSize = 512 on iOS: [0.0166742969, 0.0181432627, 0.0184620395, 0.0182254426, 0.0181945376, 0.0185530782, 0.0192517322, 0.0199078992, 0.0204724055, 0.0212812237, 0.022370765, 0.0230008475, 0.0225516111, 0.0213304944, 0.0200473778, 0.019841563, 0.0206818394, 0.0211550407, 0.0207783803, 0.020227218 .... Samples of bufferSize = 512 on Python: [ -52. -32. -11. 10. 24. 31. 37. 38. 33. 25. 10. -4. -18. -26. -29. -39. ....

更多:

pastebin/jrM2VWXR

Python代码:

gist.github/denisb411/7c6f601175e8bb9f735d8aa43a0db340

在两种情况下，我都使用同一台计算机.

On both cases I used the same computer.

我如何找到一种将它们转换"(不知道这是否是正确的词)到相同规模的方法?

How do I find a way to 'convert'(don't know if this is the proper word) them to the same scale?

如果不清楚我的问题，请通知我.

If I wasn't clear at the question please notify me.

推荐答案

音频样本通常以16或24位进行量化.但是这些样本可以采用的值范围有不同的约定:

Audio samples are typically quantized on 16 or 24 bits. But there are different conventions about the range of values these samples can take:

• 如果要量化8位，则样本通常会存储为0到255之间的无符号字节
• 如果您要量化16位，则样本通常将存储为2的补码有符号整数，范围从-32768到32767
• 如果您要量化24位，则样本通常会存储为无符号整数
• 等

基本上，当您决定存储样本时，有两个参数:

Basically, when you decide to store samples, you have two parameters:

• 已签名或未签名
• int或float

每个都有其优点和缺点.例如，将浮点数存储在[-1，1]范围内的优点是两个样本相乘将始终在[-1，1]的范围内……

Each has its advantages and drawbacks. For instance, storing in a float in the range [-1, 1] has the advantage that multiplying two samples will always be in the same range of [-1, 1]…

因此，要回答您的问题，只需更改打开 PyAudio 流的格式.当前，您使用format=pyaudio.paInt16.尝试更改它pyaudio.paFloat32，您应该获得与iOS实施相同的数据.

So, to answer your question, you just need to change the format with which you open your PyAudio stream. Currently, you use format=pyaudio.paInt16. Try to change it pyaudio.paFloat32 and you should get the same data as with your iOS implementation.