Songlib: built-in filters

Song Li Buser

Revision Date: November 7, 2011

Printable Version

The following filters come with the songlib system. For information on how to use them, see filters.


void lowPass(int *data,int length,double frequency,double resonance);

This filter removes the higher frequencies from the audio data. Frequencies above the given frequency are severely attenuated. According to the website, the resonance parameter should be between sqrt(2) (lowest resonance) to 0.1 (highest resonance), assuming frequency is greater than three or four kilohertz. For more info on acoustic resonance, see

4000 : the 1kHz - 4kHz mid frequency band is where the human ear is most sensitive

1.414 : the square root of 2 (1.414) is the ratio between the average and peak values of a sine wave


   void highPass(int *data,int length,double frequency,double resonance);

Like lowPass but attenuates frequencies below the given frequency.


    void amplify(int *data,int length,double amp);

This filters scales all the values in data by amp. If amp is greater than one, the effect will be to increase the volume. Conversely, a value less than one will decrease the volume.


    void attackLinear(int *data,int length,double amp,double delta)

There are two important cases for this filter. The first case is:

    amp < 1 and delta > 0

This softens the first part of the note. Sample i is scaled thusly:

    if (amp + delta * i < 1)
	i = i * (amp + delta * i);

The first sample is scaled the most, the second a little less, the third, a little less yet, and so on.

The other important case is:

    amp > 1 and delta < 0

This increases the loundess of the first part of the note. Sample i is scaled thusly:

    if (amp + delta * i > 1)
	i = i * (amp + delta * i);

Here are two typical calls:




    void attackExponential(int *data,int length,double amp,double delta);

Like attackLinear only the ramp is exponential. Sample i is scaled as follows:

    i = i * amp * pow(delta,i);

Here are two typical calls:




    void diminishLinear(int *data,int length,int offset,double delta);

    void diminishExponential(int *data,int length,int offset,double factor);

Like the attack filters, but works on the end of the data rather than the beginning. Sample i is updated thusly:

    i = i * (1 + delta * i);  //linear

    i = i * pow(factor,i);    //exponential


    distort1(int *data,int length,int cutoff);

    distort2(int *data,int length,int cutoff);

    distort3(int *data,int length,int cutoff,double level);

Three filters for adding distortion.