BiQuadFilters vs. Personalized Filter - Harnessing the Power of the Javascript WebAudio API

As part of my downsampling process from 48kHz to 16kHz, I need a filter to prevent aliasing. Thankfully, the WebAudio API provides built-in filters that I can utilize:

biquadFilter = context.createBiquadFilter();
biquadFilter.type = "lowpass";
biquadFilter.frequency.value = 12000;
biquadFilter.Q.value = 3;

However, I have also developed a simple algorithm that accomplishes the same task:

//Order 3 - Indirect form 2
var a_coef = [1.000000000000000,  -0.965779713179161,   0.582644165984302 , -0.106017056545330];
var b_coef = [0.063855924532476,   0.191567773597429,   0.191567773597429,   0.063855924532476];

var z1 = 0; var z2 = 0; var z3 = 0; var z0 = 0;
for (var i = 0; i < buffer.length; i++) {
  z0 = buffer[i] + a_coef[1] * z1-a_coef[2] * z2-a_coef[3] * z3;
  buffer[i] = b_coef[0] * z0 + b_coef[1] * z1+b_coef[2] * z2 + b_coef[3] * z3;
  z3 = z2; z2 = z1; z1 = z0;
};

I am curious about which method consumes more resources. Were BiquadFilters written in native code for efficiency?

Answer №1

The BiquadFilters are meticulously crafted with native code, making them the optimal choice in nearly 100% of scenarios.

While JavaScript engines can perform impressive optimizations that bring JS close to native performance, it may not be the case here. To achieve significant performance gains, you must understand how to structure your code for optimization, a complex field in itself (for instance, avoiding variable declarations within loops is a good starting point).

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