Sound Sampling Algorithms

Hello there. In this blog, I will show you few approaches to do sound sampling in C language.

I will not be taking WAV, MP3, or any other file formats, instead I will generate numbers randomly and use it as a sound input. Reason because I am not using WAV or any other format because the main purpose of this blog is to see how we can process big chunk of data in just few seconds with System efficiency. By system efficiency I mean, using resource of a System like Memory and CPU as low as possible. So, Let’s Begin with some basics. 

Basics 

Above is the Header information of the Wav file. Until the byte 44, all the information is related to specification of the Wav file. Actual samples start after byte 45.

For more information on the Wav format, here is the link Link

This is the actual WAV file

What Exactly I am going to do?

I am going through few approaches to build different algorithms. But question is what exactly I am going to do? I will code three different approaches adjusting the volume of a sequence of sound samples. Here, I will have 20,00,00,000 length of 16bit signed integer array which will have values between -32768 to 32767 as my sound samples. I will have to calculate those sound samples by the Volume . This is like user is adjusting volume on a device. 

Simple Approach

Code:

Compiler Argument: gcc -O1 -o output program.c

This code is simple approach and following is the result.

Optimization	Time Elapsed (mSecond)	Memory Usage (MB)
0	741	391.996
1	261	392.160
2	268	392.160
3	229	392.160

Above table shows when I use optimization level 3 , program’s elapsed time decreased by 30% and Memory usage fairly stays the same.

Compiler Argument to see Memory and CPU usage : “command time -v ./output “.

Below is the screen shout of how output looks like.

 Note: Package “command” may not be installed by default on your server. you can get it by apt-get on most of the Ubuntu distribution.

Table Look Up

In table look up approach, I pre-calculated the samples from 0 to 32768 by Volume.

This is the code:

For this approach the elapsed time and memory usage were significantly changed. This algorithm take more time and memory than simple approach.

Optimization	Time Elapsed (Second)	Memory Usage (MB)
0	2.121	782.284
1	1.180	782.760
2	1.117	782.760
3	1.117	782.856

Memoization

In this approach, main purpose is to eliminate repeating calculations. Once we calculate a sample by Volume factor, we store it in the array and next time use it instead of Multiplying.

Below is how code looks like. 

Optimization	Time Elapsed (Second)	Memory Usage (MB)
0	2.847	782.692
1	0.679	782.764
2	0.547	782.736
3	0.545	782.760

This approach cost us less time compare to the table lookup. In average, out of 20,00,00,000 total samples only 41,905 time calculation happen and all the other values just got copied from an array . So, this is the fairly improvement in terms of CPU stress.